Report No. 19217-BR Brazil Poverty Reduction, Growth, and Fiscal Stability in the State of Ceara' A State Economic Memorandum (In Two Volumes) Volume II: Annexes August 21, 2000 Brazil Country Management Unit PREM Sector Management Unit Latin America and the Caribbean Region Document of the World Bank CURRENCY EXCHANGE RATES (R$/US$) Currency Unit - Real (R$) December 1995: R$0.97/US$ December 1996: R$1.04/US$ December 1997: R$1.12/US$ December 1998: R$1.21/US$ December 1999: R$1.78/US$ July 2000: R$1.80/US$ WEIGHTS AND MEASURES The Metric System is used throughout the report. FISCAL YEAR January 1 to December 31 Vice President LCR: David de Ferranti Director LCC5C: Gobind T. Nankani Director LCSPR: Emesto May Lead Economist: Suman Bery Task Manager: Joachim von Amsberg Abbreviations and Acronyms ACC Associaq5o Comercial do Ceara BEC Ceara State Bank (Banco do Estado do Ceara) BID Interamerican Development Bank (Banco Interamericano de Desenvolvimento) BNB Northeast Regional Development Bank (Banco do Nordeste do Brasil) BNDES National Development Bank (Banco Nacional de Desenvolvimento Econ6mico e Social) CEDIM Conselho de Desenvolvimento Industrial do Ceara EMATERCE Ceara State's Technical Assistance and Rural Extension Agency (Empresa de Assistencia T6cnica e Extensao Rural do Ceara) EMBRATUR Brazilian Tourism Company (Empresa Brasileira de Turismo) EPZ Export Processing Zone (Zona de Processamento das Exportaq5es) ETENE Escrit6rio T6cnico de Estudos Econ6micos de Nordeste FDI Fundo de Desenvolvimento Industrial FGV Fundacao Getulio Vargas FIEC Federa,co das Industrias do Estado do Ceara IBGE Brazilian Institute of Geography and Statistics (Fundag,o Instituto Brasileiro de Geografia e Estatistica) ICMS Value Added Tax (Imposto de Circulag5o de Mercadorias e Servi,os) IFC International Finance Corporation IPEA Institute of Applied Economic Research (Instituto de Pesquisa Econ6mica Aplicada) IPLANCE Planning Institute of Ceara (Funda,co Instituto de Planejamento do Ceara) LSMS/PPV Living Standards Measurement Study (Pesquisa das Padroes da Vida) PME Monthly Employment Survey (Pesquisa Mensal de Emprego) PNAD National Household Survey (Pesquisa Nacional por Amostra dos Domicilios) PRODETUR Programa para o Desenvolvimento de Turismo SDE Secretaria de Desenvolvimento Economico SDR Secretaria de Desenvolvimento Rural SEBRAE/CE Servi,o de Apoio as Micro e Pequenas Empresas no Ceara SEFAZ Secretaria da Fazenda SEPLAN Ceara State Secretariat of Planning and Coordination (Secretaria do Planejamento e Coordena,co) SETUR Secretaria de Turismo SUDENE Superintend6ncia para o Desenvolvimento do Nordeste BRAZIL: POVERTY REDUCTION, GROWTH AND FISCAL STABILITY IN THE STATE OF CEARA Table of Contents 1. THE ECONOMY: IMPROVING COMPETITIVENESS . .8.... Executive Summary ................................................................. Introduction ...............................................................1.1 Recent Economic Growth and Future Prospects ........................................................ 12 Overview ............................................................... 12 Agriculture .............................................................. 15 Industry .............................................................. 16 Services: The Emergence of Tourism as a Leading Sector .................................... 21 Policy and Regulatory Environment .............................................................. 26 The National Policies Framework ............................................................... 26 State Fiscal or Financial Incentives .............................................................. 28 Government Investment Promotion .............................................................. 34 Summary of Major Recommendations .............................................................. 35 Export Processing Zone(s) and Bonded Customs Warehouses .............................. 35 ICMS-Related Incentives .............................................................. 36 Government Investment Promotion .............................................................. 37 Tourism .............................................................. 37 Infrastructure and Education .............................................................. 38 2. THE LAND: REVIVING THE RURAL ECONOMY ......... ............ 39 Introduction .............................................................. 40 Objectives .............................................................. 40 Structure of the Report .............................................................. 40 Data Sources .............................................................. 4.0 Background .............................................................. 40 Agricultural Sector Performance .............................................................. 42 Major Reduction in Farmed Area, Crop Cultivation, and Size of Livestock Herd .... 43 Changes in the Output Mix - their share in the sector's economy ........................... 45 On The Evolution Of Farm Prices .............................................................. 47 A Trend of Increased Farm Fragmentation ............................................................. 48 Tenancy and Farm Fragmentation .............................................................. 50 Production by Farm Size .............................................................. 52 Rural employment - the bulk of rural labor is self-employed .................................. 52 Yields, Technical Assistance, And Adoption Of Improved Technologies ................. 53 Water Resource Management and Irrigation Development .................................... 56 Rural Poverty in Ceara .............................................................. 58 Household Income Analysis (Northeast) .............................................................. 59 The Main Findings and Policy Implications .............................................................. 62 Agriculture's Performance - sharp decline in growth ....................... ....................... 62 Land productivity ............................................. 63 A Trend of Increased Farm Fragmentation ............................................. 63 Rural Labor - Mostly Self-Employed ............................................. 64 Water resource Management and Irrigation Development ...................................... 64 On Rural Poverty ............................................. 67 3. the people: reducing poverty ...................................... 70 Introduction ................................................ 7.1 Poverty in Ceara: the Facts ................................................ 72 A Brief History ................................................ 72 Aggregate Indicators and the Poverty Profile in 1996 ............................................. 75 Location ................................................ 79 Building the Assets of the Poor ................................................ 83 How it is being done ................................................. 83 How It Can Be Improved ................................................ 87 Increasing the returns on the assets of the poor ................................................ 90 Labor and Human Capital ................................................ 90 Land ................................................ 90 Protecting the Vulnerable in a Shock-Prone Economy ............................................... 90 How It Is Being Done ................................................ 90 How It Can Be Improved ................................................. 92 Conclusions and Some Tentative Recommendations ................................................ 93 4. THE STATE: MANAGING FISCAL STABILITY ........................ 96 State Fiscal Diagnosis, Outlook And Risks ........................................ 97 Background ............................................... 9.7 Revenues ............................................... 9.7 Expenditure Analysis by Economic Category ............................................... 100 5. BIBLIOGRAPHY ...................................... 107 6. STATISTICAL ANNEX .................. 113 Tables TABLE 1.1: GROWTH RATE COMPARISONS FOR NORTHEASTERN STATES, 1985-96 13 TABLE 1.2: SECTORAL COMPOSITION OF THE CEARENSE ECONOMY (% SHARES) 14 TABLE 1.3: CEARA: VALUE ADDED GROWTH RATES, 1970-80, 1980-90 AND 1990-96 (IN %)14 TABLE 1.4: PRODUCTION OF PRINCIPAL AGRICULTURAL PRODUCTS, SELECTED YEARS, 1970-97 (1970 = 100) 15 TABLE 1.5: CEARA: ANNUAL GROWTH RATES IN TOURIST DEMAND AND AIRPORT PASSENGER ARRIVALS (%) 24 TABLE 1.6: CEARA: TOURISM ESTIMATES AND PROJECTIONS, 1997-2001 24 TABLE 1.7: APPROVED PROJECTS UNDER THE ICMS-RELATED INCENTIVES, BY SECTOR, 1995-98 29 TABLE 1.8: NET DISBURSEMENTS OF THE ICMS-RELATED INCENTIVES, 1996 AND 1997 (IN MILLIONS OF CURRENT R$) 32 TABLE 1.9: AGGREGATE EFFECTIVE ICMS TAX RATES, 1996 AND 1997 (IN %) 33 TABLE 2.1: LAND USE IN 1985 AND 1995/96, IN ('000) HECTARES, CEARA. 43 TABLE 2.2: CHANGE IN CULTIVATED AREA AND LIVESTOCK FIGURES, FOR SELECTED PRODUCTS, IN CEARA. 44 TABLE 2.3: CHANGES IN THE PRODUCTION STRUCTURE, IN PERCENTAGES, CEARA. 46 TABLE 2.4: PRICE INDEXES FOR MAJOR CROPS AND LIVESTOCK PRODUCTS, CEARA. 47 TABLE 2.5: NUMBER AND AREA OF FARMS BY FARM SIZE, 1995/96, CEARA. 48 TABLE 2.6: EVOLUTION OF FARM DISTRIBUTION (NUMBER AND AREA) BY SIZE, CEARA.49 TABLE 2.7: TENANCY DISTRIBUTION (%), IN CEARA. 51 TABLE 2.8: SHARE IN VALUE OF PRODUCTION BY FARM SIZE (1995/96), CEARA. 52 TABLE 2.9: YIELDS OF SELECTED CROPS, IN KG/HA, AND PERCENT CHANGES, IN CEARA. 54 TABLE 2.10: PERCENTAGE OF FARMS WITH IMPROVED AGRICULTURAL PRACTICES OR SERVICE ACCESS, BY MESO-REGION, IN CEARA. 54 TABLE 2.11: TECHNICAL ASSISTANCE (PERCENTAGE), BY FARM SIZE, IN CEARA, 1995- 1996. 55 TABLE 2.12: FERTILIZER USE AND PEST CONTROL, IN CEARA, 1995-1996. 55 TABLE 2.13: IRRIGATION, PERCENTAGE FIGURES BY FARM SIZE, IN CEARA, 1995-1996. 57 TABLE 2.14: HARVESTED IRRIGATED AREA, BY MAJOR CROPS, IN CEARA, IN 1995-1996.57 TABLE 2.15: SOCIOECONOMIC PROFILE OF RURAL HOUSEHOLDS IN NORTHEASTERN BRAZIL. 60 TABLE 3.1: POVERTY HEADCOUNTS IN CEARA, THE NORTHEAST AND BRAZIL, 1985- 1996, BASED ON A SET OF REGIONALLY SPECIFIC POVERTY LINES PROPOSED BY ROCHA (1998). 72 TABLE 3.2: ACCESS TO BASIC SERVICES OVER TIME, STATE OF CEARA. (%) (SHARE OF POPULATION IN HOUSEHOLDS WITH ADEQUATE ... ) 74 TABLE 3.3: (HOUSEHOLD PER CAPITA) INCOME SHARES BY POPULATION TENTH ('DECILE') IN CEARA (%) 74 TABLE 3.4: POVERTY AND LIVING STANDARDS IN 1996: CEARA IN CONTEXT 78 TABLE 3.5: POVERTY PROFILE 1996: CEARA, Z = (R$ 65.07/MONTH), I = 1I, 0=1.0 79 TABLE 4.1: TRENDS IN CURRENT REVENUES 97 TABLE 4.2: TRENDS IN ICMS AND GDP 98 TABLE 4.3: LOSSES ARISING FROM LEI KANDIR 98 TABLE 4.4: SECTORAL COMPOSITION OF ICMS RECEIPTS 99 TABLE 4.5: DISBURSEMENTS AND RECEIPTS OF INDUSTRIAL TAX INCENTIVES 100 TABLE 4.6: TRENDS IN NUMBER OF PERSONNEL 101 TABLE 4.7: TRENDS IN DEBT STOCK 102 TABLE 4.8: TRENDS IN CURRENT AND CAPITAL EXPENDITURE 103 TABLE 4.9: ACTUAL AND PROJECTED FISCAL INDICATORS 104 TABLE 4.10: ALLOCATION OF EXPENDITURE 104 FIGURES FIGURE 2.1: CEARA'S AGRICULTURAL GDP 42 FIGURE 2.2: COMPARISON OF FARM DISTRIBUTION (NUMBER) BY FARM SIZE, IN CEARA.50 FIGURE 3.1: SPATIAL COMPOSITION OF POVERTY IN CEARA 81 FIGURE 3.2: THE POVERTY-EDUCATION PROFILE IN CEARA 82 FIGURE 3.3: THE OCCUPATIONAL SECTOR - POVERTY PROFILE IN CEARA 83 FIGURE 4.1: ALLOCATION OF EXPENDITURE 106 BOXES BOX 1.1: TOURISM IN THE DOMINICAN REPUBLIC 23 1. THE ECONOMY: IMPROVING COMPETITIVENESS This chapter is based on a background paper by William Tyler. ACKNOWLEDGMENTS Information for this paper was collected during a World Bank mission to Fortaleza during the period July 7- 17, 1998. Efforts were devoted to understanding the problems facing the expansion of the Cearense economy, focusing on the economy's structure, its competitiveness, Government policies and the economy's future prospects. In addition to data collection and meetings with Government officials and staff, a series of interviews were conducted with the private sector. Firms from a number of sectors were interviewed, including shoes, apparel, textiles, ceramics, tourism, construction, food processing, beverages, steel, and metalworking. The regional office of the IFC, located in Fortaleza, was very helpful in arranging a number of these interviews, and the author is grateful to Ralph Daniels and Yana Chagas for that support. The largest debt, however, is with the Government of the State of Ceara, particularly the Secretaria de Planejamento (SEPLAN) and with IPLANCE (the Fundacao Instituto de Planejamento do Ceara). Indeed, the report was done on a truly collaborative basis with IPLANCE. The author extends special thanks to Alberto Teixeira, Francisco Ferreira, Eloisa Bezerra, Celio Pinheiro, Tania Maria de Matos Brito, Yoshio Namekata and Carlos Azzoni. Thanks also go to Pedro Falcao for his conscientious help with the statistical materials and data analysis. 8 Executive Summary 1.1 Outlook for Future Growth. The dramatic economic transformation of Ceara over the past thirty years has been characterized by reasonably high growth, changes in sectoral output and employment composition, continuing urbanization and improvements in living standards. Agriculture has continued its secular decline but remains important as an employer. Industry has assumed an increasingly important role, although its performance as a generator of employment has been disappointing. Within the services sector a major impetus has come from the development of tourism. By 1997 its direct share in the state's GDP is estimated to have been 4.8 percent, and in 1998 it is expected that tourism's share will be larger than the contribution of agriculture to Cearense GDP. 1.2 The outlook for the future is that the observed trends will continue. Agriculture holds little promise in playing a key role in the state's economic expansion, although it will continue to be important as part of any strategy to alleviate poverty. Manufacturing, particularly light manufacturing (e.g., shoes, apparel), is expected to continue its expansion in an increasingly competitive economic environment. In addition, a major role seems destined for tourism in leading Cearense growth. 1.3 Economic Policy Stance. The general conclusion is that the overall strategy and policy stance of the state Government of Ceara is, in large measure, an appropriate one. An emphasis has been made on putting the state's finances on a sound fiscal basis and focusing the state's interventions on the provision of such public goods as education, health, sanitation and infrastructure and on the establishment of a conducive environment for private sector development. This strategy has paid off in the realization of higher rates of growth for Ceara than for neighboring states and for the country as a whole. In addition, despite continuing poverty, the overall image of the state and its government is that of a modernizing and progressive one. This in itself should continue to serve as an attraction for new private sector investment. 1.4 The general policy implication is largely for a continuation (with some important adjustments) of the present policy stance and direction. Importantly, the state Government should avoid the temptation of doing a number of things that it is presently not doing in a major way. Saying no to policy proposals for selected interventions is sometimes difficult for policy-makers to do, but exercising restraint and allowing the market to function is frequently the best course of action. The state Government should avoid a pro-active approach of targeting policy interventions to support individual firms or sectors (e.g., steel, petrochemicals). To the extent that such interventions do exist they should be de-emphasized and phased out. Some specific policy measures for consideration by the state authorities are posited in five areas: (a) export processing zones; (b) the ICMS-related incentives; (c) government investment promotion; (d) tourism; and (e) infrastructure and education. 1.5 Export Processing Zone(s). Recognizing the controversy surrounding this issue, it is recommended that the state Government of Ceara reconsider the advantages and disadvantages of moving to put into operation an initial EPZ. The logical site for such an operation would be in the new port of Pacem. Indeed a successful EPZ there could help make the port venture a very visible success as well. There is no presumption that 9 state government monies should be used in establishing, financing or administering the EPZs. 1.6 ICMS-Related Incentives. In view of the distortions generated by the ICMS- based incentive system, some revamping would appear to be desirable. Two options - one marginal and one radical - are posited for Government consideration. They are: (a) Option One: Marginal Changes. Modifications in the way in which the system is administered can be envisaged to reduce some of the distortions resulting from the incentive system. These changes could include inter alia: (a) Govemment refusal to extend the covered incentives period for firms benefiting from the incentives; (b) granting incentives to more than one firm in an area producing in a given sector; (c) substantially reducing the scope for administrative discretion in the awarding of the incentives; and (d) simplifying the process of granting the incentives. (b) Option Two: Replacing the Present System with a Wage Subsidy for Unskilled Workers. There are a number of substitutes possible for the ICMS- related incentives. One possibility would to replace it with a system of incentives based upon the payroll taxes (the encargos sociais) paid by employers. The state Government could simply assume and pay to the federal Government a share of these payroll taxes for unskilled workers receiving up to, say, two times the minimum wage. The substitute system would have to be introduced gradually, grandfathering in firms operating under the current ICMS incentive system, and carefully calibrating the new system so that it would be at worst fiscally neutral. Over time the new system based upon the state payment of payroll taxes could be gradually extended from new firms - the target group under the present system - to all firms paying such taxes. 1.7 Government Investment Promotion. Several suggestions are made to improve the effectiveness of the state Government's investment promotion. First, the Government should consider a reorganization of the SDE to permit a greater professionalization of the investment promotion function, including a separation of investment promotion from any negotiation of the incentives. Such a reorganization need not involve new budgetary commitments. Second, investment promotion activities on the part of the Government should not concentrate on industry but should also include other activities, including tourism. Also by undertaking the establishment of an initial EPZ in Pacem, the reformulated SDE would concentrate its efforts not on negotiating incentives but seeking out investors and selling the image of the state. This is also the approach that should be pursued to attract investment in tourism facilities. Third, the SDE should adopt a greater emphasis on strengthening public - private sector partnership arrangements in attracting new investments. Taking greater advantage of private sector organizations - such as the FIEC and the ACC - would be obvious starting points. Fourth and similarly, the SDE should consider contracting out of a number of functions SDE to the private sector, including early on the preparation of promotion materials - e.g., a Doing Business in Ceara (in both English and Portuguese) guide for prospective investors. Finally, the SDE's investment promotion office should seek outside professional advice and assistance on attracting foreign direct investment. One example 10 of such support might be to involve the World Bank/lFC Foreign Investment Advisory Service (FIAS). 1.8 Tourism. The Government's overall approach to promote tourism should be threefold. First, efforts led by the state Government at its highest level should go into the development of an integrated state strategy for tourism development. The state strategy should include a strong private sector participation and entail a regional focus as well as one based upon Ceara. To proceed with the formulation of such a strategy a special Commission is suggested, with technical support involving international as well as national expertise. One input into the Commission's technical work would presumably be the recent work on tourism clusters done under the auspices of the Iniciativa pelo Nordeste. 1.9 A second dimension of the state Government's approach, indeed as a part of the strategy indicated above, would be to access the infrastructure requirements for successfully developing tourism in the state. While PRODETUR resources have helped, there are indications that serious bottlenecks in such infrastructure services as water, sewerage and energy are either present or are emerging for tourism. But this needs to be more carefully assessed, especially in view of the scarcity of public investment resources and other demands placed upon them. GeKting private sector participation in the provision of such services should also be an objective. 1.10 Third, state public finance questions need to be addressed as related to tourism. Currently, hotel and restaurant services are exempt from payment of the ICMS. At some point, the Government may wish to consider changes in this status as part of a generalized tax reform for the ICMS. The international experience has been to subject tourism - and tourists - to taxation, and there is no prima facie reason that Ceara should be different. 1.11 Infrastructure and Education. The use of public resources to finance infrastructure and other public goods lies at the heart of the state government's economic management and strategy. Making sure that scarce public resources are effectively rationed and used is a primary responsibility of good public administration. In this context, the Government may want to consider a small, but well placed and highly technically qualified, unit to analyze and vet proposed public investment projects. The logical place for such a unit would seemingly be SEPLAN, possibly as part of a budget group. The public sector investment program however should be developed on a multi- year basis. As part of a results oriented and cost conscious approach to public expenditures, the Government would be well advised to consider a re-prioritization for some of its public sector investments and expenditures, with a greater emphasis on education and infrastructure and less on large scale irrigation projects. Introduction 1.12 For many years Ceara was considered as one of Brazil's poorest and most backward states. In recent years, however, the state's image has undergone some important changes, as the economy has grown and modernized. 11 1.13 A part of the ongoing modernization has been a change in the overall strategy and policy stance of the state Government. The role of the state, both at the federal and state levels, has undergone an important redefinition. The reliance on market mechanisms and the private sector has been increased, and the scope of government interventions in the economy has been reduced. The emphasis of the state government of Ceara has gradually undergone this transformation beginning around 1988. An emphasis has been made on putting the state's finances on a sound fiscal basis and focusing the state's interventions on the provision of such public goods as education, health, sanitation and infrastructure and on the establishment of a conducive environment for private sector development.' This strategy has paid off in the realization of higher rates of growth for Ceara than for neighboring states and for the country as a whole. In addition, despite continuing poverty, the overall image of the state and its government is that a modernizing and progressive one. 1.14 This paper examines recent economic growth in the state of Ceara and the prospects for future growth. The state's changing economic base will be examined, with particular attention paid to the role of industry and tourism. While the policy instruments in the hands of state policy-makers are limited, there is an important role for state policy to encourage the development of the economy. The paper provides an analysis of state incentives and a discussion of state investment promotion. A closing section presents some policy recommendations for consideration. Recent Economic Growth and Future Prospects Overview 1.15 Dating back to the turn of the century, the Northeast has been the poorest region in Brazil. Regional disparities were exacerbated as the Center-South industrialized. Agriculturally based, tie region been subjected to periodic droughts, economic isolation and continuing backwardness. Over the last forty years numerous efforts have been made by both federal and state governments to reduce Brazil's regional income disparities through tie promotion of higher rates of growth in the Northeast. These efforts have focusecl largely on two separate strategies: (a) drought alleviation (e.g., relief, reservoir construction, agricultural irrigation, etc.) and (b) industrialization (e.g., state firm investments, credit and fiscal incentives for private sector investment, etc.). The previously observed increase in the disparities seems to have stabilized and growth has occurred in most of the region. As national economic integration occurs, including that brought about by political pressures, one would expect the regional income disparities to dirminish, such as has happened in other large countries with sustained growth and economic development.2 In the United States, for example, the last fifty years have witnessed a substantial reduction in the income 1 A good statement of the Cearense Governme-nt's strategy is contained in Governo do Estado do Ceara, Piano de Desenvolvimento Sustentavel, 1995-1998 (Fortaleza, 1995). In many ways this policy program served as a point of departure for this paper. 2 The available empirical evidence for Brazil suggest that convergence in per capita income levels is indeed taking place. See Aguirre (1998), Arraes (1997) and Azzoni (1997). One recent study however (Azzoni and Ferreira (1997)) suggests that Brazil's poorer regions have experienced a worsening of their industrial competitiveness from 1985 on and that this may bode poorly for continued convergence. 12 disparities between the states, with the poorer South gradually catching up with the rest of the country. 1.16 In the case of Brazil there is little evidence of a convergence of income levels for the Northeast as a whole and the rest of the country.Table 1.1 presents some growth rate comparisons for Brazil and the major Northeastern states for the period 1985-96. For the region as a whole, the rate of GDP growth was the same as for the country (2.5 percent annually). The aggregates of course disguise some interesting developments. The state of Ceara has grown more rapidly than the rest of the country and most other Northeastern states. The overall question is twofold: (I) whether this observed convergence for Ceara can and will continue and (ii) the extent to which state economic circumstances and/or policies can make a difference in accelerating growth and thereby diminishing economic disparities. Table 1.1: Growth Rate Comparisons for Northeastem States, 1985-96 GDP (R$ bin) Annual Growth Rates (in %) 1996 1985-90 1990-96 1985-96 Brazil 778.82 1.8 3.0 2.5 Northeast 109.37 2.2 2.8 2.5 Ceara 17.13 3.4 4.9 4.2 Maranhgo 10.12 8.9 3.6 6.0 Rio Grande do Norte 7.35 6.7 4.8 5.6 Pernambuco 18.38 4.5 1.8 3.0 Bahia 33.52 2.5 2.4 2.4 Notes: 1) GDP growth comparsons, using constant prices of 1996. 2) Revised data. Sources: Brazil: IBGE/DECNA; Northeastern states: SUDENE/DPO/DCR; Ceari: IPLANCE/DEP/DEAC. 1.17 Over the past thirty years Ceara's economy has undergone a dramatic transformation. The economy has grown substantially (with GDP growth averaging 5.8 percent annually for the 1970-97 period, slightly higher than the national average). Such growth has been accompanied by sectoral changes, continuing urbanization and an improvement of living standards, despite persistent poverty. Some of this is suggested in Table 1.2 showing the changes in the sectoral composition of state GDP and employment. The contribution of agriculture to total output has continued a secular decline, decreasing from nearly 16 percent of state GDP in 1970 to less that 6 percent in 1997. Agriculture however continues to be a major provider of employment, with some 43 percent of the economically active population still engaged in agriculture (down from over 68 percent in 1970). The comparison of these sectoral trends illustrates Ceara's major growth dilemma. Agriculture has decreased in its relative importance, but employment growth in the more dynamic sectors of the economy has not been sufficient to transfer workers out of low income, subsistence and drought prone agriculture. Despite the growth in industrial activity, manufacturing employment has lagged. Questions are posed as to the nature of the growth process itself and its future prospects. 1.18 The observed sectoral recomposition of Ceara's output has allowed the state to expand at rates greater than the national averages. If the state had been consigned to maintain the sectoral shares existing in 1970, the observed high aggregate growth would not have occurred. Reflecting the changing sector composition, industry has constituted 13 the economy's leading growth sector, even though it has not contributed to concomitant employment growth. Table 1.3 shows the differing sector growth rates since 1970.3 Table 1.2: Sectoral Composition of the Cearense Economy (% shares) Years Agriculture Industry Services State GDP 1970 15.8 18.6 65.7 1980 9.4 25.4 65.1 1986 8.3 25.1 66.6 1997 5.7 27.4 66.9 Employment 1970 68.4 10.4 21.2 1980 54.3 14.4 31.4 1986 44.0 16.7 39.3 1996 43.2 14.2 42.7 Source: IPLANCE. Table 1.3: Ceari: Value Added Growth Rates, 1970-80, 1980-90 and 1990-96 (in %) Sector 197040 1980-90 1990-96 Agriculture 3.0 0.8 4.2 Industry 12.0 3.5 5.5 of which: Manufacturing 15.4 2.0 8.6 Services 8.4 4.3 4.6 TOTAL (State GDP) 8.5 3.8 4.8 Source: IPLANCE. See Annex Table 14 1.19 Industry, and especially manufacturing, has led Cearense growth in the 1970s and 1990s. During the 1980s the overall rate of growth, as in all of Brazil, was slow, with manufacturing losing its steam in leading the economy's growth, although recovery took place in the 1990s. Growth in agriculture, reflecting its declining share, has been sluggish. 1.20 One striking facet of the Cearense economy has been its overall inward- looking nature. Exports have not been important in leading the economy's growth. The markets for Ceara's goods and services have been national, rather than international. Merchandise exports currently represent only about 2 percent of the state's GDP.4 And this share has not grown appreciably. Moreover, Ceara's exports - totaling US$ 353 million in 1997 - represent only a tiny portion of Brazil's total exports (less than 0.85%), and this share has decreased over recent years, reflecting a more robust rate of export growth for the country as a whole.5 1.21 Although Cearense export growth has been insignificant in an aggregate sense, it has been relevant for some activities. This is suggested in the changing composition of the state's exports. By 1996 a full 57 percent of those exports were manufacturing products, as opposed to 20 percent in 1985.6 While cashew nuts are the single most important export product, shoes, textiles and apparel have become important export categories as well. The major markets for Ceara's exports have been NAFTA (58 3 A more detailed picture is presented in Annex Table 14. 4 By way of an admittedly artificial comparison, it might be noted that no independent country in the world has such a low ratio. 5 See Annex Table 5. 6 Annex Table 19. 14 percent in 1997) and MERCOSUL (18 percent), with the US and Argentina constituting the largest two country markets. 1.22 The failure to develop an important export sector(s) has been associated with a vicious circle of underdevelopment for Ceara. Economic isolation and looking toward the local and regional markets have resulted in a lack of concern for competitiveness, which in turn has made entering export markets difficult, thus reinforcing the state's isolation. Breaking out of this mold will prove to be important for increasing competitiveness and growth. While expanding merchandise exports may not be absolutely essential for lifting living standards in Ceara, becoming more competitive is. Agriculture 1.23 As seen in Table 1.1 and Table 1.3, agriculture's performance in the state economy has been a disappointing one. The sector has been characterized by socio- economic dualism as reflected in number of dimensions, including income inequality, subsistence versus commercial agriculture, irrigated versus unirrigated production, and disparities in rainfall and soil qualities. Minifundia is a common characteristic reflecting the importance of subsistence agriculture, with some 200,000 farms in 1985 (the last year for an available agricultural census). Productivity levels in agriculture are very low when compared to those existing for other sectors. Value added per worker in the Cearense agricultural sector was less than one-tenth of that for industry in 1996.7 As a result and not surprisingly, poverty in the rural sector has been prevalent, persistent and deep. Table 1.4: Production of Principal Agricultural Products, Selected Years, 1970-97 (1970 = 100) Product 1970 1980 1985 1990 1997 Cotton 100.0 82.5 104.9 20.9 12.1 Peanuts 100.0 65.0 135.0 107.6 164.2 Rice 100.0 71.6 355.8 497.3 711.4 Cashew Nuts 100.0 204.0 364.8 268.3 195.3 Bananas 100.0 47.3 43.6 33.2 32.8 Coffee 100.0 71.5 41.3 69.4 59.6 Sugar Cane 100.0 62.7 87.6 126.5 102.3 Coconut 100.0 180.9 164.0 206.1 216.4 Beans 100.0 86.2 131.3 129.3 251.8 Oranges 100.0 72.5 60.3 54.8 49.6 Cassava 100.0 58.1 41.0 54.2 45.9 Corn 100.0 85.2 147.2 107.0 236.2 Source: Computed from IPLANCE information. See Annex Table 28 1.24 Periodic - and inescapable - droughts have contributed to a high volatility in production. Table 1.4 indicates this volatility, as well as suggesting the slow overall growth of Ceara's agricultural output and its changing composition. Some products have experienced reasonable growth (e.g., rice, coconuts, cashew nuts) while others have declined. Particularly noteworthy is the decline in cotton production, beginning around 1975, primarily due to the infestation of an uncontrollable pest (the bicudo). It is only now that the pest has been controlled and a recovery of this crop - particularly important for the rural poor in unirrigated areas - is taking place. 7 See Annex Table 2. 15 1.25 The prospects for future agricultural growth are limited. It is improbable that the sector will ever resume its prominence in the state's economy or will emerge as a leading sector for the state's economic growth. Indeed, the secular decline in its share of total state output may well continue, especially if the nonagricultural economy can grow at rates greater than 4 percent annually. While agriculture is unlikely to be the source of major growth, its role for employment will remain critical and therefore it will continue as important for poverty alleviation. 1.26 The best prospects for agricultural growth would appear to involve high value crops, particularly fruits. One such product is cashew nuts - either in unprocessed or processed form. This is a traditional export product for Ceara but one which possesses a high potential. World market demand for cashew nuts is growing rapidly (e.g., about 6 percent annually between 1986 and 1993) and can be expected to continue such high growth in the future.8 To provide protection for cashew nut processing industry, the Brazilian Government has imposed restrictions on the export of unprocessed cashews (em natura). This export restriction imparts an effective tax equivalent on growers of about 40 percent.9 Despite the growth of cashew production (Table 1.4), this discriminatory government measure has clearly impeded the development of the crop. While one would hope that an internationally competitive processing industry would develop and grow in Ceara, it is questionable that such growth should occur through the effective subsidization of the industry as currently borne by effectively taxing the growers of cashew. 1.27 A major challenge will continue to be to use scarce water economically. Water resource constraints severely limit the expansion of Cearense agriculture. The state Government has responded to long-standing concerns to reverse the relative decline of agriculture through the pursuit of a number of large scale water resource and irrigation projects. The most ambitious of these are projects involving the transposition of water from the S30 Francisco river and the Castanhao reservoir. The costs of this, and other, water will be quite high. Water should be used in an economic way and priced accordingly. In any case, the economic viability of future irrigation projects needs to be carefully assessed. Industry 1.28 As demonstrated in Table 1.2 and Table 1.3, the industrial sector has emerged as Ceara's leading growth sector - although its performance as a generator of employment has been disappointing. While the origins of Ceara's manufacturing sector go back many years (most notably for textiles, apparel and of course food products), it has only been since the early 1970s that a significant industrial sector has emerged. During the past thirty years, Brazil has witnessed a decentralization of industry from the South and Southeast of the country to the Northeast. Much of this decentralization has 8 For a discussion of the cashew market and an appeal for developing the Cearense processing industry see Bosco de Almeida and Soares, "Industria de Castanha de Caju: Situacao Atual e Perspectivas," 1995. 9 The effective export tax equivalent is estimated through the comparison of international (export) and domestic prices. International prices are currently reported to be about US$750/ton while domestic prices are approximately US$450/ton. Without the export restrictions, the domestic price for unprocessed cashews would approach the international price. The export restrictions have driven a wedge between international and domestic prices. 16 taken the form of existing firms based in the South and Southeast establishing branch plants in the Northeast. In addition, some true migration has also taken place through the relocation of factories from the Center South to the Northeast. Particularly in more recent years, Ceara has been successful in capturing some of this investment - both by existing firms and by newly established firms. 1.29 At the two digit level, Ceara's most important manufacturing industries are food products, textiles and apparel and shoes. Together in 1996 they accounted for over 56 percent of the state's manufacturing output.'° Notably, textiles and apparel and shoes enjoyed high rates of growth during the 1980s (10.2 and 7.5 percent annually, respectively), which has continued into the 1990s. In the case of textiles, there has been a competitive shock in the early 1990s coming from the generalized - but limited - import liberalization introduced by Collor administration. Nationwide, there has been a reduction in the number of firms operating in the textile industry, stagnant overall production (and exports), increased import levels and reductions in employment." In Ceara textile output has continued to grow (5.7 percent annually) while employment has been cut back.12 This has taken place in an environment which has subjected Cearense - as well as other Brazilian - producers to greater competitive pressures. Many Cearense producers have met the challenge through ambitious modernization programs, involving new investments and more exacting quality control. Concerns on the part of these producers are the high costs associated with the so-called Custo Brasil, the threat of further import liberalization (especially in the absence of measures to reduce the Custo Brasi), and continued high interest rates. 1.30 Attractions for Manufacturing Investment in Ceara. There have been a number of attractions for firms to set up manufacturing operations in Ceara.'3 First, and perhaps most important, is an intangible attraction. The state is blessed by a favorable image stemming from a fiscally responsible and modernizing political leadership and public administration, a "can do" attitude, and a reputation for a hard working and honest labor force. A priori one would expect more private investment in a state where there is a greater sense of fiscal responsibility. This factor seems to be working in an important way in the case of Ceara. Public sector reforms initiated in 1987 have centered on fiscal adjustment and a redefined role of the state. In addition to the much improved fiscal situation and stance, the state Government's image has also been boosted by a number of other policies and activities. The state's leadership has expressed a commitment to improving the state's economic infrastructure, as witnessed in the highly visible airport project, the Pacem port, and investments in roads. All of this - plus a keen public relations sense at the top - has helped bring in new investments. Faced with a choice to locate in Ceara or elsewhere in the Northeast, a number of firms choosing Ceara emphasized the importance of good (and honest) state government and fiscal responsibility in their decision. 10 See Annex Table 14. This table also presents growth rates at the two digit level for the 1970-96 period. 11 A recent BNB/ETENE study of the Northeast's textile industry presents basic data and a good assessment of producer viewpoints. (See BNBIETENE, 1997). 12 See Annex Table 15 for employment data and employment growth. 13 These findings, along with many others expressed in this report, are a result of a number of interviews conducted with private sector firms operating in the state. 17 1.31 A second major attraction that Ceara possesses stems from labor market conditions. Wage levels in Ceara are much lower than in the Center-South. Indeed, Cearense wage levels make it potentially internationally competitive in a wide range of light manufacturing products. One firm reported (typically and entirely in keeping with other firms) that it paid entry level, unskilled labor in its Ceara plant R$150/month versus R$280/month paid at its Sao Paulo plant.14 Taking into account the additional payroll taxes and fees (the encargos sociais), this brought its total labor costs for an unskilled worker in Ceara to R$263/month versus R$560/month in Sao Paulo. In general, for unskilled labor the cost of such labor in Ceara is about one half that a firm would pay in the Center-South. This implies that for a firm whose labor costs represent, say, 20 percent of its total production costs, the lower wage costs could give it a competitive edge of up to 10 percent. When asked about the comparative productivity of such labor in the two locations, the answer from firms is generally that productivity in Ceara is as high as in the Center-South, although some greater initial supervision and training may be necessary. In general, labor quality and attitudes - especially for unskilled labor - are considered a plus for Ceara. Moreover, the pressures either for unionization of the labor force or from unions are considered to be fewer than in the Center-South. Better labor relations are frequently cited as an important reason to relocate in Ceara. 1.32 A third, and very visible ard oft cited, attraction for investing in manufacturing in Ceara is the availability of the ICMS-based incentives. These incentives are the focal point of the state Government's promotional efforts to attract investment to the state. For those firms fortunate enough to get the full incentive amounts, their effect can be equivalent of up to 10 percent of their ex factory price. One firm, selling its products mostly in the Center-South market, indicated that the incentives slightly more than fully compensated the firm for its additional transportation costs associated with manufacturing in Ceara. 1.33 Many firms are attracted to the Northeast - and to Ceara - for the regional market potential. The overall Brazilian market for most products remains - at least by international standards - a fairly protected market. The Northeast is of course a part of that protected market and it is further separated by transportation costs from the rest of the country. Many Center-South firms locating production facilities in Ceara do so as part of an overall strategy and to take advantage of proximity to the markets in the Northeast. 1.34 The emphasis on regional markets means that few firms locate in Ceara to use the state's location as an export platform or base. Much is made of the new port being built at Pacem, the modern airport facility, the proximity to US and European markets, but these are, for the time being, potential attractions. Very few manufacturing firms operating in the state are exporting more than 50 percent of their production. And fewer still have come to Ceara to set up manufacturing for export operations. For example, one successful apparel manufacturer indicated that the firm's strategy was to keep exports to no more than 25 percent of total sales. While its products were competitive internationally, profitability on domestic sales (undertaken in a protected commercial policy environment) continued to be higher. In the case of this fairly 14 Cearense wage levels would seemingly provide a basis for intemational competitiveness for labor intensive export manufacturing. An illustrative comparison is with the unskilled wage levels in the successful La Mercedes Export Processing Zone in Nicaragua, where monthly wage levels are about US$300. 18 representative firm - as well as others - a further dismantling of domestic protection would have an adverse initial effect on its profitability. 1.35 Competitiveness. While manufacturing has indeed grown considerably in Ceara, it is unclear how efficient, or even how profitable, such industry has been or is currently. While no comprehensive and direct data for examining this question are available,'5 some indirect suggestive evidence can be used. A number of the firms interviewed indicated that their costs in Ceara were (slightly) less than those for their plants in the Center-South. A recent ETENE/SEBRAE study also provides some illustrative information, although that evidence points to rather low levels of efficiency, productivity and economic performance for Northeastern industry.'6 Only 10 percent of those firms surveyed for the study reported the use or attainment of ISO 9000 standards for their products. The average age for the firm's major piece of capital equipment or machinery was 9 years (12 years for large firms), and exports for the surveyed firms represented an average of only 7 percent of their sales revenues. The international competitiveness of the firms surveyed is in question. 1.36 A number of the firms interviewed voiced some trepidation at the prospects of future import liberalization. This is even the case where the firms were successfully exporting. The protected domestic market has afforded higher profit margins for domestic sales than for exports. Ideally, future trade policy liberalization should occur along with measures to reduce the Custo Brasil and align the exchange rate in keeping with its equilibrium value and macroeconomic consistency. With such policy changes Cearense industry would necessarily undergo an adjustment process, imposing some - but not insurmountable - difficulties in achieving levels of greater international competitiveness. The industrial activities less likely to encounter major difficulties in this process are those that are more labor intensive and those that are presently exporting, e.g., apparel and shoes. 1.37 Attaining reasonable levels of international competitiveness is an important consideration for attracting and installing manufacturing firms in Ceara. If indeed Brazil is to become a more open economy in the future, meeting the test of potential international competitiveness should be a criterion. There is of course less risk for the government if no public resources are involved either presently or at risk in the future. The greater the involvement of public resources in attracting such firms (through ICMS-based incentives, donations of land, subsidized provision of infrastructure services, etc.), the greater should be the care exercised by the government so as to assure that competitiveness can be attained and that there will be no future drain on public resources. The risk is greatest where there is no obvious or apparent comparative advantage for Ceara, such as in heavy, capital intensive industry. Steel, petrochemicals and automobile 15 The Gazeta Merchantil's annual survey (Ceara: Balango Anual, 1998) provides a compilation of the financial results of the state's largest firms. Interestingly, the reported operating results were in several instances different from those informally reported by the firms to the author. 16 This study (BNB/ETENE/SEPRAE, Qualidade e Produtividade na Industria Nordestina) conducted a survey of over one thousand firms. Of these firms, 23 percent were located in Ceara, and a total of two- thirds operate in Ceara, Bahia or Pernambuco. While the study presents a wealth of interesting descriptive data from the survey, it draws short of reaching any conclusions on economic performance. Moreover, no real basis for comparisons is provided; comparisons are presented only within the sample and across firm size and industry groupings. 19 manufacturing are cases in point. In these three examples there is no inherent advantage for Ceara based on the presence of natural resources, the availability of a human resource base, unique market access or other compelling factors. All three activities are high risk for Ceara. For the state Government to actively promote - with its resources - heavy industry manufacturing activities such as these is a risky, poorly conceived and ill-advised strategy. If the risks were to be borne solely by the private sector, the concem by the state government might be limited. If, on the other hand, public resources are at risk, the state Government might want to consider alternative demands on its scarce resources. 1.38 Constraints on Manufacturing Expansion. The constraints that manufacturing firms face in Ceara are much the same as private sector firms face in other sectors of the Cearense economy. All firms complain about the high interest rates, which are a reflection of national macroeconomic policy management. All firms also face the same types of problems with labor quality and productivity. The manufacturing firms the author interviewed noted, as indicated above, that there were no real problems at the most basic levels of unskilled labor, despite the low levels of educational attainment and schooling. For supervisory personnel however there do seem to be problems. A number of firms indicated that there were real difficulties in recruiting qualified individuals for supervisory and technical positions. Frequently firms resort to bringing in staff from the Center-South, but problems were noted in the costs, local resentment and cultural acclimation. The scarcity of these individuals in the labor market is most commonly attributed to the failures and inadequacy of the local educational and training system. Improving education seems to be a must for consolidating the gains made so far in expanding the economy and pushing to the next level. 1.39 An important constraint for expanding manufacturing output involves the adequacy of supporting economic infrastructure. This is reflected partly in the noted Custo Brasil. The costs of doing business in Brazil are generally considered to be higher than in many other countries. Transactions costs are driven up by antiquated administrative and regulatory arrangements. The tax environment and the availability and cost of infrastructure services also contribute to the Custo Brasil. One can expect that with the privatization of many services previously performed by state firms or entities, the quality of these services will improve and costs will fall. Telecommunications, railway transportation, port services and electricity are cases in point. There was no evidence - at least easily available - that the Custo Brasil was less or more in Ceara than elsewhere in the country. 1.40 Export Processing Zones. One interesting feature existing in many successful exporting, labor abundant economies is not present in Ceara. This is the institutional mechanism of the Export Processing Zone (EPZ). EPZs are frequently set up to overcome the constraints and obstacles in developing manufacturing that characterize many developing economies. Access to infrastructure can be relatively easily provided, obtaining intermediate inputs at international market prices market is assured, dealing with government authorities is facilitated, externalities are generated through "clustering," and marketing obstacles are sometimes more easily overcome. In addition, confidence in competing in international markets is built, with EPZs serving as a stepping stone to more vigorously contesting world markets, through a demonstration effect to others about the viability of export activity. While there have been some experiences with EPZs internationally that are less than fully satisfactory, the experience has generally been 20 positive; EPZs contribute to export growth, domestic value added, employment generation and linkages with the rest of the economy.17 In some cases, the success of EPZs has been notable (e.g., Taiwan, Korea, Mexico, Honduras, Nicaragua, etc.). 1.41 In 1988 legislation was passed in Brazil authorizing the establishment of EPZs. Indeed, there was some discussion in Ceara and a site for a prospective EPZ was approved in Fortaleza. To date there has been no further development of the original proposal. While the reasons for not moving ahead are not entirely clear and may be mostly political in nature, some economic rationale for inaction is also apparent. First, EPZs in Brazil are frequently misunderstood, with repeated references made to the Zona Franca in Manaus. In fact, the Zona Franca in Manaus is entirely different in its conception and administration. It is not an export processing zone; the operation essentially supports the assembly of goods with imported components to be sold in the protected Brazilian domestic market. It may more appropriately be termed an import processing zone. 1.42 Second, with the trade liberalization begun in 1990 the argument was made that such liberalization would preclude the need for any EPZ-type arrangements. This would indeed be correct if trade policy liberalization had been complete. An EPZ is definitely a second best arrangement; the first best would be to turn the entire country into a large EPZ through free trade. This however is not about to happen. Thus, the arguments for EPZs remain. A third, and similar, argument is that EPZs are not needed in Ceara because of the availability of other policy instruments such as the drawback and bonded customs warehouses. The answer to this objection is that there is no reason to view such instruments as competing. There are no reasons why EPZs can not co-exist with drawback arrangements and bonded warehouses. Indeed, in most country instances, they do. 1.43 The likely underlying reason for not implementing one or more EPZs involves vested, non-Cearense economic interests. That reason has to do with protectionism and the desire to shield domestic producers from potentially very competitive firms producing for the external market. The domestic producers whose interests might be adversely affected the emergence of Ceara as a successful base for export based manufacturing are not for the most part Cearense producers but those based in the Center-South of Brazil and with substantial influence in national policy-making. In addition, the fact that the new EPZ export producers are not yet present - and may be foreign - makes keeping them out all the easier. 1.44 The creation of an EPZ remains controversial today. With trade liberalization the advantage and importance of an EPZ has declined but-with significant trade barriers remaining-not disappeared. Taking the changed policy environment and the lessons for the design of a successful EPZ on board, the State Government could take the initiative and reconsider the installation of a well designed EPZ at the port of Pecem to complement other trade-related policy instruments. There is no presumption that state budget funds should be used in establishing, financing or administering the EPZs or that legislation protecting labor rights and the environment would not apply in an EPZ. 17 There exists an ample literature on the international experience with EPZs. See, for example, Madani (1998), Braga (1997), Rhee et al. (1990), and World Bank (1991). 21 Services: The Emergence of Tourism as a Leading Sector 1.45 As is apparent from the rough constancy of the share of the service sector in state GDP (Table 1.2) its growth has approximated the growth of the state economy. Underlying the aggregate performance, the composition of the service sector has changed remarkably.18 There has been a shift away from more traditional services and an increasing emphasis on the services that characterize a modern economy. Communications, commerce, financial services and private educational services have grown dramatically over the past thirty years. (Annex Table 14) Employment in the service sector has also grown fairly robustly, at rates exceeding those for manufacturing employment. (Annex Table 15) 1.46 One sector not measured directly in the national accounting framework is tourism. There is a category in most countries' national accounting frameworks for "Hotels and Restaurants." This category - frequently and inaccurately termed "tourism" - understates tourist spending in that tourists obviously spend their vacation monies on other things as well, and it overstates tourist spending since obviously all people eating in restaurants are not tourists. To deal with these measurement anomalies, countries where tourism is important have resorted to more sophisticated measurement techniques. These techniques involve indirect measurement, based upon estimating the number of tourist arrivals, the duration of their stays, and their spending habits both in composition and amount. Since there is some question regarding the present importance and future role of tourism in the Cearense economy, we have undertaken some such estimates for Ceara. 1.47 Tourism in Ceara has grown, at least initially, as something of a stepchild, beginning from a starting point of very little only a few years ago. In the past policy- makers have considered development and growth through tourism as not feasible and less attractive (in terms of linkages, as well as glamour) than industry. Political leaders everywhere, and Ceara has been no exception, have always found it exciting to extol the virtues - however dubious they may be - of heavy industry, e.g., steel mills, refineries, petrochemical complexes, automobile plants and the like."9 Tourism has not had the same appeal. It has been commonly viewed as menial in content and even undignified in its nature, pandering to the hedonistic interests of nonresidents, who are frequently foreigners. 1.48 The Intemational and National Context. The international market for tourism is one experiencing very rapid growth and where the prospects for continued rapid growth are quite promising. Over the period 1980-96 worldwide tourism receipts grew at a rate of over 9 percent annually, with the number of international tourists - as measured by tourist arrivals - growing by nearly 5 percent annually. Brazil has not benefited from this world market expansion. Over the same period Brazilian foreign exchange earnings from 18 Most countries employ the United Nations System of National Accounts (SNA). The Brazilian national accounting system is slightly different but not enough so that there are problems in relating concepts. In both systems there are problems with the definition and aggregation of different service components. For example, education provided by the public sector is included in a Public Administration category, while that provided by the private sector is lumped into a catch-all category including private health services. 19 The fascination with heavy industry has also led to a relative disregard for light manufacturing, despite frequently stated employment generation objectives. 22 tourism grew at only 1 percent annually in current US dollars. This lackluster performance for Brazilian tourism is reflected in a fall in its percentage of the international tourism market. Its share of the total international tourism receipts fell from 1.7 percent in 1980 to 0.5% in 1995.2° Some countries have emphasized tourism as an important element of an overall development strategy and have done quite well. (See Box 1.1 on the Dominican Republic.) Box 1.1: Tourism in the Dominican Republic The Dominican Republic has a number of similarities with the state of CearA. Both are poor (1996 per capita income in the Dominican Republic was US$1,600 vs US$2,600 for Ceara); both have similar sized populations (8 million in the D.R. vs 6.8 million for CearA); and both possess a tourism potential stemming from beaches, climate, natural beauty and the charm of an easy-going and friendly population. Until fairly recently the Dominican Republic had been besieged by poor economic management and associated slow growth. While tourism grew in the 1980s, an acceleration of that growth occurred in the 1990s. Between 1990 and 1996, tourist accommodations in the country and direct employment generated by tourism roughly doubled, tourist revenues increased at an average annual rate of 16 percent, and international tourist arrivals grew by 9 percent annually. As a result of tourism expansion, GDP growth increased, registering 7.1 percent annually between 1992 and 1996, up considerably from earlier periods. By 1996 tourism revenues accounted for over 13 percent of Dominican GDP, with tourism emerging as the economy's leading sector. In addition, the indirect effects have also been substantial. Construction activity has increased in order to meet the growing need for hotel and tourism related facilities, and foreign direct investment has also increased (growing at some 19 percent annually between 1990 and 1996). By 1996 international tourism arrivals and eamings for the Dominican Republic rivaled those for Brazil as a whole (1.9 million and US$1.7 billion for the D.R. vs 2.0 million and US$2.1 billion for Brazil, respectively). 1.49 Tourism in Ceara. While Brazil's overall performance in the international tourism market has been mediocre, for some parts of Brazil the story has been quite different. In Ceara tourism, unfavored by any special incentives, has nevertheless grown substantially. Over the period 1980-97 the number of tourists arriving in Ceara has grown at an annual rate of 6.7 percent (Table 1.5). During the early eighties this growth was considerable, although beginning from a low base. With slow economic growth for the economy as a whole and related economic uncertainty - both nationally and for the state - Cear4's tourism growth slowed, only to pick up again in the mid-1990s.21 Between 1993 and 1997 tourism demand grew by 10 percent annually, with an increase of more than 25 percent in 1997. Of the estimated tourist arrivals (amounting to 970,000 in 1997), the overwhelming majority (94.3%) were Brazilian residents. Yet it is international tourism that has grown the fastest in recent years (e.g., 38% in 1997) and possesses the greatest potential for future expansion.22 In any case, there appears to be ample room for future growth, especially for international tourism.23 20 EMBRATUR, Anuano Estatistico, 1996 (Brasilia: EMBRATUR, 1997). 21 Between 1986 and 1993 tourism in Ceara was stagnant. Only in 1994, concurrently with the Piano Real and macroeconomic stabilization, did tourism begin growing again. See Annex Table 19. 22 The greatest number of foreign tourists have come, somewhat surprisingly, from Italy (some 17% in 1997), followed closely by the US and Argentina. An insightful SETUR study, based upon a gravity model, has identified the most promising international markets for Ceara tourism to be the US, Germany and Argentina. See Teles, 1997. 23 Ceara's foreign tourists in 1997 were about 3% in number of those visiting the Dominican Republic. 23 1.50 By 1997, by our estimates based on SETUR (Secretaria de Turismo) data, tourism revenues were equal to some 4.8 percent of the state's GDP.24 (Table 1.6) Including its indirect effects on state output and incomes, tourism generated 7.4 percent of state GDP.25 Despite its labor intensive nature, the corresponding, direct plus indirect, employment generated by tourism (totaling some 112 thousand employees) was only 3.9 percent of the state's total employment. This is due to the economy's employment predominance in low wage, low productivity agriculture. Table 1.5: Ceara: Annual Growth Rates in Tourist Demand and Airport Passenger Arrivals (%) Passenger Arrivals at Periods Tourist Demand (Arrivals) Fortaleza's Airport 1980-86 12.8 7.4 1986-97 3.4 5.1 1980-97 6.7 5.9 Source: SETUR and Teles, 1998. 1.51 Tourism also generates tax revenues. In the case of Ceara hotel and restaurant services are exempt from the ICMS. Nevertheless, tourists purchase other goods and services which are subject to the ICMS tax. In addition, there are indirect effects, including with other forms of taxes. In 1997 a lower bound estimate of ICMS tax revenues directly attributed to tourist spending was R$51 million.26 Table 1.6: Ceari: Tourism Estimates and Projections, 1997-2001 1997 1998 1999 2000 2001 Tourist Demand (No. of Tourist Arrivals) Brazilian Residents 914,700 1,216,600 1,520,700 1,900,900 2,281,100 Foreign Tourists 55,300 73,500 91,900 114,900 143,600 Subtotal: 970,000 1,290,100 1,612,600 2,015,800 2,424,700 Total Tourist Spending (in millions of 1996 R$) Brazilian Residents 811.0 1,078.6 1,348.3 1,685.4 2,022.4 Foreign Tourists 44.2 58.8 73.5 91.9 114.9 Subtotal: 855.2 1,137.5 1,421.8 1,777.3 2,137.3 Tourism Spending as % of State GDP: 4.8 6.0 7.1 8.5 9.7 Total (Direct plus Indirect) Effects Production as % of GDP 7.4 9.2 10.9 13.0 14.8 Employment 112,400 148,300 182,300 223,900 264,600 Notes: Estimations made using tourist budget, spending and stay duration estimates from SETUR, SEBRAE, and EMBRATUR. The IPLANCE/USP econometrically estimated input-output model for Cear6 was used to estimate the indirect effects of tourism spending on state production and employment. 1.52 In sum, tourism has become one of the Cearense economy's leading growth sectors and an important presence in the economy. Reflecting this change, as well as 24 This was only slightly less than the agricultural sector's share in state GDP (5.6%). In 1998 tourism is expected to exceed agriculture in its share of state output, but not of course in employment. 25 The newly installed, still-in-calibration, II'LANCE/USP model was used to make the estimates. This model extends and updates the earlier IPLANCE input-output model (based upon 1985 data) through the re-estimation of the technical coefficients econometrically. Its main potential usefulness is that it will permit policy-makers to have estimates of the effects of exogenous shocks and policy changes on the Cearense economy. 26 This estimate was made using effective ICMS tax rate estimates for 1997. By subsequently incorporating such effective rates into the IPLANCE/USP model, one will be able to estimate the total - direct and indirect - effects on ICMS tax revenues stemming from certain types of economic activity (e.g., tourism). 24 what may be a more receptive and open attitude, policy-makers are now extolling the virtues of developing tourism and attracting tourists.27 1.53 The prospects for continued tourism growth in the foreseeable future are quite promising. As noted, there is ample room for continued expansion. Growth in tourism earnings was on the order of some 27 percent in 1997, and SETUR projections for 1998, based in great part on the first quarter, vacation month results, are that tourist arrivals in Ceara will grow this year by 34 percent.28 Such growth in itself amounts to about a 1.6 percent increase in the state's GDP. A factor not included in these projections has been the recent deregulation of the domestic airline industry. This deregulation has resulted in a tumbling of domestic airfares, with roundtrip fares from the Center-South to Fortaleza falling by as much as 50 percent. While no econometric analysis has been done, one could easily expect that the decline in airfares alone might result in additional tourist arrivals by 25 percent. 1.54 Based upon the recent past, SETUR projections, increasing tourism promotion, and improvements in the overall environment (including the outlook for airline fares), some projections of tourism arrivals and expenditure have been made for illustrative purposes (Table 1.6). These projections, while perhaps optimistic, are nonetheless feasible under the right conditions; they envisage tourism emerging as a leading sector in the Cearense economy over the next 5-7 years. By the year 2004 tourism expenditures could easily account for some 20 percent of state GDP. Bringing this about however will involve overcoming a number of problems and constraints. 1.55 Constraints to Developing Tourism in Ceara. While very appealing, attractive and possessing enormous potential, the state's tourism facilities are not up to international standards. Maintenance and quality standards of hotels leave considerable room for improvement. Technological gaps exist as well, especially with respect to telecommunications and computerized information systems. Water, sewerage and energy infrastructure are overburdened, especially in the outlying coastal areas. Given that international tourism flows can be quite sensitive to health concerns, improving water and sewerage systems should presumably constitute a high priority. The highway network also appears to be a problem for opening up attractive areas for tourism development. In short, infrastructure bottlenecks either currently exist or are on the short- term horizon in impeding investment and growth in the tourism industry. Also, to be successful in attracting event tourism - very important for the off seasons - a world class convention center may be needed.29 1.56 In addition, there are serious human resource constraints in both managing and staffing tourism facilities. Catering to international tourists requires a rather unique mind set and openness, not to mention language abilities. The Cearense educational system is presently producing few individuals with the requisite skills. Indeed, operators 27 It is noteworthy that many firms and operators in tourism complain that the Government's claim that tourism has become a priority for development is only lip service and that tourism is not truly a priority. They cite - predictably - the absence of incentives for tourism and what they claim is a lack of government response in the provision of infrastructure for tourism. 28 SETUR, "Sintese do Desempenho Recente do Turismo no Ceara," Fortaleza, Marco de 1998. 29 It is not clear that the existing Convention Center in Fortaleza meets these criteria. 25 and firms active in the tourism industry complained about the scarcity of trained and qualified personnel. 1.57 Another constraint is the partly unfavorable popular image that Brazil has in some quarters abroad as a country beset by problems of poverty, crime and health hazards. Concerns of potential tourists regarding personal security and health can be partly addressed through a continued emphasis on improving the public sector services in police and health. Also, these concerns can be allayed - in part at least - by adroit public relations and marketing efforts. 1.58 The Government is of course limited in the extent to which it can address some of these constraints. Much of the effort will have to involve private sector initiatives. A challenge for the Government, however, will be to provide an adequate infrastructure base, including the human capital skills, that will be needed to accompany such a transformation of the Cearense economy as envisaged in our projections. Policy and Regulatory Environment 1.59 Many of the economic determinants of growth of Ceara's economy are national or regional in nature and as such are outside the direct influence of state policy- makers. Fiscal, monetary and exchange rate policies - all pursued at the national govemment level - affect the decisions and behavior of private sector economic agents, as well as those of subnational govemment policy-makers. Yet, at the same time, there are a number of important policy instruments that the state authorities have at their disposal which also importantly affect economic outcomes. Of the most important of these, in addition to Government interactions and persuasion, are infrastructure provision, public sector investment projects and expenditure programs as well as fiscal incentives and other subsidies that can be provided by the state. The key question is how the Cearense Government can use the instruments available at the state level to sustain better than country-average growth over the next decade. The challenge for policy-makers at the state level is not to encourage economic policies that would direct growth toward certain sectors (an approach that is likely to fail) but to focus government policies on complementary measures that will facilitate growth in sectors in which Ceara has a comparative advantage, e.g., tourism. The National Policy Framework 1.60 The State of Ceara faces the same policy framework as other states in Brazil. While in some instances the influence of the state as exercised by its political leadership on federal policies may be quite circumscribed, there are other areas in which the state's authorities can exercise influence over policy outcomes. This ability to exercise influence politically and administratively exists both at the congressional and executive levels of the federal government. Clearly, capable state government officials are adroit in exercising such influence. 1.61 The federal Government's macroeconomic posture has resulted in high interest rates and negatively impacted growth nationwide, and there is little that the state Government of Ceara can do except to contribute to the debate that will continue after the upcoming national elections in October. Trade policies also have important 26 implications for Ceara and there may be some scope in exercising influence. For example, the export restriction currently existing on unprocessed cashew nuts has been referred to above. Since Ceara is the major state affected by this rather unique and noxious export restriction, state influence might be used to have it lifted. Also, Cearense views would be presumably important in any renewed national policy initiatives to facilitate the establishment of EPZs. 1.62 The federal regulatory framework is also fundamental for the development of the Cearense economy. But this is also an area where state officials can presumably exercise influence. The recent change of domestic airline regulations, which will substantially benefit the development of tourism in Ceara, is a good example of the appropriate use of political and administrative influence at the federal level to bring about a regulatory reform very much in the interests of Ceara. Working towards a change in the regulatory environment governing coastal shipping would be another area of enormous potential interest and importance to Ceara. The current legal and regulatory environment, entailing enormous levels of restriction on private sector activity, has effectively resulted in the demise of Brazil's coastal shipping industry and has impeded the development of a cruiseline tourism industry. 1.63 A third example of federal regulations which might be influenced by state officials for the benefit of the state deals with internet commerce. Ceara has been - somewhat surprisingly - the site of the development of a growing software and informatics industry. Worldwide, the informatics revolution has led to the explosion of internet commerce, and it is expected that these developments will continue. Brazilian consumers and producers are currently effectively and formally denied access to international internet commerce.30 Potential Brazilian exporters are precluded from selling their products intemationally over the internet. The restrictions mostly involve (but are not limited to) Central Bank regulations. Getting these policies/rules changed - to more closely conform to those existing in the rest of the world - would benefit Cearense producers and software developers. 1.64 In addition to the overall Brazilian policy and regulatory framework, there are a number of national programs and incentives which are directly targeted on the Northeastern states. The most significant federal tax incentive is the income tax incentive. This involves an exemption of firms, for a period of ten years, from the payment of 75 percent of the net operating results for firms either making or expanding their investments in the Northeast. 1.65 Some special credit programs also benefit the Northeast. For SUDENE approved projects generous financing is provided through FINOR. This financing - extended under generous and subsidized terms - can amount to up to 40 percent of the total investment for approved projects. In addition, BNDES has been making increasing 30 A Brazilian consumer may be able to make a small purchase internationally over the internet, pay for it with a credit card and have the product mailed to Brazil. Since credit card transactions within limits are protected by bank secrecy, he may be able to get away with it. But strictly speaking such transactions are illegal. In the case of a Brazilian producer selling his product abroad over the internet, he would not be able to receive payment for the product charged by his buyer to a credit card. He would also encounter formidable (insurmountable?) obstacles when he tried to mail or send the product to his buyer. (As a part of economic measures announced by the federal Government on September 8, 1998, some measures to facilitate internet commerce and small scale exports will be initiated.) 27 amounts of resources available to the Northeast. For most of its existence BNDES lending operations were focused in practice on the Center-South. The Northeastern states, including Ceara, were effectively, although unwittingly, largely excluded from BNDES credit. With democratization and resulting political influences, BNDES is now devoting more of its attention and activities to financing investment projects in the Northeast. Finally, the BNB (Banco do Nordeste Brasileiro) has played an important role in channeling resources into the Northeast. In 1997 its loans to the region totaled R$8.4 billion.3" BNB's lending has been mostly concentrated (about 80 percent) in the rural sector in agricultural and livestock activities. One might question this mix, especially for Ceara (where such activities account for less than 6 percent of state GDP). State Fiscal or Financial Incentives 1.66 Description of the State Incentives. The major state incentive for investment is based upon the value added tax (Irmposto de Circulaq5o de Mercadorias e Servigos or ICMS). While the tax is designed as a value added tax, there are some wrinkles in its actual implementation that preclude it from being considered a true value added tax. The fact that it complements what is essentially an industrial value added tax (the lmposto sobre Produtos Industrializados or hDI) administered by the federal government further complicates its actual administration. The ICMS is administered at a rate of 17 percent, with some important exceptions (e.g., telecommunications - taxed at 25 percent, electric energy - taxed at 20 percent, and interstate commerce - taxed at several different rates). Some sectors effectively escape the tax, notably agriculture and many services. 1.67 The ICMS-related incentives can be provided by the state government to industrial firms for new investment projects, investment increases or capital equipment modernization. The incentives are mostly calculated based upon the distance from Fortaleza, increasing with that distance with the objective of encouraging regional decentralization. The supposed maximum incentive permissible is an effective tax deferral of the payable ICMS extending up to a period of 15 years, with a grace period of five years. Most of the incentives are granted for a 10 year period. Formally and legally, the ICMS-related incentives are set up not as a fiscal incentive but as a financial incentive. A long-term credit is granted through a special fund (the Fundo de Desenvolvimento Industrial or FDI) to the firm in the amount of its tax deferral. 1.68 The incentives are awarded on a firm basis for investment projects. This permits an analysis of the incentives based upon information from the individual projects. Table 1.7, which provides an overview of the approved projects in Ceara for the period January 1995 to June 1998, demonstrates several noteworthy points.32 These are features of the attracted activities and firms and are indeed related to the nature and exercise of the incentive system. First, the magnitude of the investments are important. By way of comparison, total private sector investment in Ceara amounted to R$1.8 billion in 1996, suggesting that the investments covered by the incentives include a significant proportion of private investment. Second, the projects cover activities in a wide variety of sectors. Indeed, every manufacturing industry is represented at the two digit level. The 31 BNB, Balanco Social, 1997. 32 An alternative presentation is by municipality destination for the projects. Annex Table 4 demonstrates that the geographic dispersion within Ceara has been considerable for the 1995-98 period. 28 most notable concentrations in terms of the number of firms are in apparel, shoes and food products. Apparel and shoes also contribute the greatest employment generation, together accounting for nearly one-half of the total jobs created. The largest single investment, totaling some R$800 million, is destined for a very capital intensive steel plant currently being developed in the new port of Pacem.33 Third, while the incentives are supposedly designed to promote industrial projects, there are some approved projects in activities not considered manufacturing. Fourth, although the planned capital intensity varies considerably across sectors, the averages for capital intensity are nonetheless very high.3' The average investment cost per job is R$45,000 (approximately US$45,000). Even in the more labor intensive sectors (apparel, shoes) the cost per job (R$15,000 and R$12,000, respectively) may be considered high. By way of comparison, one large recently established hotel operator (a sector without-such incentives) indicated for his project an investment cost per job of around R$8,000. It should be noted however that the estimated capital-labor ratios are averages and that there are high levels of variance around the means. Table 1.7: Approved Projects under the ICMS-Related Incentives, by Sector, 1995-98 Sector/Subsector No. of Investment (R$ Employment (L) InviL firms 000) (R$) INDUSTRY Mining 5 25,370 630 40,270 Public Utilities 1 8,483 7 1,211,857 Construction 12 39,905 721 55,346 Manufacturing, of which: Nonmetallic Minerals Manuf. 14 38,156 1,079 35,362 Metals and Metalworking 16 925,088 3,303 280,075 Machinery 18 71,025 2,327 30,522 Electrical Equipment 19 170,923 2,792 61,219 Transportation Equipment 16 99,070 2,291 43,243 Wood Products 1 634 51 12,422 Furniture 10 11,727 1,075 10,909 Paper Products 6 46,700 986 47,363 Rubber Products 1 3,000 94 31,915 Leather Products 5 21,800 1,620 13,457 Chemicals 22 81,642 1,225 66,647 Pharmaceutical Products 6 9,050 646 14,009 Perfumery Products 8 49,630 1,380 35,964 Plastics 30 150,783 3,792 39,763 Textiles 30 562,384 9,089 61,875 Apparel 40 223,022 14,610 15,265 Shoes 41 189,566 15,785 12,009 Food Products 44 252,086 6,735 37,429 Beverages 4 262,500 1,400 187,500 Graphics and Printing 5 36,150 613 58,972 Miscellaneous Manufacturing 9 11,070 709 15,614 SERVICES Commerce 5 18,500 921 20,087 Communications 1 40,000 300 133,333 TOTAL 369 3,348,263 74,181 45,136 Note: Data cover 1995 to June 1998. Source: Computed from information provided by the Secretaria de Desenvolvimento (SDE). 33 This investment is being undertaken by a joint venture of several private sector firms. Its economic viability (as well as its profitability) will depend - among other things - on the price at which natural gas is provided to the plant. A gas pipeline, to be undertaken by the Petrobras group, is envisaged for construction from gas fields in Rio Grande do Norte to Pacem. 34 The data are ex ante data, i.e., those provided by the firm in anticipation of the project. Since there is supposedly a premium on labor intensity, the employment projections may indeed be overstated, signifying that the investment costs per job may be underestimated. 29 1.69 One thing not shown in the aggregate information presented inTable 1.7, but which is apparent from an examination of the underlying data set, is that the great part of the approved projects are fairly large in size. Of the total of 369 projects, only 67 envisaged investments of less than R$500,000 (roughly US$500,000), representing only one-half of one percent of the total p anned investment. In practice, the incentive system has focused on the larger firms. Small firms are effectively left out. 1.70 The state incentive based upon the ICMS existed prior to 1995, although there was less activity under the system, particularly prior to 1991. For the period 1991 to 1994, the system operated essentially as it currently functions. There are three notable differences. First, the level of activity was somewhat less. Over the four year period 1991-94 a total of 204 projects were approved, totaling R$2.6 billion (in prices of 1997).35 This compares to 369 projects totaling R$3.3 billion for the three and a half year period January 1995 to June 1998. Actual implementation in the 1991-1994 period was quite slow. By mid-1997 only 66 of the 204 approved projects were actually functioning. These delays, according to a number of firms interviewed, were mostly due to the then prevailing unstable macroeconomic situation and related economic uncertainty. A second difference relates to the evolving decentralization from the greater Fortaleza metropolitan area. For the earlier period three-quarters of the approved projects were for the Greater Fortaleza region, as opposed to less than 60 percent for the later period. A third difference - while perhaps not so dramatic - relates to the capital intensity of the projects. The earlier, 1991-94 approved projects possessed a cost per job of more than R$59,000,36 in comparison R$45,000 for the 1995-98 period. In both cases, the level of capital intensity appears quite large. 1.71 Administration of the State Incentives. The legislation establishing the ICMS- related incentive framework for Ceara has evolved gradually, with important decrees in 1993, 1994 and 1995 establishing the financing rules and further emphasizing the decentralization dimension of the iicentives.F The incentives are formally financial incentives, with the financing amounts - funded in the form of the Fund for Industrial Development (Fundo de Desenvolvimnento Industrial or FDI) through the state bank (the Banco do Estado do Ceara or BEC) - related to a firm's ICMS tax liabilities. There are formally three different modalities for the FDI: (i) PROVIN (Programa de Incentivos ao Funcionamento de Empresas); (ii) PDCI (Programa de Desenvolvimento do Com6rcio Intemacional e das Atividades Portu&rias do Ceara); and (iii) PROAPI (Programa de Incentivos as Atividades Portuarias 6e Industriais do Ceara). In practice it is the PROVIN modality that is the most important and accounts for most of the incentives awards. The incentives take the form of financing the firm's ICMS tax liabilities covering an eligibility period of up to 20 years, with a three year grace period. After the three period grace period, the financed amount is due, subject to a forgiveness in the principal amount (normally 50 percent) and monetary correction applied to the balance according to the TJLP (Taxa de Juros de Longo Prazo, currently at 9.75%). 35 A discussion is contained in Jose Romeu de Vasconcelos et al, Ceara: Economia, Finangas Publicas e Investimentos nos Anos de 1986-1996, Relati5rio de Pesquisa, IPEA/PNUD, Fortaleza, October 1997. 36 The 66 projects actually implemented had an average investment cost per job of some R$55,000. 37 Decrees No. 22,719-A193 and No. 23,113f94. 30 1.72 While the basic incentives are amply defined, there is considerable discretion allowed to the implementing authorities in the specification and award of the incentives. Ambiguity exists on several levels. First, there is the matter of the activities which can be benefited. While the general intent seems to be to provide incentives for manufacturing and for a number of manufacturing activities that are clearly specified (e.g., textiles, metalworking, capital goods, etc.), there are provisions to allow awarding the incentives to "any pioneer industry in the state," or "any industry that has at least 10 percent participation of foreign capital." 1.73 Second, there seems to be some ambiguity in the level of the incentives. There is a maximum for the incentives (financing) of 75 percent of the ICMS payable permitted and restricted in principle to those locations furthest from Fortaleza. In practice, the incentive amount has sometimes exceeded 75 percent. The remaining 25 percent of the ICMS is reserved for municipal governments, but sometimes municipal governments have found it advantageous to provide their portion as well to the investing firms as part of the overall incentive package. In addition, some firms have been awarded the incentives at the 75 percent level even if they are in close physical proximity to Fortaleza.' Exceptions appear to focus on two broad categories - the need for infrastructure (e.g., a port) or labor intensity and employment. 1.74 Third, there appears to be ambiguity on the time limits of the award period. The law has specified a 20 year limit for three activities - steel, automobiles and petroleum refining. A 10 year period is allowed for activities outside the Greater Fortaleza Metropolitan Region, with 6 years permissible to those firms operating within that Region. In practice, some flexibility exists. If a firm is highly labor intensive or operates with what is considered to be modern technology (tecnologia de pronta), a longer period for the incentives is permitted. Recent practice has included extensions up to 15 years. Finally, there also seems to be some flexibility in the amount of loan forgiveness. A maximum of 99 percent forgiveness is allowed. 1.75 With such diverse experience in the awarding of the incentives and with such descretionality in the hands of the state authorities, it is clear that much depends upon the negotiation process for a firm interested in receiving the incentives. Considerable energies go into the application process. Apart from any potential for abuse that such a system may allow, there seems to be a nonuniformity of treatment across firms. 1.76 Formally, the ICMS-based incentive system is administered by the state government in the form of the Industrial Development Council of Ceara (Conselho de Desenvolvimento Industrial do Ceara or CEDIM). CEDIM is nominally presided over by the Governor and consists also of the Secretaries of Economic Development, Finance, Planning, and the President of BEC. The Executive Secretary of the CEDIM is the Secretary of Economic Development (the SDE, previously the Secretariat of Industry and Commerce). In effect, it is the SDE that presents the proposals and applications for approval and in practice engages in the negotiations with the applicant firms. While the SDE purports to analyze the proposals, its staff is quite restricted and the process focuses on negotiation. Interestingly enough, the negotiation frequently transcends the 38 One firm dealing in petroleum products argued that proximity to the port of Fortaleza was essential and that they should not be penalized because of the nature of their business. They received the full incentive amount. 31 ICMS-related incentives. Land and subsidized public utility services are sometimes offered as part of the package to allure firms to Ceara. 1.77 Economic Effects. There are two major economic effects of the ICMS-based financial/fiscal incentives: (i) their fiscal costs; and (ii) the distortions they introduce. 1.78 Fiscal Costs. There are two means of measuring the fiscal costs of the incentives for the state Government. A direct estimation of those costs is available on a cash flow basis through an analysis of the components of the FDI (Fundo de Desenvolvimento Industrial). The net disbursements (gross disbursements minus repayments to the FDI by the beneficiary firms) for 1996 and 1997 are presented in Table 1.8 for the three modalities of the incentives. The incentives carried a fiscal cost amounting to 4.2 percent of the state government's net current revenues in 1996 and 4.5 percent in 1997. Expressed as a percentage of the state's GDP the fiscal cost amounted to 0.45 and 0.44 percent of GDP in 1996 and 1997 respectively.39 These estimations of fiscal cost presume that the firm's would have located in any case in Ceara; this may not be the case. If not, the estimated fiscal costs may be over-represented. No matter what the bias in actual measurement may be, whether these incentives are excessive or not is a matter of judgment.0 Table 1.8: Net Disbursements of the ICMS-Related Incentives, 1996 and 1997 (in millions of current R$) Year PROVIN PROAPE PDCI Total Net Total as % of Current Net Total as % of Disbursement State Revenues (RCL) State GDP 1996 77.1 0.3 0.0 77.3 4.2% 0.45% 1997 77.9 4.2 1.1 83.2 4.5% 0.44% Source: computed from SEFAZ information. See Annex 4. 1.79 A second, more indirect, means of estimating the effect of the fiscal incentives on fiscal revenues is to examine actual ICMS tax revenues. Effective rates can be estimated by comparing actual tax collections with value added, the base on which the ICMS is mostly levied. Table 1.9 presents a summary of effective rate estimations for 1996 and 1997, estimated using nominal values for both tax collections and value added amounts. The nominal tax rate for most manufacturing activities is 17 percent. The effective rates of 11.5 and 10.3 percent, respectively for 1996 and 1997, show considerable leakage.4' Some of this shortfall can be attributed to administrative imperfections - totally expected in any economy. Another form of leakage demonstrated in these effective rates may be in the concession of the ICMS-related incentives. But the difference between the effective ICMS rates for manufacturing and the maximum of the statutory rate of 17 percent puts an upper bond limit on the magnitude of the estimated incentives. 39 Since the incentives are meant to encourage industrial development, perhaps a better reference point is manufacturing value added. The fiscal cost amounted to 2.4 percent of manufacturing output in 1996 and 2.3 percent in 1997. 40 To put the matter in perspective, one can note that during the period of heavy protection and import substituting industrialization during the 1970s and early 1980s in Brazil average effective rates of protection for manufacturing were on the order 30-35 percent. (Tyler, 1983) The present aggregate rates of 2.4 percent of value added seem modest in comparison. Of course for some firms the protection afforded by the ICMS-related incentives may be substantial. 41 The reasons for the fall in the effective ICMS tax rates - mostly related to the one time effects of the implementation of the so-called Lei Kandir- are treated in Dillinger (1998). 32 Table 1.9: Aggregate Effective ICMS Tax Rates, 1996 and 1997 (in %) Sector 1996 1997 Agriculture 0.2 0.2 Industry 10.6 9.4 Manufacturing 11.5 10.3 Services 8.9 5.0 TOTAL 8.8 6.0 Source: calculated from SEFAZ and IPLANCE information. See Annex Table 83. 1.80 Distortions. The description above of the incentive system related to the ICMS has discussed the features of the projects approved under the incentive system. In doing so, we have presented some evidence of a number of distortions introduced into the economy. Some of these distortions are implicit in the nature of the incentive system itself. Others are a result - sometimes unintended - of the administration of the system. These major distortions are described in the next few paragraphs. 1.81 A major distortion in the incentive system relates to the application of the ICMS itself. Activities that are not taxed are simply not relevant for the administration of the incentives. Most important among those nontaxed activities are agriculture, tourism and exports. By omission they are not provided incentives. One can argue that there is an unintended de facto bias against export production since exports are already exempt for the ICMS. In addition, it is indeed the intent of the incentives legislation to focus on industrial activities, to the explicit exclusion of agriculture and tourism. Most economists would question the wisdom of such selectivity. 1.82 A second distortion stems from an operational bias in favor of large firms even though the program does not formally exclude small firms. This bias is apparent in the data presented and summarized in Table 1.7. The reason is quite simple: there are substantial transactions costs in seeking and obtaining the incentives. Only large firms seem willing or able to bear these costs. A third distortion relates to a capital intensive bias, also referred to above. Even though employment generation is a declared objective of the program, the approved projects demonstrate very high capital/labor ratios, i.e., the investment cost per job created is quite high - averaging R$45,000 per job. 1.83 A fourth distortion of the existing ICMS-based incentives system is its discrimination against existing prediction capacity. Indeed, the purpose of the incentives is to seek out and attract new investments to the state. This sometimes places existing firms at a competitive disadvantage vis-a-vis the new entrants. One firm interviewed explained that two new producers of one of its major products were being established in Ceara with the benefit of full incentives and that the existing firm was not going to be able to compete on the basis of price. As it turns out however, the existing firm - long established in Ceara - was taking advantage of similar fiscal incentives in a neighboring state and expected to be able to supply the Cearense market from its plant there, despite substantial transportation costs. 1.84 A fifth distortion in the incentive system originates in its administration. There exists an emphasis in practice on the part of the SDE officials managing the system to pursue decentralization objectives extending beyond the scope of the incentives legislation. The Government discourages the granting of incentives to more than one firm in the same sector in a given geographical area. The intention is spread industrial activity as widely as possible among municipalities. Despite the lip-service at the policy-making 33 level to the importance of promoting the formation of clusters, the Government is actually pursuing the opposite, i.e., an anti-cluster policy. 1.85 Finally, a distortion exists in the possible tendency to defer modernizing and expansion investments for firms functioning under incentive system concessions. Incentives can be awarded for plant extensions and modernizing investments. If a firm is presently covered under the incentive system there may be less reason to accelerate plant modernization if the lifetime of the incentive benefits can be extended later on. One firm interviewed explained that it felt no rush to proceed with a needed modernization in one part of its plant, because it would be at a disadvantage under the incentive system, even though the investment would eventually be necessary for it to remain competitive. Government Investment Promotion 1.86 The responsibility for investment promotion within the state government lies with the Secretariat of Economic Development (Secretaria de Desenvolvimento Econ6mico or SDE). This function is generally seen as an extension of the ability to negotiate and concede incentive packages with firms. There is no separate office or unit within the SDE that deals with investment promotion.42 Indeed, the emphasis in SDE is on the negotiation of the incentives with individual firms. Little organized effort is given to actually marketing the state's rather attractive investment environment and seeking out potential investors. In addition to there being no pro-active and concerted marketing for new investors, there is also little in the way of passive marketing. For instance, it is no easy task for potential investors to get information about investment opportunities in Ceara. For example, while the state Government has a website on the internet, there is little attention devoted to selling the state to potential investors.43 In a more general way, what little promotional activity there is ad hoc and highly personalized. In addition, it is also focused almost exclusively on attracting industrial firms. To the extent that there are concerted efforts - other than those simply imbedded in the incentives - to attract new ventures and investment, those effcrts have been concentrated - generally through individual visits of ranking state officials - on the country's Center-South. 1.87 Little has been done to allure foreign direct investment. Indeed, of all the firms establishing productive facilities in Ceara, there is not one case (at least that the author was able to discern) of a foreign firm establishing its first operations in Brazil in Ceara. In all cases of multinational firm involvement, there has been prior Brazilian experience in the Center-South. Ceara operations are viewed as an extension of the overall Brazil involvement. 42 Over the past several years the SDE has undergone major reform and streamlining. In addition to a name change - from the Secretariat of Ctommerce and Industry to the Secretariat of Economic Development - a reorganization has substantially reduced its size. Its number of employees has reportedly been reduced from around 600 to a little over 100. 43 By way of comparison and possible examples of best practice, one can refer to the websites maintained by the governments of some American states as one part - but only one minor part - of an investment promotion strategy. The states of South Carolina and Virginia have been particularly successful in promoting investment, particularly aftracting new investment from other regions in the US and from other countries. 34 Summary of Major Recommendations 1.88 A major conclusion of the present study is that the statewide policy environment is largely an appropriate one. The overall orientation and direction of state economic policies is consistent with promoting efficiency and growth. The general policy implication is largely for a continuation (with some adjustments) of the present policy stance and direction. Importantly, the state Government should avoid the temptation of doing a number of things that it is presently not doing in a major way. It should avoid a pro-active approach of.targeting policy interventions to support individual firms or sectors (e.g., steel, petrochemicals). To the extent that such interventions do exist they should be de-emphasized and phased out. 1.89 Among other things, the interviews conducted as a part of this study have lead to a general conclusion that, despite a growing sense of modernization and awareness of the needs to increase competitiveness, old attitudes and habits are long lasting and slow to change. First, there is still a general tendency to view the Government - whether federal, state or even municipal - in a paternalistic way. Government is still looked to as a provider of subsidies (in their various forms) and as a resolver of disputes and problems. Second, a strong preference, and even expectation, of protection afforded by government intervention to producers still prevails, despite lip service to the concept international competitiveness. The Government is looked upon to protect domestic industry from the vagaries of the international market place. Indeed, many of the recently established firms have set up in Ceara to produce for the Northeast's market; others view their market as a national one. Precious few firms have set up primarily to service export markets. To some extent this preference for domestic markets is a natural one, stemming from the nationwide trade, commercial and macroeconomic policies. Domestic markets, despite substantial liberalization in the early 1990's, continue to enjoy significant protection. Export Processing Zone(s) and Bonded Customs Warehouses 1.90 As stated above, present Brazilian legislation, enacted in 1988, permits the functioning of Export Processing Zones (EPZs). Additional legislative initiatives are now being debated and processed in the Congress. The purpose of proposed changes is to improve upon and liberalize the existing legislation. In particular, more liberal rules are proposed governing the sale of output in the domestic market. 1.91 It is recommended that the state Government of Ceara reconsider the advantages and disadvantages of moving to put into operation an initial EPZ. The logical site for such an operation would be in the new port of Pacem. Indeed a successful EPZ there could help make the port venture a very visible success as well. 1.92 There is no presumption that state government monies should be used in establishing, financing or administering the EPZs. The private sector has found it attractive in other places to set up and run EPZs. In the case of Pacem however the state Government would have to exercise some initiatives. 1.93 The Government should also consider setting up one or more new bonded customs warehouses. One should operate in Pacem, irrespective of a possible EPZ. 35 ICMS-Related Incentives 1.94 In view of the distortions generated by the ICMS-based incentive system, some revamping would appear to be desirable. Two options - one marginal and one radical - are posited for Government consideration. They are: (a) Option One: Marginal Changes. Modifications in the way in which the system is administered can be envisaged to reduce some of the distortions resulting from the incentive system. These changes could include inter alia: (a) Government refusal to extend the covered incentives period for firms benefiting from the incentives; (b) granting incentives to more than one firm in an area producing in a given sector; (c) substantially reducing the scope for administrative discretion in the awarding of the incentives; and (d) simplifying the process of granting the incentives. The major advantage of this option is that it would be relatively simple to implement, since no legislative action would be necessary. Its major drawback is that it would leave the core of the incentive system, with its inherent distortions, unaffected. (b) Option Two: Replacing the Present System with a Wage Subsidy for Unskilled Workers. There are a number of substitutes possible for the ICMS- related incentives. One possibility would to replace it with a system of incentives based upon the payroll taxes (the encargos sociais) paid by employers. The state Government could simply assume and pay to the federal Government a share of these payroll taxes for unskilled workers receiving up to, say, two times the minimum wage. The substitute system would have to be introduced gradually, including (a) grandfathering in firms operating under the current ICMS-based incentive system and (b) carefully calibrating the new system so that it would be at worst fiscally neutral. The calibration process would have to entail a careful quantification of the awarded incentives and of their effects for firm payroll tax liabilities. Over time the new system based upon the state payment of payroll taxes could be gradually extended from new firms - the target group under the present system - to all firms paying such taxes. The main benefits would be that the new arrangement would eliminate the distortions existing under the present system, remove a distortion driving unskilled wage costs above their shadow price, provide an incentive to regularize workers under the labor code, and reduce a major element in the so-called Custo Brasil. It would also be nondiscriminatory, non-discretionary and fully transparent. Drawbacks would include: the need to do a careful analysis to assure fiscal feasibility for the state; a possible spreading of the gains to individual firms so thinly (especially after the extension to all firms employing unskilled labor) so that their benefits would be much less than those presently extended to firms under the present ICMS-based incentive system; and, finally, a partial loss in the state's competitive position in the so-called "Fiscal War" with other states to attract new investment. 36 Government Investment Promotion 1.95 Several suggestions are offered with a view to increase the effectiveness of the state Government's investment promotion. First, the Government should consider a reorganization of the SDE to permit a greater professionalization of the investment promotion function, including a separation of investment promotion from any negotiation of the incentives. Such a reorganization need not involve new budgetary commitments. Second, investment promotion activities on the part of the Government should not concentrate on industry but should also include other activities, including tourism. Also by undertaking the establishment of an initial EPZ in Pacem, the reformulated SDE would concentrate its efforts not on negotiating incentives but seeking out investors and selling the image of the state. This is also the approach that should be pursued to attract investment in tourism facilities. Third, the SDE should adopt a greater emphasis on strengthening public - private sector partnership arrangements in attracting new investments. Taking greater advantage of private sector organizations - such as the FIEC and the ACC - would be obvious starting points. Fourth and similarly, the SDE should consider contracting out of a number of functions SDE to the private sector, including early on the preparation of promotion materials - e.g., a Doing Business in Ceara (in both English and Portuguese) guide for prospective investors. Finally, the SDE's investment promotion office should seek outside professional advice and assistance on attracting foreign direct investment. One example of such support might be to involve the World Bank/IFC Foreign Investment Advisory Service (FIAS). Tourism 1.96 The Government's overall approach to promote tourism should be threefold. First, efforts led by the state Government at its highest level should go into the development of an integrated state strategy for tourism development. The state strategy should include a strong private sector participation and entail a regional focus as well as one based upon Ceara. To proceed with the formulation of such a strategy a special Commission is suggested, with technical support involving international as well as national expertise. One input into the Commission's technical work would presumably be the recent work on tourism clusters done under the auspices of the Iniciativa pelo Nordeste. 1.97 A second dimension of the state Government's approach, indeed as a part of the strategy indicated above, would be to access the infrastructure requirements for successfully developing tourism in the state. Resources made available under the PRODETUR program undoubtedly have helped. Nevertheless, a preliminary assessment is that serious bottlenecks in such infrastructure services as water, sewerage and energy are either present or are emerging for tourism. But this needs to be more carefully assessed, especially in view of the scarcity of public investment resources and other demands placed upon them. Getting private sector participation in the provision of such services should also be an objective. 1.98 Third, state public finance questions need to be addressed as related to tourism. Currently, hotel and restaurant services are exempt from payment of the ICMS. At some point, the Government may wish to consider changes in this status as part of a generalized tax reform for the ICMS. The international experience has to subject tourism 37 - and tourists - to taxation, and there is no prima facie reason that Ceara should be different.44 Infrastructure and Education 1.99 The use of public resources to finance infrastructure and other public goods lies at the heart of the state government's economic management and strategy. Making sure that scarce public resources are effectively rationed and used is a primary responsibility of good public administration. In this context, the Government may want to consider a small, but well placed and highly technically qualified, unit to analyze and vet proposed public investment projects. The logical place for such a unit would seemingly be SEPLAN, possibly as part of a budget group. The public sector investment program however should be developed on a multi-year basis. As part of a results oriented and cost conscious approach to public expenditures, the Government would be well advised to consider a re-prioritization for some of its public sector investments and expenditures, with a greater emphasis on education and infrastructure and less on large scale irrigation projects. 1.100 A final note should be devoted to education. Ultimately, the development prospects of the state are tied to its human resource base. Improving that base through educational programs would appear to be a very high priority for the state Government. 44 See Annex Table 3 for some tourist service taxes in the Caribbean. 38 2. THE LAND: REVIVING THE RURAL ECONOMY This chapter is based on a background paper by Alberto Valdes (RDV) The excellent assistance of Guilherme Bastos and Detlev Puetz is gratefully acknowledged 39 Introduction Objectives 2.1 Overall, Ceara's agriculture's has experienced a significant slowdown during these last years. Labor productivity in farming particularly in the Sertao is extremely low, and the incidence of poverty in rural appears is very high. As part of a Ceara State Economic Memorandum, this section has sought to provide an assessment of past performance of the sector, tried to identify the main factors that explain such poor performance, and present plausible policy options. As part of this analysis this section examines the potential role of agriculture (especially in irrigated areas) for growth and poverty reduction in rural areas of the State and what are the implications for public policy. Structure of the Report 2.2 The report comprises three main sections. One looks in some detail at the agricultural sector performance since the Census of 1985, and the second section presents an analysis of household income and poverty in Ceara, using the LSMS for the Northeast of Brazil, adding information gathered from other sources. In the first part we cover the main findings on the evolution of farmed area and crop production, livestock herd, composition of agricultural production, trends in irrigated area and output mix under irrigation, and present a brief analysis of factors which could explain the slowdown of the sector. As part of this analysis we also present a characterization of the farmstructure by size and employment. The second part consists of a quantitative analysis of household income by type of farms and other household characteristics. The last section presents the main findings and policy implications. Data Sources 2.3 In addition to the material collected during the World Bank mission to the State of Ceara in July/98, as well as World Bank material, in preparing this report we used two key data sources, namely (i) the agricultural Census, 1995-1996, from IBGE; and, (ii) the Household survey (Pesquisa sobre Padrao de Vida, 1997) which is representative for the Northeast region, not specific for the State of Ceara. Background 2.4 The Northeast has long constituted the single largest area of rural poverty in Latin America. This Region, covering nine states and part of a tenth, accounts for 19% of Brazil's total land area and 30% of its 147 million population. More than half of all Brazilians living in poverty, and almost two-thirds of the country's rural poor, lives in the Northeast. According to a recent study by the Ministry of Planning and Budget, some 12 million rural inhabitants of the Northeast live in extreme poverty, with annual per capita incomes under US$214 (less than one-tenth of the national average). Among the underlying causes of rural poverty in the Northeast are the relatively poor resource base of large parts of the region and variable agro-climatic conditions which make them vulnerable to drought. Skewed access to land and the virtual absence of a functioning 40 rural financial system for the poor are additional constraints. Limited input use and slow rates of technology adoption characterize the Northeast agriculture. Productivity is low, with output per farm worker less than half that of other regions. Overall Northeast agricultural GDP growth was negligible during 1991-1994. 2.5 Ceara is the fourth largest state in the Northeast and has a total population of 6.4 million. The entire state area is considered part of the 'drought polygon", which also includes other states, such as Rio Grande do Norte, Paraiba, Pernambuco and Bahia, and smaller proportions of all the other Northeastern states except Maranhao. The dry period last for about eight months, with a very irregular rainfall, with an average of approximately 620 mm and average temperatures of about 25°C. Ceara is the only state in Brazil without permanent rivers. The limited humid areas of Ceara are located in a few fertile highlands. Soil types of medium and low fertility are found in the semi-arid and infertile coastal areas. Principal agricultural products include cotton, fruit (principally cashew), beef and milk, beans, com, sugarcane and cassava. The state enjoys a long coastline that supports a growing tourist industry and extensive fishing industry, including exports of lobster. 2.6 In the past two decades, Ceara's economy has undergone rapid urbanization and industrial expansion, leading to a significant concentration of income and economic activity in the state capital of Fortaleza. Available evidence demonstrates a sharp decline in agriculture's share of GDP--although the agricultural sector is still vital to the economic well being of Ceara's 2.2 million rural inhabitants. Rural poverty in Ceara, as elsewhere in the Northeast, is closely correlated with agro-climatic conditions, the poor natural resource base of the semi-arid zone, and skewed land distribution. The drought of 1993, which affected nearly three-fourths of the Northeast and some 12 million people, was particularly devastating in Ceara, where agricultural output declined by 47.2%. Small farmers lack modern technology and adequate working capital. Irregular rainfall produces crops of low quality with minimal income-generating capacity. For the landless wage workers drought eliminates their principal, albeit temporary, source of income and employment. In search of economic alternatives and social infrastructure that would provide sustainable living conditions, these vulnerable family groups migrate either temporarily or permanently to urban centers in the interior or to the capital, where they join the ranks of the urban informal sector and add to already deteriorating urban conditions. 2.7 Until the early 1980s, agriculture was predominantly dependent on cotton and livestock. Nowadays, agriculture is more diversified. The predominant production system vary among its main subregions, namely the Northeast coast (cashew, coconut, and livestock near Sobral); the North (beef and milk, cotton, poultry and some food crops; the Sert6es (cotton, extensive grazing system, maize, beans, and cassava); the region around Jaguaribe River (annual cotton, irrigated rice, and cultivated pastures); and the South (dryer areas, with extensive grazing system, and more humid areas, with beans, maize, cotton, sugar cane and rice). 2.8 Salient features of the rural sector of Ceara are (i) a high volatility of agricultural production due to severe droughts; (ii) high degree of dualism between the Sertao and commercial farming in irrigated areas, and between a large number of small semi-subsistence farming and medium-large size commercial farms; (iii) very slow 41 overall agricultural growth;45 (iv) extremely low levels of schooling; (v) low labor productivity, (vi) extreme disparity between agricultural and non-agricultural labor productivity4, and (vii) according to official statistics, agriculture continues to be a major provider of employment - approximately 43% of the active population - contributing with less than 6% of the State's GDP (in 1997). 2.9 By the end of 1995, the State's Secretariat of Agriculture (SEARA) presented a multi-sector plan to alleviate rural poverty and promote the economic development of the rural sector, the Plano Indicativw de Desenvolvimento Rural do CearS: 1995/1998. Many of the issues above are directly, or indirectly addressed by the set of programs, which will promote irrigation and agro-industrial centers, improve agriculture practices without irrigation (agricultura de sequeiro), strengthen livestock, develop aquaculture and fishing, and finally promote the farm restructuring. Figure 2.1: Ceari's Agricultural GDP 1,300 1,200 0 _ - F 0 - ---- - ----- -- - - -- --- - \-/ c-Avg.90Q91-96197 trend line 800 - ------------ - -G D P i -. - Linear Regression (GDP) 700 1990 1991 1992 1993 1994 1995 1996 1997 Agricultural Sector Performance 2.10 The exceptionally high year-to-year instability in agricultural production in Ceara is well documented in various reports.47 Less well recognized is the sharp desaceleration of the State's agricultural economy since the late 1 980s. For example, the annual growth rate in agricultural GDP in Ceara has declined dramatically, from 8.03% p.a. for the 1981-86 period to 1.38% p.a. between 1987 and 1997. Even the 1.38% growth p.a. could be an overestimation of the actual growth rate. Examining the 1995 45 However, there are important subsectoral changes. For example the near extinction of cotton could be partially compensated by the development of new and higher value products such as fruits. 46 As measured by the agricultural GDP per capita, which is the source of widespread and deep rural poverty. 47 See, for example, World Bank, 'Public Expenditures for Poverty Alleviation in Northeast Brazil: Promoting Growth and Improving Services", World Bank, 1998. 42 agricultural census figures one finds that the census figures for 1985 and 1995 point to a significant decline in farmed area and crop production and, at best, a stagnant livestock production. In fact, calculating the agricultural GDP growth for average 1990/91 to 1996197 figures suggest an even lower annual (compound) growth rate of 0.84% p.a. (Figure 2.1, and Annex Table 14).48 2.11 It is then not surprising to find that between 1986 and 1997 the share of agriculture in the state's GDP declined significantly, from 8.26% to 5.72%. Although the decline in the share of agriculture in the economy is a worldwide structural phenomenon during the growth process, 5.7% seems an exceptionally low share for the level of development of Brazil, and particularly for Ceara. Major Reduction in Farmed Area, Crop Cultivation, and Size of Livestock Herd 2.12 The sharp decline in the total farmed area since 1985 is striking. According to the agricultural Census figures for Ceara, between 1985 and 1995/96 the crop area (annual and permanent) fell by 42.4%, while total farmed area fell by 18.6% (Table 2.1). Improved pastures, although still minor, increased by 76.4% in the area since 1985. Natural pastures still support most of the 2.4 million heads of cattle, mainly in a semi- extensive grazing system. Table 2.1: Land use in 1985 and 1995196, in ('000) hectares, Ceara. 1985 1995/96 Change Total farm area 11,009 8,964 -18.6 Cultivated Area 4,569 3,281 -28.2 Crops (annual and permanent) 2,376 1,369 -42.4 Improved Pastures 112 197 75.9 Commercial Forests 7 25 257.1 Fallow (em descanso) 808 761 -5.8 Unused productive area 1,266 929 -26.6 Natural Pastures 3,382 2,435 -28.0 Natural Forests 2,436 2,700 10.8 Unused land 623 548 -12.0 Source: IBGE - Censo Agropecu6rio, 1995-1996. 2.13 Based on the Census data for 1985 and 1995/96, one observes a drastic reduction in crop area in cotton (both herbaceo and arb6reo) falling from 757,000 ha to 17,000 ha, beans (458,000 to 373,000 ha), maize and others (Table 2.2 and Annex Tables 41 and 42). The exception is cashew that increased from 163,000 to 280,000 ha, coconut and banana. Moreover, in addition to the drastic reduction in total farmed area, the share of some of the major crops in total land use also changed significantly. For example, cotton fell from 33.9 % in 1985 to 1.3% in 1995/96. But maize, beans, cashew, and banana have increased relatively to the proportion of land area cultivated. On the other hand, looking at the figures from the PAM, it is clear that the decline in cotton area was mostly compensated by a significant increase in crop area with beans, maize, cashew and rice. The item other fruits although increased, remained as a low share of the total harvested area. The difference between the Census data and the PAM data 48 All agricultural GDP computations are based on IBGE time series. Trend figures based on least squares regressions suggest a 2.1% growth rate for the 1990/1997 period, but are influenced by two very low production years, 1993 and 1990. 43 regarding the change in acreage between 1985 and 1995 for selected crops raises a question about the true data and it is striking. Comparing columns (A) and (B) inTable 2.2, census data reports a drastic reduction of area harvested with rice, beans, cassava and maize (-29.7%, -18.6%, -55.8% and -24.1%, respectively), while using the PAM data, area harvested with these crops shows a significant increase when comparing to levels of 1985-86 (66.8%, 67.7%, 1.1°/o and 46.7%, respectively). 2.14 Except for poultry, the picture for livestock shows a similar declining trend in the size of the herd between 1985 and 1995/96. The stock of goats, cattle and sheep fell by 19.4%, 3.8% and 1.8% respectively. Pork inventories dropped 15.9%, however, poultry inventories, increased by 16.7%. Here, the discrepancy of the data between the Census and PAM discussed above, also applies to some of the livestock figures, such as goats. Table 2.2: Change in Cultivated Area and Livestock Figures, for selected products, in Ceari. 1985 1985 1986 1994 1995 1995196 Change Change (Censo) (PAM/P (PAM/P (PAM/P (PAM/P (Censo) (%) (%) PM) PM) PM) PM) (Censo) (PAM/P PM) shares (%) (A) (B) Cotton (Herbaceo) 16.9 14.8 14.9 5.3 4.2 0.6 -97.9 -66.8 Cotton (Arb6reo) 17.0 21.7 17.5 3.3 3.2 0.7 -97.6 -82.8 Rice 3.3 1.8 2.6 3.5 3.7 4.0 -29.7 66.8 Banana 1.0 1.4 1.4 1.7 1.9 2.7 60.4 29.7 Coffee 0.7 0.5 0.4 0.4 ..... -28.7 Cashew (nut) 7.3 10.5 9.6 14.3 14.5 21.3 71.8 48.9 Sugarcane 1.7 2.2 2.5 1.9 1.9 1.6 -46.2 -15.9 Coconut 0.3 1.0 1.0 1.7 1.7 1.6 250.0 78.3 Bean 20.5 18.1 21.0 32.1 31.5 28.4 -18.6 67.7 Cassava 4.3 4.6 5.3 4.1 5.7 3.2 -55.8 1.1 Maize 27.7 21.4 21.9 30.8 30.6 35.8 -24.1 46.7 Other Fruits 0.3 0.3 0.4 0.4 ..... 43.6 Crops, total 100.0 100.0 100.0 100.0 100.0 100.0 -41.3 3.7 number of heads Beef 2,475 2,500 2,605 2,186 2,266 2,382 -3.8 -12.8 Sheep 1,635 1,259 1,337 1,333 1,369 1,606 -1.8 4.1 Goats 987 949 1,029 1,080 1,116 796 -19.4 11.1 Pork 1,245 1,245 1,291 1,201 1,211 1,047 -15.9 -4.9 Poultry 17,728 18,087 20,033 19,681 18,718 20,690 16.7 0.7 Tabulation: World Bank Mission. Note: Column (B) reflects the percent change in average harvested area from 1994-95 with respect to 1985-86. Sources: IBGE - Censo Agropecunrio 1995-1996; FPAM - Pesquisa Agricola Municipal; PPM - Pesquisa Pecuana Municipal. 2.15 Thus, the broad picture that emerges from the Census data suggests a dramatic slowdown of the agricultural economy in the State of Cearasince approximately the mid-1980s, both in terms of total farm area, crop area and cattle inventories, poultry is the exception.49 There are several factors underlying this decline, although determining the relative weight of them would require further analysis. Several studies have addressed the specific case of the dramatic decline in cotton production (97% between 1985 and 1995-1996). Undoubtedly, the decline in the cotton sector is perhaps the major factor. But our analysis also suggests that, while less dramatic, the decline affected a large segment of the sector. Among the possible contributing factors to this decline one should mention the decline in the falling real producer prices since 1993-94, for most 49 Again, this decline is not fully reflected in the agricultural GDP figures as explained in para. 2.6 above. 44 farm products, and the falling aggregate domestic demand, due to Brazil negative per capita growth rate during 1985-1995 (see para. 2.24). 2.16 The collapse of the cotton sector, as explained by Haddad et al. (1994)5, is the result of the incidence of bicudo (cotton weevil) on the cotton arb6reo, a fall in the world price of cotton, and the effect of changes in the labor code5' (which resulted in a sharp increase in the payroll tax increasing the cost of labor), all contributing to a break down of the traditional share-cropping production system in the Sertco, based on cattle, cotton, and beans. So far the region has not been able to resolve the effect of the bicudo. While hopes are placed on cultivating pest resistant cotton (herbaceo), the cultivation of herbaceo is vulnerable to droughts, and thus requires irrigation and chemical fertilizers, which makes it less suitable for small farmers in the semi-arid regions of the SertAo. Under irrigation, it would compete with tropical fruits and other high value products. 2.17 Drought conditions in most years, unfavorable soil conditions (low in organic matter, poor water retention) underground water that is scarce and in most cases too saline for cultivation, all conform very adverse condition for farming in the Sertao. What can small farmers produce competitively under these semi-arid conditions without irrigation it is still a major unresolved challenge, as also perceived by Haddad et al. (op. cit.): "No tocante a agricultura de sequeiro, continua a busca para identificac,o de um modelo estruturante, capaz de sustentar a popula9ao do interior. A busca deste modelo e importante porque as restric6es de 6gua nao permitirao o aproveitamento de todos os solos aptos a irriga,co. (...) Num ano de seca, a produrao agricola pode ter um colapso total. Em algumas localidades, a agricultura 6 virtualmente eliminada, deixando desempregada a grande massa de trabalhadores rurais e pequenos agricultores." 2.18 Several products were often mentioned during the World Bank mission as offering a promising prospects for growth, such as goats and sheep. Nonetheless, these alternatives have been researched at least on the technology for not less than 15 years, and still represent a tiny subsector, amounting to less than 1.0% (each) of the agricultural GDP. Changes in the Output Mix - their share in the sector's economy 2.19 If one takes the broader definition of agricultural GDP (including agroprocessing activities, autonomous and auxiliary services), a slight increase in the share of crops and services is observed, between 1990/91 and 1996/97, while livestock and crops remained practically constant, and extrativismo vegetal and agroindustry decreased their participation in the total agricultural GDP (Table 2.3). Excluding agro- 50 See, Paulo Roberto Haddad, Antonio Rocha Magalhaes and Paulo Fontenele e Silva (1994), in "Estado do Ceara: Analise das Financas Publicas e Tendencias S6cio-Econ6micas", Banco Interamericano de Desenvolvimento (BID). 51 See Brazil: The Management of Agricultural, Rural Development and Natural Resources. World Bank, July 31, 1994 (Annex B: Social Security and Rural Development, vol.2). 45 processing and services, the share of the crops and livestock subsectors were 51.3% and 48.7% respectively. 2.20 By far, poultry is the siibsector which contributed the most, with 19.5%, followed by beef and milk (10.0% and 10.4% respectively), beans (10.8%), maize (7.4%), and eggs adding another 5.4%. All fruits together contributed with almost 11%, although it is worth underscoring the increasing participation of the item Other Fruits, which includes avocados, pineapples, cashew (fruit), oranges, limes, papayas, mangoes, passion fruit, watermelons, melons, tangerines, and grape. Cotton, sugarcane and cassava reduced their participation, now representing 1.6%, 4.8%, and 5.2%, respectively. One should also observe that goats and sheep, activities which the World Bank mission was told has potential for growth, still remain less than 1.0% of the agricultural GDP, each. 2.21 In terms of agricultural exports, according to the 1995 figures, essentially there are only two products of agricultural origin which represent a share of significance in the State's total exports. These are cashew nuts (US$ 130 millions) and cera de carnauba (US$ 38.5 million). On the other hand, the next highest share comes from melons, which represents only US$ 224,000 (see Annex Table 43). This in itself is not a test of performance because maybe Ceara's main market could be the Brazilian domestic market. Export market diversification is an attractive goal partly because it could help in reducing the fluctuations in total export revenues. However, export diversification is more the outcome of a competitive economic environment rather than a trade policy objective per se. Table 2.3: Changes in the production structure, in percentages, Ceara. Share of Total Agric.GDP Share of Total Agric.GDP (1990+1991) (1996+1997) Agr. GDP Crop & LS Agr. GDP Crop & LS Cofton (Herbaceo) 0.9 1.3 0.2 0.2 Cotton (Arb6reo) 1.3 1.9 0.9 1.3 Rice 2.9 4.1 3.8 5.4 Banana 1.6 2.3 1.5 2.2 Coffee 0.7 1.0 0.5 0.8 Cashew (nut) 1.7 2.4 1.6 2.2 Sugar cane 4.4 6.2 3.1 4.4 Coconut 2.6 3.7 2.6 3.7 Bean 5.2 7.4 6.9 9.9 Cassava 3.9 5.6 3.3 4.8 Maize 3.0 4.3 4.7 6.8 Other Fruits 1.1 1.6 1.9 2.7 Other Products 2.1 2.9 2.0 2.8 Crops, total 31.4 44.6 33.0 47.3 Beef 3.5 5.0 6.4 9.2 Milk 9.4 13.4 6.7 9.6 Sheep 0.6 0.8 0.6 0.8 Goats 0.6 0.9 0.6 0.8 Pork 1.1 1.5 1.0 1.5 Poultry 9.5 13.5 12.6 18.0 Eggs 4.8 6.9 3.5 5.0 Pescado 9.4 13.4 5.4 7.8 Livestock, total 39.0 55.4 36.8 52.7 Crops and Livestock, total 70.4 100.0 69.9 100.0 Extrativa veg., Agroindustry 6.9 5.5 Agropecuaria, total 77.3 75.4 Services (autonomous + auxiliaries) 22.7 24.6 Agriculture Total 100.0 100.0 46 Fruits: Avocado, Pineapple, Cashew (fruit), Oranges, Lime, Papaya, Mango, Passion fruit, Watermelon, Melon, Tangerine, and Grape. Notes: (1) Cotton varieties: herbdceo (annual) and arb6reo (shrub). Tabulation: World Bank Mission. Source: IPLANCE. On The Evolution Of Farm Prices 2.22 In order to track the evolution of price incentives during these last years we examine the trend in real producer prices during the period 1990-97. Real producer farm prices were derived to capture the evolution of the purchasing power of farm prices; they were defined as the current farm price deflated by the Brazil's General Price Index (IGP- Dl). 2.23 Real farm prices were higher for most products during the 1990 - 1993/94 period, but this was followed by a significant reduction between 1994 and 1997 (Table 2.4). For example, between 1990 and 1994, the real price of beans fluctuated between R$ 50 and R$ 68 (per 60 kg), falling toR$ 41 to R$ 47 during 1995-97, a decline of 20%. For cashew nuts, prices fluctuated between R$ 0.82 and R$ 1.86 during 1990-93, subsequently fell to a range between R$ 0.42 and R$ 0.48 during 1995-97.52 A falling real price situation, in the range of 20 to 40% since 1994 applies also to rice, cotton arb6reo, sugar cane, and maize. Even for high value crops, such as fruits and horticultural products, real prices decreased over the years (see Annex Table 43). Table 2.4: Price Indexes for Major Crops and Livestock Products, Ceari. Price Index 1990/91 1993/94 1996/97 Cotton (herb6ceo) 100.0 101.6 107.4 Cotton (arb6reo) 100.0 99.6 72.8 Rice 100.0 87.2 70.8 Banana 100.0 112.2 81.9 Cashew (nut) 100.0 153.4 51.1 Sugar cane 100.0 106.5 70.6 Coconut 100.0 141.6 80.7 Bean 100.0 99.6 75.0 Cassava 100.0 148.2 87.0 Maize 100.0 106.9 70.9 Crops, total 100.0 115.1 75.6 Beef 100.0 104.3 77.0 Milk 100.0 83.0 75.5 Sheep 100.0 104.8 88.1 Goats 100.0 60.9 54.5 Pork 100.0 94.6 72.2 Eggs 100.0 100.0 61.3 Livestock, total 100.0 92.8 74.3 Tabulation: World Bank Mission. Source: EMATERCE (adjustment of inflation by FGV) 2.24 To sum up, the weighted real producer price index for crops increased 15% in 1993/94 compared to 1990/91, but the index was markedly 25% lower in 1996/97 than the 1990/91 level. Prices for livestock also declined throughout the period. They were 7% lower in 1993/94, and in 1996/97, they were 25% below the 1990/91 level.What explains this fall in real prices and what can be expected for the medium term should be pursued. For tradable products, which represent the majority of farm products, there are three 52 The drastic decline in cashew nuts prices is striking. One should pay attention to the average price in exports, US$4.59 per kg (see Annex Table 43). 47 possible factors, namely appreciation of the real exchange rate, and/or lower border prices, and/or lower levels of protection (price support/tariffs)."3 The appreciation of the real and perhaps the opening of the economy under Mercosurare probably part of the explanation for this outcome in Brazil. For non-tradables, the negative overall economic growth during 1985-95 is also a contributing factor. 2.25 The reduction in aggregate demand in Brazil (between 1985-95, per capita income decreased 0.8% annually), implies a contraction in consumer demand, and in particular for "non-tradable" products, such as beans, vegetables, and cassava. That would explain in part the decline in real prices. However, it is interesting to observe that according to Iplance, the annual growth rate of GDP per capita for the State of Ceara was 4.42%, between 1987 and 1997. A Trend of Increased Farm Fragmentation 2.26 The trend of increased farm fragmentation that has been observed since the 1970s continues. Using Census data, one observes that the average farm size (by size of operation) went down from 33.9 ha to 26.3 ha between 1985 and 1995/96 (Table2.5 and Annex Table 46). The share of farms with less than 10 ha increased from 49% in 1970, to 63.3% in 1985, and to 72.3% in 1995 (Table 2.6 and Figure 2.2). In absolute numbers, 245,000 farms have less than 10 ha in the State, out of a total of 340,000 farms, and more than one third of all farms have less than 2 ha (121,000 farms). 2.27 It is unlikely that these are all full-time farmers, and thus many of them may receive some non-farm income. What is their income situation has to be assessed based on household income data, which we examine later in the text. But from a farm production and productivity perspective, this large number of very small farms in the State poses a major challenge in terms of assisting them with an effective extension system. As it will be shown below, the share of farms with access to extension services in 1995/96 was less than 4%. 2.28 The share of small farms (farms of less than 10 ha) in total farm area increased but at a much lower rate, from 3.9% in 1970 to 6.2% in 1995 and 7.0% in 1995. If we focus on the smallest size farms, one observes that more than one third of all farms (35.7%) are less than 2 ha and 60.8% are less than 5 ha, with an average farm size in the less than 10 ha category of 2.6 ha, which is hardly viable for full-time farmers in a semi-arid region. Table 2.5: Number and Area of Farms by Farm Size, 1995196, Ceara. Area Number Avg. farm Farm size (ha) '000 ha '000 size ha <10 627 245.0 2.6 < 2 376 206.0 1.8 < 5 117 121.0 1.0 10-100 2,438 76.0 32.1 100 - 1000 4,123 17.0 242.5 >1000 1,730 0.8 2,162.5 53 A decomposition approach to measure the relative weight of these three factors is developed in A. Valdes (1996), "A Surveillance of Agricultural Price and Trade Policy in Latin America during Major Policy Reforms" World Bank Discussion paper # 349. 48 Total 8,918 338.8 26.3 Source: IBGE - CensoAgropecu6tio 1995-1996. Table 2.6: Evolution of Farm Distribution (Number and Area) by Size, Ceara. Number of farms Area Farm size (ha) 1970 1985 1995 1970 1985 1995 <10 49.0 63.3 72.3 3.9 6.2 7.0 < 2 23.1 20.7 49.4 0.2 0.7 1.3 < 5 32.4 47.8 60.8 1.6 3.1 4.2 10- 100 41.5 30.0 22.5 27.5 28.4 27.7 100 - 1000 9.0 6.4 5.0 44.3 45.4 46.0 1000- 10 000 0.5 0.3 0.2 20,7 19.0 17.5 >10,000 0.0 0.0 0.0 3.6 2.0 1.8 Total 100.0 100.0 100.0 100.0 101.0 100.0 Tabulation: World Bank Mission. Note: Categories <2 and <5 cannot be added, because they are also part of the category immediately above. Source: IBGE - Censo AgropecuArio 1995-1996. 49 Figure 2.2: Comparison of farm distribution (number) by farm size, in Ceara. | - 1000 -lOOOOha 1970 i 0.5% >10,000 ha l r- 0.0% El<10 100 - 1000 ha . @1 10 - 100 49.0% El1 100 -1000 'E 1000 - 10 L> IO,000 0.2 >10,000 ha . . . . . . . . . . ..... . . < 22:5 7:..:%:: : 100-10003 ' .''.',.''. ."."' ,'' . . 3o, . . . . . . . . . . 11 00-lO ha / ......... . . . .......34% {4150/~~ . . . _,_ . . .v 0~~~~~~~~~~~~~~~~~~~25 - 0h j1000 -10 000 ha| 1 0.2% >I >10000 ha 100 - 1000 ha \/ 00 5.0% 93SVE<10 |10 - lOO ha <1 . .........p......1000 All farms Cotton 0.6 1.0 1.5 0.6 0.9 Rice 11.3 6.5 4.4 0.8 7.8 Banana 10.8 17.6 13.6 3.0 13.0 Cashew (nut) 4.3 10.4 14.1 39.3 10.3 Sugar cane 5.4 10.7 17.2 15.8 9.9 Coconut 3.6 3.8 8.4 19.7 5.6 52 Bean 23.6 17.1 12.8 4.4 18.3 Cassava 7.8 6.5 5.6 5.2 6.8 Maize 24.9 19.4 20.0 10.8 21.3 Tomatoes 7.7 7.0 2.5 0.6 6.1 Crops, total 100.0 100.0 100.0 100.0 100.0 Beef 16.2 17.7 22.6 37.1 20.1 Milk 26.3 35.7 38.0 47.7 34.8 Sheep 1.6 1.9 2.1 2.0 1.9 Goats 1.4 0.9 0.9 1.1 1.0 Pork 9.1 4.2 2.3 1.9 4.7 Poultry 30.9 25.1 16.0 9.9 22.7 Eggs 14.4 14.5 18.1 0.3 14.8 Livestock, total 100.0 100.0 100.0 100.0 100.0 Tabulation: World Bank Mission. Source: IBGE- Censo Agropecunrio 1995-1996. Yields, Technical Assistance, And Adoption Of Improved Technologies Yields 2.36 In general, crop yields for major products in Ceara are relatively low, particularly those of food/subsistence crops cultivated in non-irrigated areas. In 1995- 1997, yields for maize averaged about 0.75 t/ha, for beans 0.35 t/ha, and for Cassava 6.4 t/ha (Table 2.9 and Annex Table 51 for other crops). Cotton arb6reo produced between 0.09-0.19 tlha, while sugarcane yielded about 49 t/ha. The strong yield increase observed in rice, beans and maize during the 1990s seems to be from cultivation of these crops under irrigation (see Table 2.14, although unfortunately we do not have time series data showing the evolution of the shares). Increment in cotton yields were result of the successful introduction of new varieties. 2.37 Low yields may reflect poor soil quality, poor seeds, and low utilization of irrigation, fertilizer, and/or crop protection. High production risks, particularly in non- irrigated areas, and limited access to credit are likely to keep farmers from using more intensive production technologies that could lead to higher yields. 2.38 According to the Censo Agropecuario data, average yields seem to have increased since 1985, possibly as a result of the general decline in cropping area. Marginal, low-productivity land may have been taken out of production. 2.39 Interestingly, with the exception of cotton, farms of different size have either very similar yields for major crops. In fact the yields in farms above 10 ha are slightly lower than those in farms smaller than 10 ha (see Annex Table 52). 2.40 For instance, yields for beans vary only from 0.31 - 0.34 t/ha by farm size category. Similarly low variations can be observed for maize (0.74 - 0.81t/ha), cassava (6.00 - 6.85 t/ha), or bananas (740 - 810 cachos/ha). For cashew, sugarcane, coconuts, and rice average yields are between 20-45% lower on larger farms. Only cotton is grown more intensively on larger farms than on smaller ones, with yields between 0.83 - 1.14 t/ha for farms above 100 ha, vs. 0.62-0.64 t/ha on the other farms. Extension 53 2.41 According to the 1995/96 Agricultural Census, a very low proportion of farmers participate in extension programs. Only 3.8% of all farms currently obtained any form of technical assistance (public or private) (Table 2.10). One should observe the uneven distribution of extension services and consequent adoption of improved agricultural practices by meso-regions. Fortaleza, Jaguaribe and Centro-sul are the regions with less number of farm units, but where extension services seem more efficient. Comparing to other regions, a relative high percentage of farms use irrigation techniques, mineral fertilization and crop protection. The problem of minifundios and the effectiveness of extension services is well underscored with these figures. On the other hand, soil conservation practices are more widely adopted by farms in the Centro-sul, Sul and Sert6es. Technical assistance (TA) is markedly higher in areas with more irrigation. Table 2.9: Yields of Selected Crops, in kglha, and Percent Changes, in Ceari. 1985 1985 1986 1994 1995 1995/96 1997 Change Change Change (Censo) (PAM) (PAM) (PAM) (PAM) (Censo) (LSPA) (%) (%) (%) (Censo) (PAM) (LSPA) Cotton (herb.) 327 374 195 511 680 687 896 110 109 51 Cotton (arb.) 194 146 74 133 175 87 117 -55 40 -24 Rice 1,399 2,407 2,489 2,432 2,679 2,145 2,758 53 4 8 Banana(1) 752 1,436 325 814 807 778 721 3 -31 -11 Cashew (nut) 404 328 120 210 243 88 109 -78 1 -52 Sugar cane 34,398 42,055 42,216 45,337 46,925 49,381 47,695 44 9 3 Coconut (2) 5,336 5,016 3,567 3,569 3,550 3,548 3,312 -34 -17 -7 Bean 192 207 228 363 375 320 290 67 69 -21 Cassava 3,534 8,004 8,927 7,869 7,740 6,415 7,630 82 -8 -2 Maize 500 374 537 690 730 790 571 58 56 -20 Pineapple (2) .... 4,252 4,593 6,556 7,444 .... 8,333 .... 58 19 Papaya (2) .... 20,140 18,981 23,418 20,735 .... .... 13 .... Mango (2) .... 54,450 50,717 48,211 42,496 .... .... -14 Passion fruit (2) .... .... .... 118,377 118,129 .... .... 0 .... Watermelon (2) .... 261 244 1,181 1,503 .... .... 431 .... Melon (2) .... .... .... 17,775 17,370 .... .... 111 .... Grape .... 2,250 2,250 9,275 24,583 .... .... 652 .... Tabulation: World Bank Mission. Note: (1) in cachos/ha, (2) in fruits/ha. Sources: IBGE - Censo Agropecu4irio 1995-1996; IPAM - Pesquisa Agricola Municipal; LSPA - Levantamento Sistematico da Produgco Agricola. 2.42 Larger farms have better access to TA, particularly from private and other non-government sources, and are more likely to request it for livestock production (Table 2.11). Between 6% and 33% of farms above 10 ha report contact with TA. Among the smallest farmers, only 2.4 percent receive any TA. Most technical assistance is provided for crop production (72%), compared with TA for livestock (28%). Table 2.10: Percentage of farms with improved agricultural practices or service access, by meso-region, in Ceara. Irrigation Technical Mineral fertilizer Crop protection Soil Number of assistance conservation farms Noroeste 6.0 2.0 14.7 43.0 7.9 83,305 Norte 6.6 2.9 14.8 36.2 16.0 56,883 Fortaleza 12.7 5.3 28.7 40.9 3.6 10,293 Jaguaribe 21.9 8.4 20.2 77.5 9.8 31,861 Centro-sul 17.3 6.2 19.1 70.7 38.8 34,492 Sul 6.2 3.5 5.6 49.8 26.3 48,880 Sertoes 4.1 3.2 4.1 67.4 47.1 74,488 Total 8.5 3.8 12.5 54.2 23.7 340,202 Source: IBGE - CensoAgropecu6rio 1995/96 54 Table 2.11: Technical Assistance (percentage), by farm size, in Ceari, 1995-1996. Farm size Farms with Source of TA (for farms with TA) TA for Crop (ha) TA Public Private Other vs. LS <10 2.4 44.5 29.9 25.7 78.4 < 5 2.0 49.1 30.6 19.7 76.9 < 2 1.3 58.3 31.8 8.3 72.3 10 - 100 6.0 47.9 37.8 15.5 70.9 100- 1000 11.2 29.6 55.3 17.6 54.7 > 1000 33.4 19.2 67.9 15.7 52.6 Total 3.8 42.9 37.4 20.6 71 6 Source: IBGE - Censo AgropecuAno 1995/96 Fertilizer Use and Pest Control 2.43 The utilization of chemical and organic fertilizers (i.e. livestock manure) in Ceara's crop production is amazingly low, even on larger farms. Only 6.7% of all farms apply any chemical and 9.0% any organic fertilizer (Table 2.12). This explains the relatively low yields in major crops. Although application rates are somewhat higher in larger farms, this data suggests a situation of low profitability in intensifying production, particularly considering the high real interest rates in Brazil and the decline in real producer prices. Another explanation would be that many soils may be sufficiently fertile- especially when crop rotation includes legumes (beans)--but that the critical missing factor is water (or the high risk of droughts) (Haddad et al., op. cit., 1994).As a matter of fact, mineral fertilizer and crop protection use are highest in meso-regions with more irrigation, such as Jaguaribe, Centro-sul, and Fortaleza (Table 2.10). 2.44 Chemical control of crop pests and livestock diseases is significantly higher than soil fertilization. There is, however, a marked contrast in the use of veterinary medicine in the small and larger farms, 17% in farms < 10 havs. 57-88% in farms above 10 ha. This fact suggests that extension is not necessarily the determinant factor in explaining low average yields, as even for smaller farms, the proportion using pest/disease control is substantially greater than their use of fertilizers. Thus, are the returns to higher fertilizer application relatively low? If so, to what extent this reflects a fairly "flat" physical response function to fertilizers (due to existing varieties used and lack of irrigation) and/or real prices of output vis-a-vis fertilizer costs? This should be explored in more detail further. Table 2.12: Fertilizer Use and Pest Control, in Ceari, 1995-1996. Farm size Farm with fertilizer applications Farms w. pest/disease control Ha Chemical Organic Livestock Crops <10 6.4 7.4 17.0 37.3 < 5 5.8 6.6 13.9 36.0 < 2 4.8 5.5 9.6 32.5 10-100 7.2 11.7 56.7 46.3 100- 1000 7.1 18.2 82.1 48.7 > 1 000 13.8 35.0 87.7 50.1 Total 6.7 9.0 29.3 39.3 Tabulation: World Bank Mission. Source: IBGE - Censo Agropecudrio 1995196 Conclusion 2.45 It is paradoxical that although crop area declined drastically, prices also declined, agricultural GDP fell less than expected. What explains this apparent 55 discrepancy is not clear yet, as high value crops (e.g. fruits) have not increased a lot in their share to the Agricultural GDP (see Table 2.3). So, even a considerable increase in the yields of these high value crops would not be sufficient to explain a less dramatic fall for the agricultural GDP. We should add that in Haddad et al. (1994) they made references about possible inconsistency in the state agricultural GDP estimates for the period 1991-1993. In fact, as shown in Annex Table 41, the IBGE estimates for 1997, using the LSPA, are considerably higher than the agricultural'Census estimates for 1995-1996, although lower than the PAM time series. If these estimates based on the census were used for the GDP calculation, one would anticipate that the current available agricultural GDP figures are overestimated, and thus the fall in ag. GDP could be greater than it is shown by the figures of IPLANCE. Water Resource Management and Irrigation Development 2.46 Water management ana irrigation development figures prominently in the rural development strategy of Ceara. As stated in the "Plano Indicativo de Desenvolvimento Rural do Ceara 1995-98" (SEARA, 1995, op.cit.), the objectives of the irrigation strategy include: (i) improving the efficiency of the Ceara's integrated water resource management system and, (ii) expanding the irrigated area. Since irrigation increases farming intensity, in contributing to agricultural growth irrigation in most cases it also greatly increases labor demand. Rightly so, in our judgment, the Secretaria de Recursos Hidricos has recently given considerable emphasis to the development of an appropriate institutional framework encouraging the involvement of water users associations, the development of the appropriate legal framework, moving towards the implementation of a water pricing policy more consistent with cost recovery and pricing of water that reflects its opportunity cost in alternative uses. 2.47 In collaboration with the State government, the World Bank has had a long term involvement in the developmeit of water resources in the State. More recently it has submitted a comprehensive plan of action for additional lending operations in this area with a specific initiatives and proposals regarding (i) demand management (water policy reforms and institutional development); (ii) construction of new water storage reservoirs and associated distribution systems; (iii) integration of river basins to interconnect supply reservoirs; (iv) rehabilitation of existing water supply infrastructure and (v) watershed management (World Bank, 1998).54 This and other documents have examined most of the key technical and economic issues regarding water resource management, and thus this topic is not covered in this report. In this SEM we focus selectively only on a few issues which seems to deserve special attention. 2.48 Irrigation, mainly in the form of flooding (inundagao), use of sprinklers (aspersao), or infiltration (infiltraqjo,}, is particularly important in Jaguaribe, Centro-sul, and Fortaleza: in Jaguaribe, 21.9% of farmers have some sort of irrigation, 17.3% in Centro-Sul, and 12.7% in Fortaleza. In all other meso-regions less than 7% of farms have any irrigated area (4.1% - 6.6%) (Table 2.10). 54 See, Larry d. Simpson, in "Ceara Integrated Water Resources Management Project", an Office Memorandum of the World Bank, in July 1, 1998. 56 2.49 According to the Censo, in 1995/96 about 8.5% of farms used some form of irrigation. 23.8% of irrigated land was cultivated on farms of <10 ha, 30.1% on farms between 10 and 100 ha, and the rest on farms above 100 ha(Table 2.13). 58% of farms with at least some form of irrigation fall into the category of small farms with <10 ha. Table 2.13: Irrigation, percentage figures by farm size, in Ceara, 1995-1996. Farms with Irrigated area of all Irrigation area by farm Farm size (ha) irrigation farm land size <10 6.9 4.1 23.8 < 5 6.1 3.8 13.2 < 2 5.1 3.0 3.3 10-100 11.4 1.3 30.1 100-1000 18.8 0.8 30.4 > 10,000 37.4 1.0 13.6 Total 85.7 14.0 97.9 Source: IBGE - Censo AgropecuArio 1995/96 2.50 According to information provided by the Secretaria de Recursos Hidricos, in 1994, Ceara had about 51,700 ha under irrigation. This figure is surprisingly less than 50% of the total area irrigated estimated by the census.55 The goal of theSecretaria is to reach a total of 99,100 ha by the end of 1999 (SEARA, 1995, op. cit.). Investment projects under construction will incorporate about 25,000 ha under irrigation, so a total of 75,000 ha should be in operation in the near future. Including small scale irrigation works, the mission was informed that the estimated maximum area under irrigation in the State was about 300,000, although 150,000 ha seems a more realistic figure, according to the opinion of a specialist consultant. 2.51 Based on the 1995/96 agricultural census data, we computed a total of 63,287 ha under irrigation (Table 2.14). This excludes, however, other horticultural products, mostly vegetables and herbs, and more permanent fruit crops, such as mango, passion fruit, papaya, and lemons, which are likely to be intense in irrigation techniques. The Censo does not provide detailed area figures or information on irrigation for these crops, so one should see this figure as an underestimated value. Table 2.14: Harvested irrigated area, by major crops, in Ceara, in 1995-1996. Harvested Proportion Irrigated by Crop in Yields (1 irrigated Total (t/ha) Crops area Harvested Harvested Irrig. No Irrig. (ha) irrig. (%) area (%) Cotton 455 0.7 5.5 1.5 0.6 Rice 11,667 18.4 22.4 4.2 1.4 Banana 5,466 8.6 15.3 0.9 0.7 Cashew(2) 1,261 2.0 0.3 0.4 0.3 Sugarcane 10,813 17.1 51.9 67.7 45.1 Coconut 5,435 8.6 26.3 7.7 3.1 Coffee 251 0.4 3.8 0.5 0.4 Beans 15,470 24.4 4.1 0.8 0.3 Mandioca 456 0.7 1.1 6.6 6.2 Maize 9,422 14.9 2.0 1.1 0.8 Oranges 425 0.7 28.0 41.8 35.5 Tomatoes 2,166 3.4 89.7 30.7 24.3 Total main crops 63,287 100.0 55 See, Censo Agropecuario 1995-1996, for the State of Ceara, Table 8. In addition, accordingly to the methodological, the census did not seem to consider simple irrigation methods. 57 Tabulation: World Bank Mission. (1) Banana: '000 cachos/ha; Cashew, Coconut, Orange: fruits ('000)/ha (2) Figures for area consider cashew (nuts) and cashew (fruits). Source: IBGE- Censo Agropecudno 1995-1996. 2.52 As would be expected, yields on irrigated crops are in general significantly higher than those on non-irrigated land, particularly when mineral fertilizers and crop protection are used. Higher yields in irrigation are particularly apparent for rice (4.18 vs. 1.39 t/ha), beans (0.75 vs. 0.29 tVha), coconuts (7.7 vs. 3.1). In other crops intensive irrigation doesn't increase yields by more than 50%. Surprisingly, average yields in irrigated maize are just 1.1 t/ha, which is very low by international standards (and Brazilian standards). 2.53 The high share of the irrigated area cultivated in food crops has important economic implications. According to the information gathered by the World Bank mission in the field, the economic returns to food crops such as bean, maize and rice under irrigation in the large scale irrigation areas are low, and are likely to remain low. More likely, large-scale irrigation schemes and water resources projects (in the Jaguaribe Basin for example) require for their economic viability the production of high value products, in particular fruits. 2.54 The implications of this finding on the use of irrigated land deserves further attention. The fact that such a high proportion of the area is in the relatively lower value crops, suggests a significant misallocation of water resources. Furthermore, (a) it suggest that the economic returns to irrigation investments are probably much lower than actual anticipated in ex-ante evaluations; (b) no rigorous ex-post economic evaluation studies were available to the Bank's mission. Such evaluations of the major irrigation schemes would seem a priority, and certainly called for before deciding on the expansion of the irrigated area; (c) inadequate pricing for water stands as a strong hypothesis to explain why such a high proportion of irrigated area remains in relatively low value crops. Higher prices for water to reflect its opportunity costs would encourage a greater area into higher value products; and (d) the present policy of allocating half the irrigated area to small farmers in large scale irrigation schemes should be reassessed. Fruit production under irrigation (partly for exports), seems to be an economically promising use of irrigated land. However, these products are usually subject to high price variability, are also a generally capital intensive, often require a constant redirection towards new products and different varieties, and fairly sophisticated marketing. Small, traditional farmers are typically not in a good position to adopt the required technologies and management approaches for such products. Rural Poverty in Ceara 58 Household Income Analysis (Northeast) 2.55 The analysis suggested below is based on a LSMS household survey (PPV - Pesquisa sobre Padr6es de Vida) taken in 1997 that covers 521 households in the Northeast of Brazil, 15 of which were located in Ceara. A socioeconomic profile of income and demographic information for the rural households in the Northeast is presented in Table 2.15. 2.56 As expected, there is considerable heterogeneity with respect to income levels and household characteristics within the rural economy in Northeast. One would want to distinguish between small owner-operated farms, tenants, share croppers and squatters, landless farm workers and people mainly employed in rural non-farm activities, because a poverty alleviation strategy for dealing with each of these groups could be quite different. However, given the limitation of the household survey data available, our analysis was restricted to two main groups, namely land-owning farms and a second category which includes tenants, sharecroppers, squatters, landless farm workers, and rural non-farm workers. The two categories of owner-operated farms (LO) and non-land owners (Non-LO) were also analyzed by farm size and income levels. 2.57 In this analysis, household income figures reported include (i) cash income from farming, (ii) (imputed) income from food production consumed at the household level, (iii) cash transfers and pensions, (iv) remittances, (v) non-farm business income, (vi) wages and benefits, and (vii) imputed rent for housing. Gross farm income was adjusted to account for production expenses in farming (by P. Lanjouw) and thus the income figures reported in Table 2.15 represent net household income from all income sources. The comparable data on household expenditures (as a proxy for income) was not used in the analysis because it was deemed less reliable. Income figures varied widely according to which of the two variables is chosen. The median per capita income for all sample households according to the income figures is R$ 178, versus R$ 110 according to the expenditure figures. Small farm land-owners are generally poorer than non-land-owners 2.58 Approximately 42% of the HH in the sample are land-owners, which means they are operating their own farms. The remaining 56% are either cultivate land as tenants, sharecroppers, or squatters, or they are landless. The data inTable 2.15, points out considerable differences between LO and Non-LO households with respect to household characteristics and level and sources of income. First, the median income of LO households - both in terms of total and per capita income is about 30% lower than that of Non-LO; second, LO obtain about 49% of their total household income from agriculture (including food produced and consumed at the farm level), compared to 37% for Non-LO households; and (3) LO households are headed by older individuals, averaging about 53 years for LO vs. 42 years for Non- LO. 2.59 The pattern that emerges from this comparison suggests that on average the category of households that own land are generally poorer than non-land owners, probably because they are less mobile in part because they are older. Unfortunately we do not have disagregated data in order to compare the household characteristics of the 59 various groups (landless, sharecroppers, small owner-operated farms), such as age, schooling, family size, etc. Table 2.15: Socioeconomic Profile of Rural Households in Northeastern Brazil. iAl HH LO Non-LO Income quintiles Low 2 3 4 high HH- size 4.6 4.8 4.4 5.9 4.9 4.3 3.8 3.1 Female head of HH % 16.1 12.3 18.9 8.2 13.1 8.7 23.3 31.6 Age of HH-head yrs 46.5 52.6 42 46.4 44.6 45.4 49 47.4 Homes with electricity % 53.3 47.2 57.8 40.4 51.5 62 60.5 60.2 Real HH-income (mean) R$ 1252 931 1487 330 606 896 1392 5723 Real HH-income (median) R$ 710 572 811 292 561 854 1154 2724 Real per-cap. income (mean) R$ 356 267 421 55 123 211 361 2290 Real per-cap. income (median) R$ 178 143 204 56 122 207 357 919 Per-cap. HH-expenditures (median) R$ 110 101 116 99 96 95 122 169 HH below high poverty line % 55.6 63.6 49.8 100 100 48.9 0 0 HH below indigence line % 17.1 24.6 11.6 61 0 0 0 0 No. of HH # 521 220 301 146 99 92 86 98 Real per-cap. income (median) R$ 178 143 204 56 122 207 357 919 Average HH income shares Agricultural income % 27 30 24 16 23 29 32 37 Home food production % 16 19 13 18 17 18 15 8 Wages and benefits, incl. agr. labor % 29 23 34 26 31 28 31 32 Subsidies and pensions % 13 15 11 20 14 11 8 6 Non-farm business income % 2 1 3 -1 2 2 4 7 Remittances % 3 2 3 3 3 3 1 2 Housing (imputed) % 8 4 11 18 9 8 7 6 Other, incl. Rental income % 2 1 2 1 1 1 2 3 Note: Per-capita income was calculated using the total number of persons per HH, not adjusted for adult equivalent. Source: Pesquisa sobre Padrao de Vida, 1997. 2.60 The incidence of poverty is particularly high among farmers with less than 5 ha (66.4%), but it is also high among farmers in units between 5 and 10 ha (58.8%) (see Annex Table 53). It should also be noted that for the average LO household with less than 5 ha, non-farm income already represents about 42.5% of total income (compared to 33% for those between 5 and 13 ha). These households already depend for a high proportion of their income on non-farm activities. It is worth mentioning that remittances represent only about 2% of the household income, while subsidies and pensions represent about 18% for the less than 2 ha farms, and 1 1% for the 5-10 ha category. Differences among the group of non-LO 2.61 The non-land owners group is very heterogeneous with respect to income levels and sources. Households in the medium income category (categories defined in terms of mean income) earn about lhree times as much as the average household in the lowest income category (lowest tercile). And those in the highest income earn almost nine times more than the lowest tercile. 2.62 Interestingly, even for' the non-land owners agriculture contributes significantly to overall income, particularly for the highest income group of Non-LO households: 39% of their total income comes from agriculture, compared to 31 and 42 % for the lowest and medium categories (with a group average of 37%). For the lowest and medium income categories, home food production is proportionately more important, covering about 15% of their total income, versus 7% in the high income category. The non-LO group apparently contains a high proportion of tenants and sharecroppers with relatively high income. 60 2.63 Many of these tenants and sharecroppers are clustered in the medium income group. On average, annual income per capita in this group is R$ 484 (weighted average for the two groups), compared to R$ 143 for the group of all land-owners. Differences by Income Quintiles 2.64 Non-farm incomes, particularly income from wages and public transfer payments, are much more important in low-income than high-income HH's. For the two lowest income quintiles, they represent on average about 64.2% of all income (weighted), compared to 54.6% in the two highest income quintiles. Most farm income in low income households is generated from home food production, i.e. > 50%, compared to a much lower proportion of about 25% in high income households. 2.65 With regard to demographic differences, the most interesting features are that wealthier HH's are significantly smaller and more likely to be female-headed than poorer HH's. The average size of households declines continuously from 5.9 members in the poorest 20 percent to 3.1 members in the best-off 20 percent of households.At the same time, the proportion of women heading rural households increases significantly from 8.2% in the poorest, to 31.6% in the best-off HH's. Conclusions 2.66 There is no question that absolute poverty and indigence levels in the rural Northeast, including Ceara, are extremely high. The LSMS survey data suggests that 55.6% of rural households in the sample fall under the 'high-poverty line', which means they have per capita incomes of less than R$ 204/year (or US$ 188.9 compared to the average per capita GNP of US$ 3,640/year for all of Brazil, considering an exchange rate for 1996 of R$1.08/US$1.00). 17.1% of households fall under the indigence line of less than R$ 65/year, which means they do not even have enough income to acquire a sufficient food basket to maintain a healthy and active life, without considering any other expenses.' 2.67 Figures from other sources indicate a similar or even higher incidence of poverty: in 1993, IPEA produced a 'hunger map' (O Mapa da Fome) with figures of rural poverty in Ceara of 66%, compared to 56% in the rural Northeast, and 43% in rural Brazil as a whole. Data from PNAD suggests that more than 99% of all rural households fall under the high-poverty line, and 78.4% under the indigence line. Poverty incidence (indigence) is slightly lower among the rural non-agricultural than the agricultural population (69.3% vs. 81.5%). 2.68 These findings suggest that in the Northeast of Brazil: (a) the bulk of the poorest of the poor in rural areas are not, perhaps, to be found among the landless workers; 56Adjusted for purchasing power (PPP), the high poverty line would be about R$ 303/capita/year, or R$ 0.83 /capita/day (equivalent to US$0.77/day), while the indigence line would mean incomes of less than R$0.25/capita/day. 61 (b) the poorest tend to be the small farmer in the minifOndio, with less labor mobility and less access to public services such as electricity (perhaps education and health); (c) considering the extremely high levels of absolute poverty found, the small size of a high proportion of the farms, and the relatively low agricultural growth potential in the non-irrigated areas, a substantial reduction of labor in agriculture seems inevitable; (d) in the long run, rural income will be largely determined by the evolution of real wages in the region. Higher level of skills, through training and education, would allow them to compete for higher paying jobs. The Main Findings and Policy Implications Agriculture's Performance - sharp decline in growth 2.69 A sharp desaceleration of the State's agricultural economy has taken place since the late 1980s, both in terms of agricultural GDP growth rate, crop area and cattle inventories. The annual rate of growth in agricultural GDP in Ceara has declined dramatically, from 8% in the 1981-86 period to about 1 to 1.3% p.a. between 1987 and 1997, with a falling share in the State's economy, now at approximately 5.7%. In spite of this very low growth, sectoral employment remained high at around 40% of the workforce, which suggests a widening of the income gap between agricultural and non- agricultural workers. 2.70 The sharp decline in total farmed area between 1985 and 1995/96 is striking. According to the Agricultural Census figures for Ceara, between 1985 and 1995/96 the area under crops (annual and permanent) fell by 42.4%, while total farmed area fell by 18.6%. One observes a drastic reduction in cotton (from 757,000 has to 17,000 has), beans (from 458,000 to 373,000 has), maize, and others. This exception is cashew which increased from 163,000 to 280,000 has and some increase in coconut and banana. 2.71 Except for poultry, the picture for livestock shows a less pronounces but still very significant declining trend in stock numbers. The stock of cattle, goats and sheep fell by 3.8%, 19.4% and 1.8%, respectively. Pork inventories dropped 15.9%. Poultry is the exception, with an increase of 16.7%. 2.72 There is no single factor underlying this decline, and although the dramatic decline in the cotton sector is perhaps the major underlying factor, our analysis also suggests that, while less dramatic, the decline affected a large segment of the sector. The collapse of the cotton sector is attributed to the impactof the cotton weevil, a fall in world prices, and the effect of changes in the labor code. So far the region has not been able to resolve the effect of the cotton weevil on the cottonarb6reo, grown in the semi- arid regions. 62 2.73 Other contributing factors to this decline, according to this analysis, are the falling real producer prices for most farm products since 1993-94, and the falling aggregate demand due to Brazil's negative per capita growth rate during 1985-95. 2.74 Real farm producer prices for crops increased 15% in 1993/94 compared to 1990/91, but the index was 25% lower in 1996/97 than in 1990/91. Real prices for livestock products declined throughout the period. What explains this fall in real prices should be pursued further. For tradable products, which represent the majority of farm products, there are three possible factors, namely the appreciation of the exchange rate, lower border prices, and/or lower levels of protection (probably related to the opening of the economy under Mercosur). For home goods, the negative overall economic growth during 1985-95 is also a major contributing factor. Land productivity 2.75 In general, crop yields for major products in Ceara are relatively low, particularly those of food/subsistence crops cultivated in non-irrigated areas. Also, and related to the above, the utilization of fertilizer (chemical and organic) is amazingly low, even on larger farms. Only 6.7% of all farms apply any chemical, and 9% any organic fertilizer; application rates are somewhat higher in larger farms. The analysis suggests a situation of low profitability in intensifying production. Partly this is probably the effect of the decline in real producer farm prices and the high-real interest rates prevailing in Brazil. But, also, this low fertilizer use reflects could be linked to water constraints. Soil fertility is not particularly low (essentially when the crop rotation includes legumes such as beans), but shortage of water and the high risk of droughts would make higher fertilizer use unprofitable. As a matter of fact, mineral fertilizer and crop protection use are highest in meso-regions with more irrigation, such as Jaguaribe, Centro-sul, and Fortaleza. A Trend of Increased Farm Fragmentation 2.76 A trend of increased farm fragmentation which has been observed since the 1970s continues. The average farm size (by size of operation, not necessarily ownership) went down from 34 has to 26 has between 1985 and 1996/96, and the share of farms with less than 10 has increased from 49% in 1970 to 72% in 1995/96. In absolute numbers, 245,000 farms have less than 10 has in the State, out of a total of 340,000 units, and more than one third of all farms have less than 2 has. (121,000 farms). 2.77 Not all of these farms are operated by full time farmers, and thus they receive some non-farm income. However, as it is discussed below, the evidence from the household income analysis indicate that absolute poverty and indigence levels are extremely high in the Northeast, including Ceara. 2.78 From a farm income perspective, the existence of such a large number of very small farms in the State poses a major budget, administrative, and technical challenge for the government, in terms of the additional resources and well trained personnel that would be required to assist them as farmers, with extension, training, and 63 credit. According to the Agricultural census data, the share of farms with access to extension services in 1995/96 was extremely low, at around 4%. 2.79 As more farms subdivided, one observes a trend from owner-operated to tenants and ocupantes. These two groups increased their share from 34.5% of all farms in 1970 to approximately 50% in 1995/96. Overall, one would expect that this high share of ocupantes and tenants would result in lower farm productivity levels, relative to titled and properly registered farm units, on the premise that tenure insecurity (i) reduces the farmers demand for investment in assets attached to the land (small scale irrigation, soil conservation, orchards, etc.), (ii) reduces the supply of credit due to lack of collateral, and (iii) inhibits the entry of more productive farmers and the exit of the less productive. Rural Labor - Mostly Self-Employed 2.80 Between 1985 and 1995/96 the total number of rural laborers in Ceara - including non-paid family members, permanent and temporary hired labor, and sharecroppers - went down slightly, from 1.3 to 1.2 million. The bulk of rural labor force in agriculture is self-employed, 80% work on their own farms, 3,9% work as permanent workers, and 13,6% are temporary workers. Water resource Management and Irrigation Development 2.81 Water management and irrigation development figures prominently in the rural development strategy of Ceara. The objectives are (i) improving efficiency of the Ceara integrated water resource management system, and (ii) expanding the irrigated area. 2.82 Since irrigation increases farming intensity, in contributing to agricultural growth irrigation in most cases it also increases labor demand. 2.83 According to the census, in 1995/96 approximately 8.5% of farms used some form of irrigation, and 23.8% of the irrigated land was cultivated on farms of less than 10 has, 30.1% on farms between 10 and 100 has, and the rest on farms above 100 has. As would be expect, land productivity on irrigated areas is significantly higher than on non- irrigated land. Higher yields in irrigation are particularly apparent for rice (4.18 vs. 1.39 ton/ha) beans, coconuts, although not so for maize. 2.84 According to Secretaria de Recursos Hidricos, in 1994 Ceara had about 51,700 has under irrigation. The goal of the Secretaria is to reach a total of approximately 100,000 has by the end of 1999. Investment projects under construction will incorporate about 25,000 has under irrigation, so as to reach a total of 75,000 has. However, there are some discrepancies among different sources about the area under irrigation. Based on the 1995/96 Agricultural Census data we compute a total of 62,000 has under irrigation in well identified crops, plus bananas and tomatoes. This excludes other horticultural products and more permanent fruit crops such as mango, papaya or lemons. The Censo does not provide detailed area figures on irrigation for these crops. The total area in these higher value products would be about 18,000 ha. The Censo reports a total irrigated area of 109,000 ha. 64 2.85 The high share of the irrigated area cultivated in food crops and the low share on high value crops is surprising. Approximately 60% of the irrigated area is in beans, rice and sugar (24.4%, 18.6% and 17.0%, respectively), while less than 5% of the area is in higher value products such as fruits, tomatoes, and cotton (long fiber). 2.86 Anecdotal evidence gathered by the World Bank mission in the field in July 1998 suggests that the (private) economic returns to food crops such as beans, maize and rice under irrigation in the large scale irrigation areas are low, and are likely to stay low. More likely, to be economically viable large-scale irrigation schemes (such as the Jaguaribe Basin) require the production of high value products, in particular tropical fruits, flowers, and some vegetables. 2.87 What explains that such a low share of the irrigated area is utilized in high value crops deserves special attention. It could imply a substantial misallocation of water resources. Furthermore, it could imply that: (a) the actual economic returns to investment is large scale irrigation schemes is probably much lower than anticipated by ex-ante evaluations. Frequently, according to World Bank experience, economic evaluations in most countries have suffered from the so-called "optimism gap" (overstating benefits and understating costs), suggesting a bias towards predicting unrealistically high rates of return;57 (b) rigorous ex-post economic evaluations of irrigation schemes in the State are needed. No rigorous evaluation was available to the World Bank mission; (c) inadequate pricing for water stands as a possible strong underlying factor explaining the extensive use of water in lower value crops. Water prices to reflect its opportunity cost encourages a greater area into higher value uses;58 (d) the current policy of allocating half of the irrigated area to small farmers should be reassessed. High value products such as fruit, flowers and other products under irrigation (partly for exports) seems to be economically promising. However, these are usually capital intensive and subject to high price variability, often requiring constant adjustments in production and fairly sophisticated marketing. Small, traditional farmers are typically not in a good position to adopt the required technologies and marketing approaches, and face a high price risk on capital intensive activities. A proportion of the small farmers will developed sort of in the back of larger commercial farms, as seasonal workers and incorporating some of their technical and marketing technology in their own farms. But this is unlikely to apply to a high share of them. 2.88 Rightly so, in our judgement, the SEARA has recently given considerable emphasis to the development of an appropriate institutional framework encouraging the 57Jones, William (1995), 'The World Bank and Irrigation" OED report 58 Dinar, Ariel and Subramanian, A. (1997), 'Water Pricing Experiences- an international experience", World Bank Technical Paper # 386 65 involvement of water users associations, the development of appropriate legal framework, moving towards the implementation of a water pricing policy more consistent with cost recovery and pricing of irrigation water that reflects its opportunity cost in alternative uses. 2.89 A system of tradable water rights would seem to offer significant advantages vis-a-vis administrative allocation methods. The key characteristic of tradable water rights are that they are secure and can be legally traded under the guidelines established by the legal, regulatory and institutional framework. In all cases, the water rights are separate from land and thus may be traded separately. Ideally, water rights should be allowed to be sold at freely negotiated prices. The experience with tradable water rights in Chile, Mexico, in the some regions in Colorado (USA) shows this is a viable and effective approach to water allocation.59 An detailed evaluation of the relative merits of tradable water rights approach for the State of Ceara seems most desirable. How Is Irrigation Financed? 2.90 It is our understanding that the costs of supplying raw water in Ceara are rising. Thus the question of financing of water supply and particularly of irrigation in our case is critical. One has to make the distinction between large water resource projects (usually multipurpose) and irrigation projects. In some cases the former does not involve agricultural use of water for irrigating. Here we are referring to irrigation projects only. For these to be economically profitable water productivity should be "high". Water pricing that reflects its true scarcity value would seem a sine qua non condition to achieve high water productivity , and here is where the tradable water rights approach could represent a major institutional innovation to achieve higher water productivity among its various uses (agriculture, urban and industrial use). 2.91 Whether full cost recovery? Is a critical question to examine further. Full cost recovery of maintenance and operations cost is presumably a generally accepted principle. It is relevant to mention that for example in Mexico (as in Chile and Australia), in recent years, the operation of irrigation districts throughout Mexico have been turned over to farmers. One of its consequences is that there had been a dramatic increase in cost recovery, from about 30% to 80%. A lesson is that the key is not only cost recovery per se, but rather financial autonomy and accountability to users.60 2.92 Cost recovery of capital costs is a far more complex question. Can one make the case that such large irrigation schemes in Ceara have an significant "public good" component? Can one identify significant (positive and/or negative) externalities? These are complex questions which deserve attention in the design and implementation of the irrigation strategy in the State. Our goal here is only to raise the issues. 59 There is a substantial fairly detailed literature on when and how to establish tradable water rights. These include works by Rosegrant and Gazmuri at IFPRI, Quiroz and Rios in Chile, Hearne and Easter (1995) in 'Water Allocation and Water Markets", Worlcl Bank Technical Paper # 315, and the work of Holden, Paul and Matheen Thobani including their 1995 study "Tradable Water Rights - A Property Rights Approach to Improving Water Use and Promoting Investment", World Bank, June 1995. 60 See John Briscoe, 1997, 'Managing water as an economic good: rules for reformers", in Water Supply, 15(4): 153-172. 66 2.93 Subtractability and excludability are the two principal criteriato define whether an investment qualifies as a public good . Except for hydroelectric generation which make non-consumptive use of water rights, the subtractibility principle would have limited application to irrigation investments for agricultural use. However, a dam builtto provide flood control on a stream is a clear case when the excludability principle indicates that there is a public good element. It is difficult to exclude farmers from their use. Similarly there could be other cases where the monitoring of individual use is so costly that cost recovery according to actual use is impractical. This is linked to the high "transactions cost" argument, which tends to create fragmented markets. Transactions among individuals who are not adjacent to one another require changes in the physical infrastructure, which typically entail organizing water users. The promotions of such organizations are, we understand, a major focus of the current policy of the Secretaria de Recursos Hidricos and of the World Bank program with the State government. 2.94 Should we consider potential externalities and market failures as relevant factors for the definition of a cost recovery strategy inirrigation projects in this State? It is easier to identify potential negative externalities, such as the contamination of surface and groundwater with chemicals from irrigation. The effect of surface water irrigation in recharging the groundwater aquifer is another case of a potentially positive externality which conceptually could be internalized if groundwater users pay the surface water irrigators for this service. Some could argue that the potential effect (reduction)on food prices would be a case of positive externality for consumers from irrigation. This line of reasoning is questionable. Ceara is one producer, albeit a small one, part of a large integrated market for food products in Brazil (and increasingly throughout Mercosur and the rest of the world); in the jargon of economists it is a "price taker" for most goods, and thus the food price argument would not apply as an externality of significance. 2.95 It would appear that the provision of more permanent and particularly seasonal employment - on farm and in packing and processing plants- is potentially the main "external" benefit of large scale irrigation projects in the State. To put it differently, are market wages significantly above shadow wages in these areas? On Rural Poverty 2.96 A household income analysis was conducted based on the LSMS - PPV survey taken in 1997, that covers 521 households in the Northeast of Brazil, but only a small fraction of which are located in Ceara. Thus this data base does not allowed a detailed analysis at the State level. However, the findings from this analysis is suggestive of general features considered relevant for the State. 2.97 The rural income analysis indicate that absolute poverty and indigence levels in rural areas of the Northeast, including Ceara, are extremely high. According to this data, approximately 55.5% of rural households in the sample fall under the "high poverty line" which means that they had a per capita income of less than 204 R$/p.a. (US$189) and 17% of households fall under the indigence line (per capita of less than 65R$p.a.). 2.98 Pensions and wage income are important income sources for the rural poor in the region. 67 2.99 The analysis also suggests that in rural areas in the Northeast of Brazil the poorest are not the landless workers; the poorest tend to be the small farmer in the minifundio in parts of the State, constrained to have less labor mobility (than the hired workers) and usually with less access to public services such as electricity and perhaps education and health. 2.100 A substantial reduction of labor in agriculture in the semi-arid areas seems inevitable, considering the high incidence of poverty, the very large absolute number of very small farms, and the relatively low agricultural growth potential in non-irrigated areas. 2.101 In the long-run, income for the rural poor will be largely determined by the evolution of real wages in the region. Rural-urban migration and the promotion of rural non-farm employment are critical variables. More training and education opportunities to allow the rural poor to compete for the higher paying jobs, and raise productivity for those who stay, appears to be the rnost critical policy variable for the reduction of rural poverty. 2.102 The current program of Reforma Agr6ria Solidaria for the State covers approximately 3,700 families (700 already settled and 3,000 in the pipeline). The current goal is to reach a total of 15,000 families in approximately 5 years. An evaluation of the potential impact of this program is beyond the scope of this report. Moreover, itis a new program, so it is too early to assess its impact. On the whole, it seems to be carefully designed and implemented. However, this program is likely to reach only a small share of farmers which are poor. Providing land ownership, technical assistance and some credit through what amounts to a highly subsidized scheme to a high proportion of the farmers which are poor - tenants and ocupantes, and expanding the size of the very small owner farms - would represent an unrealistically high demand on the government's budget. Thus the importance of identifying and implementing a viable rural poverty alleviation strategy for those not reached by the Reforma Agraria. 2.103 This report suggest that while the traditional agricultural areas (particularly in the semi-arid zone, Sert5o) will not be a source of major aggregate growth of the economy, a policy of abandoning these areas would be a mistake. This is because a very large number of people living in these areas but also because of the possibility of improving the living standards of a proportion of those who stay in these areas through productive investments (small dams, tube weels, etc.) which can be efficient even though - because of their small scale - are unlikely to contribute significantly to the overall economy of the State. -2.104 Finally, one should note that in designing a strategy for rural poverty alleviation it is crucial to distinguish among the different types of the rural poor, their household characteristics, and their sources of income. As suggested for example in Valdes and Wiens (1996),6' three distinct groups of rural poor households were identified One, which reasonable good prospects in agriculture (including both farmers as well as agricultural laborers); a second group of households with some prospects for 61 See chapter on Rural Poverty, pages 98-99 in the Annual World Bank Conference on Development in Latin America and the Caribbean, 1996: Poverty and Inequality". Shahid Javed Burki, Sri-Ram Aiyer and Rudolf Hommes, eds. 68 remaining in farming and reaching a level of household income at least equal or above the poverty line will depend essentially on a substantial share of income from off-farm employment. A third group appears to be 'trapped' in extreme poverty with no viable future in agriculture and faces considerable barriers in finding off-farm employment. The last group are generally older, often where a widow is the head of the household, and farm in poorly endowed areas. The point of differentiating between these groups of rural poor is to highlight the need to identify specific strategies that fits in the needs for each of these groups, depending to a great extent on each household's capacity for generating income from various sources. 2.105 Also important for the design of the rural poverty alleviation strategy is the need to look explicitly at labor market restrictions. Agricultural employment can be very sensitive to labor contract legislation affects the true cost to employers of hiring laborers. Both farm and rural non-farm employment are particularly sensitive to general labor regulations, which do not allow the flexibility to tailor the contracts to the characteristics of the firm an the available labor in a given season and locality. Agriculture is confronted with considerable instability in production and prices - and thus sharp fluctuation in labor demand - and with the need to process the harvest in a short period of time. Moreover, it is a sector characterized by high monitoring costs and highly seasonal patterns of work, generally under very heterogeneous conditions, even with the same geographic region. If the labor code establishes too many regulations, it limits the use of contracts which induce the cooperation between workers and employers that would otherwise increase total factor productivity. There are some evidences in World Bank studies that the removal of restrictions to free bargaining on labor contracts will add a certain dynamism to the rural labor markets. The assumption by governments that that basic conditions for all workers will improve if the government adopts requirements raising payroll taxes, in- kind payments, costly severance payments, restrictions on the flexibility for sub- contracting and for dealing with seasonal employment, reflects a misunderstanding on how labor market operate. Often the net effect could be that the new restrictions under the labor code reduced rural employment, restricting the opportunities for the rural poor to generate more cash income and diversify its sources of income. 69 3. THE PEOPLE: REDUCING POVERTY This chapter is based on a background paper by Francisco H. G. Ferreira. The author is grateful to Marcelo Neri, Louise Keely and Radha Seshagiri for their invaluable assistance. The subsection on drought relief draws heavily on Martin Ravallion's Back-to-Office Report from his mission to Northeastern Brazil, dated September 8, 1.998. 70 Introduction 3.1 Two things about poverty in Ceara are immediately striking. The first is how much is clearly being done, by various levels of government and agents in civil society, to reduce it, and to improve living standards amongst the poor. The second is how much poverty, despite all their efforts, there still remains. With an average monthly household per capita income of R$132, Ceara is close to the Northeastern average (R$135) and much below the national average (R$284).62 Even our low (or 'food-only') poverty line - which is given by the local value of a food basket that yields an internationally accepted caloric intake - still leaves almost exactly half of Ceara's population living in poverty (as compared to 23% for Brazil; or 3% for the metropolitan area of Sao Paulo). A slightly more generous, 'food-plus' poverty line leaves a staggering 76% of Ceara's people below it. Both of these poverty lines are explained in greater detail below. 3.2 In light of this basic picture, the objectives of this background paper are threefold: (i) to provide an overview of the incidence, severity and profile of poverty in Ceara in 1996, as well as a brief account of its evolution since the mid-1980s; (ii) to summarize the main instruments of public policy designed to assist the poor, across sectors; (iii) and to suggest possible policy adjustments which the new State government might consider to enhance the effectiveness of its anti-poverty policy. 3.3 The paper is organized as follows. Section 2 provides a brief overview of the recent evolution of poverty in the state, before focusing more narrowly on the basic poverty and inequality statistics, as well as on a more disaggregated poverty profile, based on the PNAD 1996 household survey. The data and methodology are briefly discussed, and the emphasis is firmly on the characteristics of the poor, rather than on exact measures of poverty. Section 3 describes the current policy instruments aimed at facilitating asset accumulation by the poor (or directly redistributing assets to them), and then provides our comments and suggestions on the existing strategy. These policies are intended to reduce long-run, 'permanent income' poverty, as well as to contribute to a more efficient use of the productive potential of the poorer citizens of Ceara. 3.4 Section 4 considers the policies and interventions, usually of a more macroeconomic or systemic nature, which could reduce distortions that currently lower the retums on assets owned by the poor. This provides an important linkage with the remaining sections of the Report. Section 5 turns to the issue of transitory poverty and vulnerability to shocks, of particular importance in an economy which is subject to highly (cross-sectionally) correlated shocks, such as those brought about by the drought of 1997/98. It describes the existing policies which seek to address the needs of these vulnerable groups, and then provides our comments and recommendations. Section 6 brings the main recommendations together, and suggests links to the growth and fiscal components of the SEM. 62 Figures based on PNAD 1996 household survey data, rather than national accounts. See below. 71 Poverty in Ceara: the Facts A Brief History63 3.5 While the analysis undertaken specifically for this paper was based on a single wave (1996) of the Pesquisa Nacional por Amostra de Domicilios (PNAD) household survey, it is useful to briefly review the recent history of poverty reduction in the state, and to place it in a regional and national context. In so doing, I shall rely heavily on a study by Rocha (1998). Rocha's analysis was based on a different set of poverty lines, and on a slightly different treatment of the PNAD data. As a result, the values of scalar poverty measures from that study are not comparable to those presented in the next section. Nevertheless, the methodolcgical differences are constant over time, and there is no reason to suppose that intertemporal comparisons based on her findings would be qualitatively different from those based on our analysis, had we been able to extend it backwards over time. The results are therefore reported below in index form, so as to abstract from absolute values and focus on trends. 3.6 Table 3.1 below presents the poverty headcounts for Ceara, the Northeastern region and the country, based on the PNADs for 1985, 1990, 1993 and 1996, with the Ceara 1996 value chosen as a base value. Table 3.1: Poverty Headcounts in Ceara, the Northeast and Brazil, 1985-1996, based on a set of regionally specific poverty lines proposed by Rocha (1998). Index: Ceard Headcount in 1996 = 1.0 Area 1985 1990 1993 1996 Ceard 2.1 1.7 1.5 1.0 Fortaleza 1.1 1.1 0.7 0.5 Urban 2.0 1.6 1.4 0.9 Rural 2.8 2.3 2.3 1.7 Northeast 1.7 1.5 1.5 0.9 Metropolitan 1.1 1.1 1.1 0.6 Urban 1.4 1.1 1.1 0.7 Rural 2.3 2.0 2.0 1.3 Brazil 1.0 0.8 0.8 0.5 Metropolitan 0.7 0.6 0.6 0.3 Urban 0.8 0.6 0.6 0.4 Rural 1.6 1.5 1.4 0.9 Source: Rocha, (1998), Table 2. 3.7 The first remarkable result is that, in the single decade since 1985, the incidence of poverty in the state of Ceara - as well as in the Northeastern region of the country and in Brazil as a whole - was halved. This was largely due to two separate growth episodes over the period, each of which had a substantial impact on per capita incomes. The first was the 1985-87 growth spurt, associated with the Cruzado Plan for macroeconomic stabilization.64 The plan failed under pressure from an unresolved fiscal deficit and was followed by a severe recession in 1990-91. As a result, poverty incidence remained stagnant over 1990-1993, both in the Northeast and in Brazil as a whole. Ceara did remarkably well to maintain a downward momentum in poverty incidence during this 63 This subsection draws heavily on Rocha (1998). 64 See Ferreira and Litchfield (1996) on the links between macroeconomic trends and the evolution of poverty and inequality in Brazil in the 1980s. 72 period, despite the adverse macroeconomic environment. It is likely that this reflects state-specific policies, as some of the evidence in Table 3.2 confirms. Note, however, that the entire decline in poverty in the state over this period took place in urban and metropolitan areas, with rural areas seemingly unaffected. 3.8 The second growth episode was associated with the Real Plan of 1994-1996. Despite negative growth early in the decade, stability after 1994 spurred a consumer-led boom which was sufficient to keep 1990-1996 average annual GDP growth rates for Brazil at 3.0% (and 4.9% for Ceara).65 The return to a more propitious macroeconomic environment (which was to last until 1998) led to the resumption of poverty reduction in the country as a whole, and to its acceleration in Ceara. 3.9 While the overall picture seems quite reassuring, then, two notes of caution are warranted. First, reduction in rural poverty, both in Ceara and elsewhere, was slower than that for urban and metropolitan areas. This is cause for concern since, as we shall see in the next section, rural areas concentrate the most pervasive and the deepest poverty, particularly in Ceara. Second, evidence not presented in the table suggests that the reduction in poverty incidence was achieved largely through increases in the incomes of those closest to the poverty line, with a simultaneous increase in the average distance between the incomes of the poor and the poverty line (i.e. P(1)1P(0); see below). While poverty gaps (P(1)) also fell, this was driven largely by the fall in headcounts (P(0)). The depth of poverty measured only amongst the poor: D = _ =i =-P(1) =() pi z p P(O) increased from 0.39 in 1985 to 0.50 in 1996 in Ceara. A similar phenomenon was observed for Brazil as a whole. See Rocha (1998). This reinforces the commonly held view that, in Ceara as elsewhere, there may now remain a "hard core" of poverty, which is predominantly rural, mostly associated with very low levels of schooling, and which is less responsive to economic growth per se, requiring instead a stronger component of direct intervention. A much more detailed inter-temporal analysis of the poor than that which is presented here would be necessary to test that hypothesis. But the evidence on the increasing average distance between the incomes of the poor and the poverty line is certainly worth bearing in mind as a warning signal. 3.10 Let us turn, then, to a set of indicators which is more closely associated with direct policy interventions. Namely, let us trace the evolution, over the same period, of three 'access-to-service' indicators for the population of Ceara: adequate access to clean water, the availability of electricity to the household, and the availability of (direct or indirect) rubbish collection. The figures reported in the PNAD samples for each of the relevant years are contained in Table 3.2. 3.11 First of all, it is noticeable that there are considerable differences in the extent of coverage among these -three services, with water being far more widespread than electricity, and rubbish collection being least common. Across all three service types, 65 See Tyler (1998). 73 there was uninterrupted improvement over the period.66 This clearly reflects a successful state government initiative, despite adverse macroeconomic conditions. The rise in electricity connection rates has been steadier over time, but has clearly made substantial inroads into rural areas, which were previously largely untouched by the grid. This has had considerable impact on both productive potential and living standards among some (if by no means all) of the rural poor. Table 3.2: Access to Basic Services Over Time, State of Ceari. (%) (Share of Population in Households with adequate...) Year Access to Water Electricity Connection Garbage Collection 1985 67.4 50.5 25.2 1990 66.4 65.5 38.0 1993 99.7 69.1 46.8 1995 99.6 71.3 48.4 1996 97.9 73.9 47.6 Source: Rocha, (1998), Tables 5, 7 and 8. 3.12 The picture is less satisfying as regards garbage (or rubbish) collection. Since the reported figure is for aggregated direct or indirect (e.g. communal or neighborhood) collections, this leaves over half of the population of Ceara having to dispose of its solid waste by burning or dumping. This remains an unacceptably high proportion, with inevitable consequences in terms of sanitation, hygiene and public health. Table 3.5 provides a more detailed breakdown. 3.13 Unfortunately, data are not available on the evolution over time of sewerage and sanitation services, which would otherwise clearly deserve reporting in Table 3.2. See Rocha (1998) for a discussion of the reasons for this. Nevertheless, it bears noting that, according to the PNAD 1996, sewerage services are not adequate for a significant majority of the population. We return to this service in Table 3.5 and paras. 3.18ff. Table 3.3: (Household Per Capita) Income Shares by Population Tenth ('Decile') in Ceari (%) Tenth 1985 1990 1996 1 0.8 1.3 0.6 2 1-6 2.6 2.2 3 2.2 3.3 3.1 4 2.8 4.3 3.8 5 3.6 5.2 4.9 6 4.6 5.7 6.1 7 6.0 7.4 7.8 8 8.6 9.2 9.5 9 14.8 14.7 14.8 10 55.1 46.4 47.1 Source: Rocha, (1998), Table 14. 3.14 Finally, let us consider briefly how the distribution of income in Ceara evolved between 1985 and 1996. Table 3.3 presents income shares accruing to each population decile in the state. Once again, the PNAD incomes on which these tabulations are based are treated slightly differently from those which were analyzed specifically for this study, 66 Except for access to water after it became essentially universal in 1993. While small variations like that between 1993 and 1995 are likely to reflect no inore than sampling errors, the slightly more pronounced fall in 1996 suggests either that new poor households are locating in domiciles without adequate water connections, or that sample responses in the two preceding years may have been somewhat suspect. A closer investigation would be required, but is beyond the scope of this paper. 74 and which are discussed in the next session. Nevertheless, these differences are likely to be time invariant, so that a comparison of trends is both valid and revealing. 3.15 Between 1985 and 1990, there was an unambiguous 'improvement' in the distribution of incomes, with shares for the bottom eight deciles rising at the expense of the top two. Earlier analysis of the period for Brazil (see Ferreira and Litchfield, 1996) suggests that at least part of this reflects the effect of stability and growth in the wake of the Cruzado Plan of 1986. However, its impacts on income distribution in the country as a whole had been largely eroded by 1990, and there may be Ceara-specific factors at play here. 3.16 Growth between 1990 and 1996, on the other hand, seems to have 'been unequalizing. In fact, while the top decile, which holds almost half of all incomes generated in the state, did not recover its 1985 share, the shares of the bottom five deciles fell between 1990 and 1996, while those of each decile 6-10 increased. Whatever poverty reduction took place over this period then, as indicated byTable 3.1, was due predominantly to growth, rather than to any progressive redistribution. In fact, the loss in income shares for the poorest deciles is clearly consistent with the earlier finding that the depth of poverty (as measured by P(1)/P(0)) seems to have increased substantially over this period, despite a decline in incidence. 3.17 Putting it simply, Ceara has always been a poor state by Brazilian standards. Its poverty reduction performance in the 1985-1996 period was basically at par with the national average, which implies a substantial reduction in incidence (SeeTable 3.1). This was accompanied by a considerable increase in the coverage of a number of important publicly provided services, such as safe water, electricity and garbage collection. In this latter respect, the state did better than most others in the Federation. However, since the economic growth which was largely responsible for the reduction in headcount ratios was not equalizing, and the poorest segments of the population seemed to have suffered relative - and possibly absolute - income losses, measures of the depth of deprivation did not improve in the same way. These remaining poor people, to whose characteristics we now turn, still account for some 50% of the population of Ceara, even by the lowest reasonable poverty line we could set. The next section investigates their profile in 1996. Aggregate Indicators and the Poverty Profile in 1996 3.18 The analysis in this section is based on data from Brazil's main household survey instrument, the Pesquisa Nacional por Amostra de Domicilios (PNAD) 1996, which is representative at both the national and the State levels.67 The PNAD 1996 questionnaire contains information on a number of variables, pertaining both to the household and to individuals within the household. The former include standard demographic variables, location and access to basic services, as well some information on ownership of durables. The latter include information on gender, race, age, educational attainment, sector of activity, job tenure, and incomes from various sources. 67 The PNAD is an annual survey collected by the Brazilian National Statistics Institute (IBGE), on non- Census years. 75 3.19 Since the PNAD does not report consumption expenditures, the welfare indicator used in this paper is total gross monthly household income per capita, spatially deflated. y l.e. it is given by y,i:= -.i , where households are indexed by i, spatial areas are Iin, indexed by j, Y5, is the total gross monthly income of household i in region j681 l is the price deflator for spatial area j , and ni is the size of household i.6 3.20 Spatial price deflation adjusts incomes for the variation in the overall cost of living across different areas in the State, and allows for more meaningful comparisons with the rest of the country. The price index was computed by Ferreira et. al. (1998) for the entire country, and is based on the expenditure patterns surveyed by thePesquisa de Padr6es de Vida (PPV), also run by IBGE. It is given by I, = OF + + OH .F is the food q+p+ 7r+ share in housing and food expenditure, and CaH is the corresponding housing expenditure share (averaged across deciles 2-5). p and q are food price and quantity vectors in the regions they are indexed by. The quantities are averages of the consumption quantities for each commodity reported by deciles 2-5 in each region, and the prices are the implicit prices for those deciles. 7X is a housing cost analogue for the same deciles in each region. All of these are taken from the PPV data set. The reference region, indexed by + , is metropolitan Sao Paulo. 3.21 Once household incomes per capita are thus deflated to take account of regional cost-of-living variations, the income vector is ready for welfare and inequality analysis. For poverty analysis, however, a poverty threshold needs to be defined, so as to identify the poor. Following standard practice, we adopt a set of three poverty lines, to check the robustness of the profile to variations in the specific line chosen. Since we have deflated the incomes by a spatial price index, we do not need region-specific lines. All three lines are expressed in 1996 reference region (metropolitan Sao Paulo) prices. These are: (e) A low (or 'food-only') poverty line, equal to the cost of the 'minimum food basket' in the reference region: ; = pRq;, where q,* is the same vector qR of average consumption bundles for deciles 2-5 in reference region R, scaled up to yield a caloric intake equal to the FAO minimum intake of 2,288 calories per day.70 This line is equal to R$ 65.07, and is the main poverty line used in this paper. 68 Total household income Y includes a value for imputed rent for households which own their homes, in line with current international practice. Since estimated imputed rents are not part of the PNAD questionnaire, our imputation was based on the predicted values from a regression of rents actually paid in the rental market on a comprehensive set of location and household characteristics. For details, see Ferreira et. al (1998). 69 In using per capita incomes throughout the analysis, we are likely to be presenting an upper-bound for poverty estimates. Research has shown that using equivalence scales which are more sensitive to economies of scale within the household reduces the aggregate poverty estimate. See Coulter et. al. (1992) for a general discussion, and Ferreira et. al. (1998) for a robustness analysis for Brazil. 70 This figure is the exact caloric recommendation for metropolitan Sao Paulo, according to IBGE/IPEA (1998), Table 1. 76 (f) A medium 'food-plus' poverty line, which scales up the cost of the minimum food basket to take into account the non-food expenditures of those people whose total incomes would just allow them to purchase that minimum food basket. I.e. z- = , where 8L is the Engel coefficient for households whose total income is equal to the indigence line. This line is worth R$ 131.97. (g) An upper-bound 'food-plus' poverty line, which scales up the cost of the minimum food basket to take into account the non-food expenditures of those people whose actual food expenditures equal the cost of the minimum food basket. I.e. z+ = , where 6u is the Engel coefficient for households whose 8u total food expenditure is equal to the indigence line. This line is equal to R$ 204.05. 3.22 Table 3.4 below summarizes some of the aggregate findings about poverty, inequality and living standards in Ceara, and compares them to the equivalent figures for Brazil, each of the macro-regions and a comparable Northeastern metropolitan area, Salvador. The poverty statistics are computed for the main poverty line of R$65.07.7' 3.23 Table 3.4 contains some striking results. The variation in headcount measures (P(O): the proportion of the population below the poverty line) across Brazil's macro- regions is very large. While Ceara is only marginally above the Northeastern average (at around 50%), this is 5.4 times greater than the poverty incidence in the country's prosperous Southeast. Poverty also seems to be deeper in Ceara: P(1), which is the product of incidence and the average distance between the incomes of the poor and the poverty line, is 7.4 times greater in Ceara than in the Southeast. When we weight the largest distances more heavily, through the P(2) measure, poverty is a full 8.8 times 71 The reader may wonder why the low ('food-only') poverty line was chosen as the main identifying threshold for this paper. After all, the medium 'food-plus' line is a well-known lower-bound poverty line concept, widely used in other studies. The basic reason is that there are good grounds to suspect that the PNAD questionnaire, even in 1996, was still far from adequate to fully capture non-wage incomes, particularly in rural areas. International evidence from much more detailed questionnaires suggests that the lack of detail in the PNAD is likely to lead to a considerable underestimate of real rural incomes (and hence to an overestimate of rural poverty), as well as to an overestimate of poverty among the self-employed in urban areas. In fact, applying the PNAD income concept to the much more detailed Brazilian LSMS (PPV) survey, yields a poverty incidence rate of 39.35% for the rural Northeast (with a lower-bound 95% confidence interval of 29.91% to 48.79%). The PNAD data yields a 68.50% rate for the same area and poverty line (Q). Readers are therefore cautioned that the poverty figures presented in this report, while the best ones available for Ceara, are likely to overestimate poverty, both due to rural and self-employment income under-reporting, and to the use of per capita incomes (see footnote 9 above). As a result, z-, whilst conceptually superior to 4, ends up yielding a poverty headcount (of 76%) which is too high to be useful for the purposes of identifying and profiling the poorest people in the state, and thus for policy purposes. To minimize this problem, we report the results obtained from the food-only line (L) in the main text. Poverty profiles exactly analogous to that presented in Table 3.5 are, however, available for the poverty lines z- in Annex Tables 57 to 70. We recognize, of course, that since the problem lies originally in the mismeasurement of rural (and to some extent urban self-employed) incomes, an ideal solution would require a better survey, rather than fudging the poverty line. In the absence of the latter, though, it was our judgement that using the lowest line for presenting results in the main text best served the interests of policy-oriented readers. 77 more severe in this state than in the Southeast, and 2.6 times greater than in Brazil as a whole. 3.24 These differences percolate to the non-money-metric welfare indicators, with the average Cearense being born with a life expectancy lower than the average Brazilian. Adult literacy is also lower in Ceara than elsewhere in the country, with barely half of the state's adults able to read and write (in 1991), as compared to 80% in the whole country. Here, there is a sensible difference even with respect to the Northeastern average, of almost ten percentage points. Income inequality, however, as measured by the Gini coefficient, seems to be lower in Ceara than in all of the country's macro-regions.72 Table 3.4: Poverty anid Living Standards in 1996: Ceari in Context P(0) P(1) P(2) g(y) Gini AdLit LEB Ceara 49.25 23.68 14.57 . 131.71 49.64 53.0 56.8 R.M. Fortaleza Core 20.06 6.49 3.07 251.66 51.83 n.a. n.a. R.M. Fortaleza Periphery 41.86 16.23 8.59 107.07 45.40 n.a. n.a. R. M. Salvador Core 24.33 8.77 4.55 266.22 64.30 n.a. n.a. R. M. Salvador Periphery 34.78 12.14 5.92 133.99 54.08 n.a. n.a. Nordeste 47.89 22.14 13.28 135.37 61.54 62.4 59.1 Norte 30.06 11.80 6.58 191.96 52.25 75.4 68.4 Sudeste 9.19 3.22 1.65 380.40 55.87 87.7 68.8 Sul 12.08 4.45 2.33 325.91 50.58 88.2 70.9 Centro-Oeste 16.63 5.90 3.08 282.75 52.92 83.3 69.1 Brazil 22.59 9.60 5.53 283.86 54.98 79.9 66.3 Notes: g(y) Mean Household Income per caDita in 1996 Reais; P(a) is a class of poverty measures given by p = n lZmx -' ( Y 0) calculated for the Low Poverty line of R$ 65.07/month; P(0) simplifies to the n~ ina z O poverty headcount, P(1) is the normalized poverty deficit, and P(2) is the Foster-Greer-Thorbecke index with c = 2. AdLit and LEB are Adult Literacy and Life Expectancy at Birth respectively and are 1991 estimates. Souwes: Columns 1-5: Authors' calculations, PNAD 1996 survey; Literacy and Life Expectancy: UNDP (1996) 3.25 Having placed Ceara in the national context, Table 3.5 below investigates the characteristics of the state's poor in greater detail, by means of a standard tabulated poverty profile. Rows denote specific population subgroups. The columns denote their population shares, mean household per capita incomes, headcount indices, poverty deficits, FGT(2) indices, and contribution to total poverty in the State. See the Notes to the table below. 3.26 Table 3.5 contains a wealth of detail, for the reader's perusal. Some aspects, however, are particularly noteworthy, either in understanding the social make-up of the state, or for designing policy responses to the persistent challenge of poverty. First, there are clear differences in poverty incidence, depth and severity across spatial areas, with central Fortaleza having a headcount of 20%, while the figure more than doubles in the periphery, to some 42%. Outside Fortaleza, poverty seems to decline monotonically with city size. It is highest in rural areas (77%), and lowest for large urban areas (31%). These differences are even more pronounced for measures which take into account the depth of deprivation, such as P(1) and P(2). Since population shares vary, this makes for the overall composition of poverty which is illustrated in Figure 3.1. 72 Note, however, that inequality measures for regions contain an element of 'between-state' inequality, which the Ceari figure clearly does not. Generally, one expects inequality to decline as one moves from large and heterogeneous aggregates to its components, provided these are more homogeneous. 78 Table 3.5: Poverty Profile 1996: Ceari, z = C (R$ 65.07/month), I = I+, 0=1.0 Household Subgroups fk 1(Y)k PO4 Pik P2k SK Characteristics Total 100.00 131.71 49.25 23.68 14.57 100.00 Location Metropolitan Core 28.60 251.66 20.06 6.49 3.07 11.65 Metropolitan Periphery 8.66 107.07 41.86 16.23 8.59 7.36 Large Urban 4.31 166.95 30.87 11.09 6.36 2.70 Medium Urban 6.88 132.19 47.68 18.58 9.44 6.66 Small Urban 16.40 106.84 51.14 23.32 13.87 17.02 Rural 35.15 47.37 76.51 42.21 27.73 54.60 Other/Not Specified 0.00 0.00 0.00 0.00 0.00 0.00 Dependency 1 6.72 340.81 2.34 0.49 0.14 0.32 Ratio* 14 23.32 46.41 83.23 49.53 33.65 39.41 Other/Not Specified 2.02 15.04 97.53 79.02 67.58 4.00 Housing Status Own House, Paid, with 58.61 140.41 44.77 20.61 12.33 53.28 Own Land Own House, Paid without 12.69 64.12 69.28 38.14 25.55 17.85 Own Land Own House, Still Paying 4.04 270.21 17.29 5.70 2.88 1.42 Rent 10.08 199.81 30.44 10.66 5.06 6.23 Ceded 14.21 67.64 71.99 37.64 23.94 20.77 Other 0.31 159.87 61.40 32.23 22.26 0.38 Not Specified 0.07 184.37 55.49 18.12 5.92 0.08 Water Piped 51.73 204.85 27.26 9.98 5.31 28.64 Not Piped 48.24 53.18 72.86 38.38 24.50 71.36 Other/Not Specified 0.02 316.08 0.00 0.00 0.00 0.00 Sanitation Sewerage System 4.85 217.17 23.78 7.00 3.24 2.34 Concrete Cesspit 1 3.72 368.08 12.60 4.10 2.07 0.95 Concrete Cesspit 2 16.25 273.03 20.13 6.73 3.20 6.64 Rudimental Cesspit 39.49 118.15 41.29 16.90 9.38 33.11 Drain 0.72 66.18 66.24 23.16 9.17 0.97 River or Lake 0.14 66.56 69.57 25.37 11.28 0.20 Other 0.07 240.42 42.54 20.45 9.83 0.06 Not Specified 34.75 45.21 78.98 43.74 28.83 55.72 Electricity Yes 73.99 163.25 37.62 16.06 9.25 56.52 No 25.95 41.73 82.39 45.41 29.74 43.40 Other/Not Specified 0.06 150.21 60.93 19.89 6.50 0.08 Waste Disposal Collected Directly 40.95 218.35 24.78 9.01 4.66 20.60 Collected Indirectly 7.00 153.36 32.08 10.23 4.67 4.56 Burned 15.85 67.74 72.02 38.01 24.43 23.17 Unused Plot of Land 34.92 57.08 70.72 36.93 23.63 50.14 Other/Not Specified 1.29 70.09 58.64 27.59 16.29 1.54 Characteristics of Subgroups fk I(Y)k POk Pk P2k Sk the Head Gender Male 83.05 128.13 51.61 25.47 15.83 87.02 Female 16.95 149.23 37.70 14.93 8.36 12.98 Race Indigenous 0.13 62.02 80.22 28.02 9.78 0.21 White 29.41 202.75 37.64 17.15 10.40 22.48 Black 70.43 102.17 54.07 26.41 16.32 77.32 Asian 0.02 122.36 0.00 0.00 0.00 0.00 Not Specified 0.02 113.12 0.00 0.00 0.00 0.00 Age 0-24 4.34 100.82 47.46 23.71 15.25 4.18 25 to 44 Years 45.18 120.30 55.14 28.59 18.21 50.58 45to64Years 37.22 142.27 49.26 22.34 13.39 37.23 >65Years 13.26 151.05 29.75 10.71 5.25 8.01 Education 0- 1 Years 41.43 60.45 66.90 33.43 20.82 56.27 1 to 4 Years 23.26 74.40 60.17 29.38 18.25 28.42 4to8Years 17.99 130.71 34.61 14.11 8.18 12.64 8 to 12 Years 13.90 273.25 9.35 3.26 1.61 2.64 > 12 Years 3.43 813.21 0.46 0.22 0.10 0.03 Immigration Not Immigrant 55.06 104.46 58.12 29.41 18.53 64.97 Status 79 Household Subgroups fk P(Y)k Pk P, P2 S Characteristics Total 100.00 131.71 49.25 23.68 14.57 100.00 Oto5Years 5.58 136.36 41.10 19.73 11.86 4.65 6 to 9 Years 4.06 135.28 44.38 18.71 10.66 3.65 More Than 10 Years 29.97 159.79 38.59 16.31 9.35 23.49 Other/Not Specified 5.34 247.55 29.92 13.82 8.78 3.24 Labor Status Inactive 18.44 144.16 39.40 16.91 10.30 14.75 Unemployed 2.11 76.41 71.86 41.12 28.22 3.08 Formal Employees 12.16 151.12 28.30 8.98 3.84 6.99 Informal Employees 15.11 75.83 66.91 31.96 18.90 20.53 Self-Employed 38.47 96.08 58.12 30.35 19.42 45.40 Employer 4.48 349.79 26.73 11.90 7.21 2.43 Public Servant 5.76 324.56 19.77 6.79 3.04 2.31 Unpaid 3.44 67.98 64.42 33.98 22.52 4.50 Other/Not Specified 0.04 114.81 30.78 16.98 9.37 0.03 Employment 0 Years 20.55 137.21 42.73 19.40 12.14 17.83 Tenure 1 Years or More 11.09 108.77 51.96 23.52 13.71 11.70 1 to 3 Years 10.27 138.12 42.51 18.74 10.27 8.87 3 to 5 Years 6.06 157.10 36.98 15.46 8.08 4.55 > 5 Years 51.52 130.91 53.79 27.28 17.31 56.26 Other/Not Specified 0.51 59.73 76.58 33.61 17.16 0.80 Sector of Agriculture # 32.29 52.03 78.06 43.26 28.50 51.17 Occupation Manufacturing 8.73 112.41 51.31 22.05 12.10 9.09 Construction 7.56 106.91 37.63 13.49 6.40 5.77 Services 25.95 203.36 27.17 9.62 4.65 14.31 Public Sector 4.93 325.63 18.21 5.80 2.50 1.82 Other/Not Specified 20.55 137.21 42.73 19.40 12.14 17.83 Notes: Sk = k ok . Similar tables for poverty lines z = z- (R$131.97/month), and z' (R$204.05) are provided in the PO statistical annex. These poverty lines are derived according to a methodology described in detail in the background papers for the forthcoming World Bank Urban Poverty Strategy Report, 1998. 1 = I' denotes the fact that incomes were deflated using the Sao Paulo-based regional price index. 0 = 1.0 refers to the fact that incomes are household per capita values. Dependency ratio is defined as the number of household members over the number of eamers in the household. # Agriculture includes other Primary Sector occupations. 3.27 Clearly, poverty remains inescapably a rural phenomenon in Ceara. Furthermore, it only acquires some significance in two specific types of urban areas: those with less than 20,000 inhabitants (small urban areas), and the metropolitan area of Fortaleza. The evidence suggests that both of these share a common feature: they are intimately linked to the rural economy, either through residents working in rural occupations or those closely related to them (as in small towns), or by immigration from rural areas (as in the periphery of Fortaleza). If efforts to reduce poverty were to be spatially targeted, rural areas should clearly receive the bulk of resources, with urban projects concentrating on small towns and on Fortaleza. 3.28 The profile also suggests that poverty increases with dependency ratio, which is a reasonable enough result, as this measures the ratio of non-eamers to earners in a household. However, as footnote 69 indicated, the numbers might well overestimate this tendency, since it takes account neither of economies of scale within households (through the sharing of fixed costs), nor of differences in needs between different ages or genders, say. 80 Figure 3.1: Spatial Composition of Poverty in Ceari Metro Core 12% Metro Periphery 7% Large Urban --\ 3% Medium Urban Rural J 7% 54% Small Urban 17% 3.29 Some of the variables on access to services are also revealing of standards of living across the state. Only half of Ceara's population live in dwellings with access to piped water.73 More strikingly, less than 5% live in dwellings connected to the main sewerage system, while nearly 60% use cesspits ('fossas septicas') of different types to dispose of their sewage. While electricity is more widely available, fully a quarter of the population does not have it at home (which compares to 8% in the country as a whole, and 3% in the South and Southeastern regions). Over half of the population (and three- quarters of the poor) do not have their garbage collected, whether directly or indirectly, and must dispose of it either by burning or dumping in unused land plots, double the shares in the South of the country.74 3.30 When it comes to characteristics of the household heads, the two most important determinants of the probability of being poor are education and occupational sector. Figure 3.2 plots the education profile, which shows how strikingly poverty incidence declines with the education of the household head, from over two-thirds for those with one year of schooling or less, to less than 1% for those with more than twelve years (i.e. some time spent at a college or university). 73 Although, as Table 3.2 indicated, this is not the same as enjoying an 'adequate' water supply. When this is extended to encompass access to a well, 'acude', or natural sprng, the coverage is near universal. 74 For municipal breakdowns of a number of the indicators discussed here, albeit without the same adjustments to the data, see IPLANCE (1997). 81 Figure 3.2: The Poverty-Education Profile in Ceari 70 - 66.90 < 60.17 60 - x 40 34.61 0 301 20 9.35 l0 O- I Years I to 4 Years 4 to 8 Years 8 to 12 Years > 12 Years Years of Schooling 3.31 Figure 3.3 displays poverty headcounts in different occupational sectors. As expected, those directly involved in agriculture are overwhelmingly poor (78%). Public servants do best of all, with only 18% in poverty, followed by workers employed in the services sector, with 27% poverty incidence. Construction, a predominantly unskilled urban sector, has an associated headcount of 38%. Manufacturing, which comprises not only modern industry in and around Fortaleza, but also the mostly backwards, low- productivity food-processing enterprises scaftered across the interior of the state (of which cashew-nut 'factories' are the prime example), has a relatively high poverty incidence associated with it, at 51%. 3.32 However, because the population share living in households whose heads work in services (26%) is approximately three times that associated with manufacturing, the share of the poor accounted for by households whose heads work in services is second only to agriculture, at 14% and 51% respectively. 3.33 Finally, as regards the labor force status of the population, it is noteworthy that only 12% of household heads described themselves as formal employees in 1996, as against 54% who were counted as informally or self-employed ('sem carteira' and 'conta propria', respectively). Only 2% reported being unemployed. These labor-market features of low unemployment and high informality are exacerbated amongst the poor, amongst whom unemployment was a remarkably low 3%, and the combined informality rate (defined as above) was 66%. 82 Figure 3.3: The Occupational Sector - Poverty Profile in Ceari 90 1 so *P( 78.06 70 * 5 60 51.31 0 -i ~~~~~~~37.63 30 __E27.17 18.21 201 10 K Public Sector Services Construction Manufacturing Agrculture Sector Building the Assets of the Poor. How it is being done. 3.34 Whichever poverty line the reader chooses, and despite the fact that rural and self-employment incomes may have been underestimated (and rural poverty overestimated) in this (and any other PNAD-based) study, the fact remains that Ceara is clearly still a poor state. This has been amply documented in paras. 3.18ff above, but another way of capturing it is to compare the total poverty shortcoming ratio (TPSR) for Ceara with its national analogue. The TPSR is defined as the share of total state income which would be required, if perfectly and costlessly targeted, to eliminate poverty at a given point in time, at minimum cost.75 For Ceara, this ratio is 11.7%, which compares to 2.2% for Brazil as a whole. While this reveals the magnitude of the task facing state authorities, it also obviates the need for thoughtful and well-designed interventions. This has been recognized by a series of State governments, and considerable effort and ingenuity have been expended in programs to improve the living conditions and earning potential of the poor. S [ z - y, ,o ____ ___ ____ _ _ znP(1) 75 Formally, the TPS ratio is given by - . Notice that this ratio is explicitly np(y) nu(y) defined with respect to total aggregated household income. One could instead - as is in fact often done - use some national accounts aggregate in the denominator, such as (state) GDP. In the case of Brazil, however, where discrepancies between national accounts product indicators and household-survey-based income measures is very large, it was felt that the latter would be less informative. 83 3.35 In general, a household is poor because the flow of income from the assets it owns (including the human capital of its members) is too low. This can happen for any of three reasons, or a combination of them: their asset base may be insufficient (say, owning no land, or having very little schooling); the returns on their assets may be low (due, say to low wages for one's skills, or low prices for the crops one can plant in one's plot of land); or finally, to a shock that affects those returns temporarily (such as a drought, or losing one's job). Ceara has policies and programs in place to deal with each of these three main causes of poverty. In this section, we briefly summarize the set of policies aimed at building up the asset base of the poor. The next section turns to policies aimed at increasing returns on those assets, and Section 5 considers policies to reduce risk. Since these programs span a number of sectors, such as education, health, rural and urban development, labor markets, and social assistance, our discussioris are perforce brief, and can not do justice to the complexity of each single initiative.76 3.36 In rural areas, four main programs account for a substantial share of the resources devoted to poverty reduction in Ceara: (a) Programa de Combate a Pobreza Rural (PCPR - "Projeto Sao Jose'), which succeeded the Programa de Apoio ao Pequeno Produtor (PAPP): This program reaches most municipalities in Ceara, and provides grants and subsidized credit for small farmers. One of its main features is to rely on rural community associations, which submit proposals to a municipal council for initial appraisal. Municipal councils are composed by members of various such community associations, as well as representatives from the municipal government. Once the council is satisfied that the project meets its priority criteria, and a technical evaluation (usually by the State's Rural Extension Agency, EMATERCE) has been completed, the proposal is referred to the Program's administrators in Fortaleza, and approved subject to the availability of funds. This reliance on local councils, which are made up of both government officials and civil society representatives (members of associations), appears to have strengthened the program, making it less prone to cronyism at a local level. (b) Programa de Apoio e Foftalecimento da Agricultura Familiar (PRONAF) is a Federal program, with sirnilar aims to those of the Project Sao Jose. It too provides a source of subsidized credit for small farmers. While some PRONAF loans do appear to reach poor farmers (after all, we have seen that 78% of farmers are poor), there is a widespread sense that the Program as a whole may be less well targeted than the PCPR, and that there may be non- negligible leakage to non-poor farmers.77 (c) Programa da Reforma Agraria Solidaria, or "C6dula da Terra". Essentially a market-based land reform program, this project is supported by a World Bank loan. It too relies on local community associations to identify properties they might be interested in purchasing, and negotiating directly with the owners. If 76 See World Bank (1998) for a much more detailed assessment of policies in all of these sectors, in the Northeast of Brazil. 77 Interviews with SDR staff and program beneficiaries, July 1998. 84 a sale is contemplated, government technicians verify land titles and further negotiate the price, usually obtaining a substantial further discount. Subject to approval from these technicians, the community then receives a grant from the government, with which to buy the property, as well as subsidized credit to start farming operations, and extension services to provide advice on technology and crop choice. By June 1998, 70 associations across the State had received land through the Program, benefiting some 1,225 families, with an average of 39.2 ha. per family. (d) Programas Pro-Renda e Proger are smaller programs, managed with the support of international NGOs, notably GTZ. These programs operate in both rural and urban areas, through identifying local community associations with an innovative project that could potentially lead to employment creation and income generation in a poor area. These projects are then supported through grants or subsidized credit. 3.37 In urban areas, one program designed to deal specifically with housing is the Programa de Mutiroes Habitacionais, managed jointly by the Labor and Social Assistance Secretariat (STAS), and the Urban Development Secretariat (SDU). The program consists of partnerships with local community associations, where the State provides construction material (and sometimes the regularization of urban land titles), and the communities supply the labor to construct popular housing. According to an umbrella group of these associations (the Federa,co das Associa,6es de Moradores de Favelas e Bairros de Fortaleza), this system is much preferred to the ready-made housing programs run as an alternative by the municipality of Fortaleza, with financing from the Brazilian Caixa Econ6mica Federal (CEF). This is due both to a higher quality of the final housing stock, influenced in the design by the future users, and also to a perception that 'inspection' by local beneficiaries entails less fraud with the procurement of construction material.78 3.38 All of the programs discussed so far share one important trait. They aim at increasing the stock of physical assets owned by the poor, be it farmland, farming capital or infrastructure, or urban housing. These are, of course, terribly important for the communities affected. But in Ceara, as elsewhere, it is often the case that human capital, in the shape of skills and education, is the main asset of the poor. The Education Secretariat (SEDUC), along with various other State and municipal organs, have developed a series of programs to address the acute educational need of the poor in Ceara. PROARES (the Programa de Apoio as Reformas Sociais para o Desenvolvimento de Crian,as e Adolescentes) is one such initiative, targeted specifically at street children, those in very poor neighborhoods, or those involved with drugs, prostitution or otherwise in trouble with the police. The basic idea is to work with the children to develop an interest on their part in returning to school. For smaller children, this often involves use of the Creches Comunitarias ("Community Creches"), through the "Aprender, Brincar, Crescee' or ABC program. 3.39 But the State does, quite correctly, have an emphasis on ensuring access to and preventing evasion from schools in the first place. This is developed through projects like 78 Interview with a director of the Federa,ao das Associa,ces de Moradores de Favelas e Bainros de Fortaleza (name withheld), on July 8, 1998. 85 the Programa "Escola Viva" ("Living School"), which aims to make teaching methods more interesting to children, thereby reducing evasion and repetition rates. The "Faster Leaming Initiative" (Programa de Aceleragao da Aprendizagem) has similar aims, but focuses on students whose age to expected grade gap exceeds two years. These students are seriously behind their cohorts, and in serious statistical risk of 'dropping out'. By focusing extra teacher time and resources on them, the State hopes to reduce evasion and possibly induce some catching up by those furthest behind in their educational development. 3.40 Finally, it is recognized that perhaps the main input into the educational production function, the key determinant of the quality of education offered and hence a crucial factor in securing faster and more learning, is the quality of the teachers. Traditionally, Ceara shared the poor Northeastem statistics in terms of average schooling of teachers in the public education system. Recent reforms in hiring and appointment of school directors have contributed to an improvement in this situation, as have training initiatives such as the Teacher Training Program (Programa de Formag5o de Educadores Infantis), which aims to train those teachers with qualifications below par, in modern teaching methods and curriculum development. As a result of this concerted action, the proportion of teachers in Ceara's public schools (excluding Fortaleza) with less than completed secondary school fell from 55.7% in 1996 to 26.6% in 1998 (SEDUC, 1998). 3.41 In addition, vocational courses and micro-credit schemes are operated by PROFITEC, an agency of the municipal government of Fortaleza. Vocational training courses are also operated across the State by the SINE (Sistema Nacional de Emprego), a federal program administered by the Labor and Social Assistance Secretariat (STAS). In addition to vocational training courses, this program provides labor intermediation services, through job centers where unemployed workers and employers with vacancies can be matched. 3.42 Apart from education, the other great interface between the State and the stock of human capital of the poor is the Health System. This is an area where the State of Ceara has (deservedly) won international recognition, for its success with thePrograma de Agentes Comunitarios de Saude (PACS). These community health agents are local residents, selected on the basis of their ability to provide advice and leadership in basic health prevention and child care. Funded through the Federal health budget (The Sistema Cinico de Saude), today there are some 8,700 such agents across the State, and every municipality is covered. In fact, the State has now moved beyond the basic PACS, and launched what is seer as its 'next phase': the Family Health Program (Programa de Saude da Familia). This program envisages the support of a qualified physician and a nurse to each ten community agents. Each such 'team' is expected to cover some thousand families (or roughly 5,000 people). Of the 1,000 necessary teams across the State, 347 were in place as of July 1998. 3.43 With primary health care much improved, through the community health agents and the new Family Health Program, the State has begun to turn its attention to the need for strengthening secondary and tertiary care facilities across the State. These are severely under-provided, and the state of disrepair and the long queues observed in hospitals, even in Fortaleza, are a source of common complaints by members of the communities that depend on secondary or tertiary care from them. 86 How It Can Be Improved 3.44 The main bottlenecks for income generation in rural areas seem to be: (e) lack of basic agricultural and other skills among the uneducated. (f) lack of employment opportunities for landless workers. (g) land concentration. (h) poor access to credit, capital inputs, irrigation and extension services for subsistence and small farmers. 3.45 To address these problems, the following strategy is suggested: (a) Maintain (and possibly extend) the targeted efforts of the PCPR and the Projeto Reforma Agraria Solidaria. Ensure that beneficiaries of the latter are also covered by the former. Small scale agriculture, even in areas of the sertao central, seems to be economically viable, once basic capital goods (e.g. tractors) and some infrastructure (rural electrification, small scale acude- based irrigation) are made available. The existing approach, through local Associations, seeks to ensure that local needs are met and seems to be working well. This approach would seem much better suited to addressing the needs of the poor than grandiose schemes which seek to move large numbers of people away from vast tracts of the sertao central, towards areas where large-scale irrigation is being planned, such as the valleys of the Acarau and Jaguaribe rivers. (See Annex 2 for further discussion of agricultural policies in general, and irrigation in particular.) (b) Conduct a review of the incidence of the two above projects, to ensure that the poorest groups - rather than the 'middle-poor' - are actually being reached. If not, refocus. (c) Continue the reform of the way primary education (or basic literacy to adults) is provided in rural areas. Within the context of the Secretariat of Education motto ("All for Quality Education for All"), this might be achieved through seeing existing (and potential) local teachers as 'agents', and initiating a drive of teacher training in situ, to raise the quality of the schooling offered and make it more attractive. This could be achieved through existing programs such as "Escola Viva" and Formacao de Educadores Infantis, and would be likely to have implications both for the effectiveness of the absorption of new agricultural technologies and for the scale of off-farm employment in rural areas. (d) On the demand side, consider the adoption of a (lower-benefit) version of the Bolsa Escola program, currently in place in the Federal District, Bel6m (PA) and Belo Horizonte (MG), for families across the State. Such a program might well be modeled along the following lines: families below a certain income 87 threshold (such as half a minimum wage per capita) are entitled to a (low) transfer (such as half a minimum wage per month79), conditional on all their school-age children being enrolled and in regular attendance. Mechanisms for targeting and enforcement could probably be better designed than those currently used in the other schemes, which rely on parents (almost exclusively mothers, as it happens) filling out a proxy-means testing form when they apply for the program. The answers to questions on this form - about income, family size, housing conditions, ownership of durables, etc - provide the basis on which program administrators allocate applicants a number of points, whose total determines whether or not a family is entitled to the benefit. Whereas this is not the place for a detailed discussion of how to design a better proxy-means testing instrument, it is our view that one could be designed. Although proper statistical evaluations of Bolsa Escola programs have so far not been conducted in Brazil, good general discussions are provided in Abramovay et. al. (1998), Rocha (1998b) and Sant'Ana and Moraes (1997). In general, the programs appear to achieve their main objectives of providing a safety net to families in severe hardship, while at the same time reducing school evasion and repetition rates among fheir children, thus improving their chances to accumulate more human capital. 3.46 The state could also adopt a variant of Brasilia's "Poupan,a Escola" program, which is a supplement to the Bolsa Escola, through which one minimum wage is deposited annually in a special savings account for each child which successfully completes a school grade, and enrolls in the next grade for the following year. This account can only be drawn when the child completes secondary school, although partial withdrawals are permitted under special circumstances. In the case of Ceara, the requirement of secondary school completion might be judged too demanding, and partial disbursements may be made a little easier, so as to maximize the perceived present discounted expected value of staying in school and studying to pass a grade. 3.47 While the number of school places in Ceara as a whole is now roughly sufficient to meet the demand for primary schooling (though, emphatically, not for secondary or higher levels), it is acknowledged that a problem remains with repetition and evasion. Getting children into school is, of course, only a first step. The battle is not won unless they stay there, and actually learn and evolve through the grade system. For many poor children (and their families) in Ceara, however, the incentives for staying the school might often be outweighed by the immediate reward of work, or worse, outside school. Incentive schemes such as the proposed Bolsa Escola have appeared, elsewhere, to have a significant impact on school permanence. Since the transfer amounts need not be very large (which in fact provides for a partial self-selection mechanism), such a program is probably feasible with relatively small restructuring of state spending. (e) Continue to upgrade secondary schools, and 'expand teacher-training initiatives to provide the level of general knowledge and teaching skills required for the effective functioning of secondary-schools. In urban areas, in particular, the demand was voiced in field visits for better post-primary 79 This transfer wold be half of that in place in the other three programs cited. We believe that this is important in order to keep the program manageable and well-targeted, through preserving an element of self-selection in a much poorer state. 88 schooling, which is (probably accurately) perceived as an essential pre- requisite for the higher-quality jobs in manufacturing and parts of the service sector, such as the growing tourism industry. (f) Expand the provision of vocational training in rural areas, aimed at occupations where there might be off-farm employment or self-employment opportunities in the area. Consult with local Associations and EMATERCE technicians on these. (g) Continue the planned expansion and enhancement of the Projeto Saode da Familia. 3.48 In urban areas, the main demands of poor communities seem to be in the following areas: (h) Lack of employment opportunities. (i) Inadequate housing. () Insufficient provision of secondary education and vocational training. (k) Inadequate access to credit for micro-entrepreneurs. 3.49 To address these problems, the following strategy is suggested: (a) Ensure a continued upgrading of the quality of the State's urban labor force, by increasing the quality of public primary schooling and both the quantity and quality of secondary schooling. Use the State's version of the Bolsa Escola program proposed above to ensure that potential demand for schooling is effective. (b) Expand the vocational training initiatives currently undertaken by both the municipal and state governments. Consult with local Community Associations, Councils and important employers, to identify the courses in greatest demand. (c) Expand the program of Mutir6es Habitacionais, combining the subsidized supply of materials and the community's own labor supply. Liaise with Associations to ensure the withdrawal of residents from the Risk Areas along the banks of the rivers within Fortaleza. (d) Conduct a proper evaluation of the performance of the micro-credit schemes operated by PROFITEC and by the Proger and Pro-Renda programs, and expand them subject to a satisfactory appraisal. It is thought likely that such an expansion would only be sensible if the average amount lent fell substantially, from the current R$3,000 observed at PROFITEC, to a level in the hundreds of reais, so that working capital for truly small entrepreneurs can be financed. 89 Increasing the returns on the assets of the poor Labor and Human Capital 3.50 Increasing the incomes of poor families, and lifting them out of poverty is a function not only of the assets they own or control, but also of the market returns they command. The main asset held by the poor is generally their labor, augmented by whatever skills (human capital) they have accumulated. The main obstacle to raising returns on these assets in Brazil, and also in Ceara, seems to be the unusually high tax burden on employment, rather than on incomes or expenditures. Payroll taxes, social security contributions and other 'e,ncargos' related to employment create a substantial wedge between the wages received by workers and the total labor costs faced by employers. A reduction in such a wedge, although in principle a matter for Federal law, would likely have a non-negligible impact on labor demand, and hence on both employment and wage rates. 3.51 In addition, any remaining distortions in favor of capital intensity or against exports, tend to reduce labor demand and the returns on the main asset of the poor. Finally, high fixed costs in meeting bureaucratic requirements for export licenses or other operational permits are heavier for small-scale, often informal, enterprises than they are for larger companies, placing the former at a disadvantage, stifling entrepreneurship among the poor and lowering their relative returns on capital. Land 3.52 Returns to land also depend on a critical factor within the control of policy- makers. The competitiveness of Ceara's agricultural products depends on the transport costs added to their farm-gate prices, which in tuM depends on the quality of the transport infrastructure, crucially of roads and ports. While it is understood that the quality of Ceara's infrastructure is not below the average for the Northeast, considerable scope for improvement remains. 3.53 The issues raised in this section are important for the incomes poor people are able to extract from their assets, but they escape the scope of this paper, and provide links with other background papers for this Report, where they are discussed more extensively. Protecting the Vulnerable in a Shock-Prone Economy How It Is Being Done 3.54 In any economy, even people who own some assets, and whose return on them is generally sufficient to avoid poverty, may occasionally experience a negative shock, and fall into deprivation. These shocks can be due to any number of causes, ranging from unemployment due to corporate downsizing, inactivity due to illness or an accident; poor crop yields due to a drought, and so on. In general, though, the various kinds of risks associated with these shocks can be grouped into two broad categories: idiosyncratic risk, which is largely uncorrelated across individuals (like the risk of illness 90 or disability), and 'aggregate' risk, which is positively correlated across individuals (like the risk of low yields due to drought). 3.55 At present, the state of Ceara provides some coverage against idiosyncratic risks, through a number of mechanisms: (a) Brazil's federal public health system (the Sistema Onico de Saude), which is free of charge and (in principle) available on demand. In fact, however, the system is both quantity rationed (through queues), and employs self- selection: services are of such poor quality that many of those who can afford private health care prefer to pay for it, rather than to use the public system. (b) The Social Assistance Law (Lei Organica de Assistencia Social, LOAS), which mandates a number of benefits such as minimum income programs for families with elderly or disabled members. (c) The FUNRURAL program, which provides for minimum retirement pensions for workers involved in agricultural activities, after they reach age 65, provided they can establish that they were involved in agriculture for a substantial period of their lives. This program, known as Rural Pensions (Aposentadorias rurais), plays an important role in reducing hardship among the rural elderly, since the majority of them would never have been formal employees, and would hence not be covered by the regular Federal pension system. (d) In Fortaleza, there is also a transfer in kind to disabled people, through the award of free public transportation vouchers or bus passes ("Vale- Transporte") to the disabled. (e) Finally, the risk of unemployment is insured against through the federally- mandated Unemployment Benefit scheme (Seguro Desemprego). However, this only applies to formal sector jobs, and has a relatively tight time limit of five months. In a state where only 18% of household heads are formally employed (in either the private or the public sector), this clearly leaves a substantial majority (and a poorer one at that) of workers uninsured against employment shocks. Since labor incomes are almost certainly the main income sources for them and their families, this deserves some attention, and we return to it in the next subsection. 3.56 'Aggregate' risk in Ceara, as in the rest of the Northeast, is largely climatic. Droughts, such as the one which affected crops throughout the region in 1997/98, are cyclical phenomena in this part of the world. In fact, only considerations of history and political economy would explain why, given their cyclicality, it was only recently that governments at all levels in Brazil have developed more effective mechanisms to help people cope with their effects. In Ceara, as elsewhere in the Northeast, there are three main kinds of programs aimed at mitigating the effects of droughts.80 80 This subsection draws heavily on Mr. Martin Ravallion's Back-to-Office Report from his mission to Northeastern Brazil, dated September 8, 1998. 91 (a) Public Work Schemes ('Frentes de Trabalho contra a Seca') are set up during drought periods. The number of 'vacancies' in these schemes is federally allocated to each State, which receives from Brasilia the sum of R$65 per vacancy. Ceara then distributes it across its own municipalities on the basis of rainfall records. Local councils, like those mentioned earlier in this paper, which include government representatives as well as members of community associations, then finally allocate the jobs to those applying for them. Demand for these vacancies exceeds supply, so that quantity rationing is in place. Furthermore, the extent of excess demand varies considerably across municipalities, indicating that the rainfall allocation criterion is imperfect. Each worker receives a monthly wage of R$90 (the extra R$25 having been put up by the State government) and the work carried out is stipulated by the local council in charge of the program. (b) Emergency Food and Wlater Deliveries to Emergency Areas is carried out under the aegis of the Federal government's 'Comunidade Solidaria' assistance program. The deliveries do not appear to be very badly targeted, and there is an element of self-selection in the targeting, given the quality and variety of the food handouts. (c) Micro-Credit Schemes are set up specifically to help mitigate the effects of the drought on the operating capital of small farmers. These are operated by the Banco do Nordeste (BNB), and are in addition to their own normal lending, as well as to other micro-credit programs discussed earlier, such as those under the Projeto Sao Jose. BNB's drought loans operate under similar rules to its general lending, which continues during the drought. The main difference is that the drought loans have more favorable terms. Like all BNB loans, the interest rate is well below the market rate. For investments in farm capital the normal interest rate is 8-9%; for the drought loans it is 6%. For working capital the drought loans are at an interest rate of 3%, as compared to 6.5% for other similar BNB loans. The repayment period is about the same for the drought loans. However, there is a grace period of up to 4 years (2 years for working capital) to reflect the impact of the drought on farm revenues. Also there is a 50% rebate on principle and interest for drought loans. The rebate is covered by the federal government.81 How It Can Be Improved 3.57 For rural areas, reasonable real wages (R$5-10/day) appear to coexist with substantial unemployment, underemployment and 'inactivity'. This could be due to 'efficiency wage' mechanisms at play, but it does raise the issue of a need for further unemployment related safety-nets for rural areas. Seguro Desemprego, which is effectively a formal sector benefit, does not reach the bulk of the rural poor. The Aposentadorias Rurais, some of the LOAS benefits and the Comunidade Solidaria in- kind transfers do play a non-negligiole role, and the safety nets now prevalent in rural Ceara are certainly superior to those in existence during the 1980s. Nevertheless, one 81 These lending terms were current as of September 1998. 92 should consider expanding the Frentes de Emergencia (public work programs). This could be done revenue-neutrally, if necessary, by reducing the R$90 monthly wage, which is relatively high for some of the affected areas. 3.58 In fact, Ceara is the only state in the Northeast to add R$25 to the R$65 per public work vacancy which is provided by the Federal Government. Most other states add R$15, paying wages of R$80. Piaui adds nothing, and pays a R$65 wage. At any of these lower wage rates, self-selection would be improved, and the poorest and most vulnerable might be likelier to participate. At lower wages, and if funds are unconstrained, the public work program could in fact be made into an employment- guarantee scheme, where a post is offered anyone wanting work.52 This would have the advantage of excluding none of the truly desperate, which at the moment, even if in'small numbers, might be slipping through the net due to administrative rationing of Frente de Emerg6ncia vacancies. 3.59 For urban areas, LOAS benefits, as well as the Seguro Desemprego for formal sector workers, provide some protection against shocks. However, given the importance of informal employment (12% of household heads in RMF), informal self-employment (24% of household heads in RMF), and the 'inactive' (23% of household heads in RMF) - as against formal employment (24% of household heads in RMF), one is led to believe that the existing safety net coverage for the (broadly defined) informal sector is inadequate. Our proposal is to do this largely through their children: i.e. by using the Bo3sa-Escola program which, if well designed, in addition to providing both the means and the incentives for children to stay in school and to avoid grade repetition, also provides needed funds to families at the very bottom of the income distribution. Conclusions and Some Tentative Recommendations 3.60 Despite considerable efforts by government and civil society alike, Ceara remains a very poor state. Even at the low 'food-only' poverty line of R$65 per month, almost half of its population is poor. A full three-quarters of the population lives below the more generous 'food-plus' poverty threshold of R$132 per month. However serious the income under-reporting problems discussed in Section 2, Ceara is considerably poorer than most states in Brazil, and Fortaleza than any metropolitan area outside the Northeast. This is reflected in a low life expectancy at birth of 57 years, and in an adult illiteracy rate of 47% (in 1991). On the inequality front, Ceara is substantially less unequal than the Northeast as a whole, with a Gini coefficient just below 50%. 3.61 Ceara's poverty is fundamentally a rural and agricultural phenomenon, and PPV data suggests that this finding is robust to different income reporting criteria. It is also clearly inversely correlated with educational attainment, and a policy focus on expanding access to and permanence in school is clearly appropriate, both for increasing productivity - and hence growth and competitiveness - and for reducing poverty and improving living standards. 82 This was recently suggested to the authorities by Mr. Martin Ravallion, and reported in his Back-to-Office Report. 93 3.62 This paper has considered policy options under three basic headings: building assets for the poor; increasing returns on those assets; and protecting the vulnerable in a shock-prone economy. Below, the main recommendations arising from our brief analysis are summarized. 3.63 Building Assets for the Poor: (d) Evaluate, re-target, and expand Reforma Agraria Solid6ria and the Projeto Sao Jos6, throughout the State. These seem to be working well, but it is as yet unclear how well targeted to the very poor they are. (e) Increase the supply of primary education in rural and urban peripheral areas, focusing on improved quality, so as to raise the opportunity costs of leaving school, and encourage families to maintain their children in school. Subject to the fiscal constraint, but with a high priority therein, increase the provision of secondary education, principally in urban areas, where demand for it has recently picked up considerably, in response to rising demand for these skills in a growing manufacturing and high-quality services industry. Finally, seek to ensure that the vocational training on offer matches the demand for skills, rather than some possibly outdated model from the past. (f These aims in the educational arena could be pursued through a twin strategy. On the supply side, there may be scope for a high-profile drive by local teachers and volunteers - perhaps called "Agentes Comunitarios de Educagcio' - to train and work with teachers in the poorest and most problematic communities, both in rural areas in the Sertfo Central and in pockets of the periphery of Fortaleza. Additionally, a substantial demand-side program, along the lines of Bolsa-Escola, could provide the necessary incentives for children and teenagers to stay in school, once they have got there in the first place. Through highly means-tested subsidies to families whose children stay in school, with additional benefits conditional on 'grade- passing', this program might also provide the main safety net for the families of workers outside formal employment, who can therefore not draw on unemployment insurance when hit by a negative employment or income shock. 3.64 Increasing the Returns on Assets Held by the Poor: (g) Reduce anti-employment biases in the tax system. These are largely of a nationwide nature, but there are measures that a state government could take to alleviate them, reducing the costs of hiring and promoting labor-intensive growth. The policies to achieve this objective are discussed in other background papers to this Report. (h) Reduce transport costs for rural produce to reach important markets, including through ports. This may be of particular importance for fruit agriculture, on which the state has recently placed so much hope. As discussed in other background papers, it is unlikely that this type of agriculture will have an impact on poverty through returns on land. It is, however, perfectly likely that a successful fruits industry may have a 94 substantial effect on the demand for agricultural labor, and hence on rural employment and wages. (i) Reduce bureaucratic fixed costs which are proportionally highest for small informal entrepreneurs. Examples of these are also provided in other background papers. Here, we only make the point that such efficiency measures are also likely to reduce poverty, through increasing the returns to the entrepreneurship and capital of small firms. 3.65 Protecting the Vulnerable in a Shock-Prone Economy (a) In the rural areas, increase the coverage of the Emergency Public Works Programs, whilst possibly reducing the wage rate from R$90. If possible, consider combining a wage reduction with a budget increase, so as to transform the program into an employment guarantee scheme. (b) In the urban areas, rely on a well-managed and highly means-tested Bolsa- Escola- type program to provide additional protection for the vast majority of the urban poor, who hail from the informal sector. 95 4. THE STATE: MANAGING FISCAL STABILITY This chapter is based on a background paper by William Dillinger. 96 State Fiscal Diagnosis, Outlook And Risks Background 4.1 Ceara has the reputation of a financially sound jurisdiction. Recent financial information tends to confirm that image. The state's primary deficit was relatively small in 1995 (1% of net current revenues) although it increased to 10% in 1996 and 16% in 1997. Personnel costs consume only 60% of net current revenues. The stock of debt is small by Brazilian standards (102% of net current revenues), and largely long term and low interest. Over the medium term (1998-2000) there are several issues that need to be addressed if this healthy picture is to be maintained. Table 4.1: Trends in Current Revenues 1995 1996 1997 Receitas correntes 1744 2180 2202 Receita tributaria 985 1227 1302 ICMS 951 1183 1242 Outro tributario 34 44 60 Transferdncias correntes 658 799 844 FPE 567 641 719 IRF 51 53 55 SalArio educa9io 10 15 14 ConvAnios 21 71 41 Outras transferencias 10 20 1S Receita patrimonial (renda de aplica6es) 57 1s 16 Outras receitas correntes 44 136 40 less: transfer to municipios 269 320 348 =receita corrente liquida 1475 1860 1854 Revenues 4.2 Taxes. The state's principal revenue source is a value added tax (ICMS), which is administered by the state government, subject to regulations imposed by the federal senate and by agreement of the council of state finance secretariats. The base of the tax is "operations involving the circulation of merchandise and the provision of transport and communication services." In general, the ICMS is administered on the basis of a tax rate imposed on the gross value of sales, less a credit for ICMS paid by the suppliers of inputs. For some products, where the imposition of the tax at the retail level would be difficult, the retail price is imputed and imposed at the manufacturing stage. Certain services are exempted from the tax by federal law. The exemptions with greatest impact in Ceara are hotels, banks, and the liberal professions. The federal Senate sets the maximum tax rate on interstate transactions (now 12% for states of the Northeast and Center-west and 7% for South and Southeast83. Rates onintrastate sales are set at the discretion of the individual states, subject only to a minimum fixed by the Senate. In Ceara, the rate on intrastate transactions is now 25% for telecommunications, electric energy and fuels, and 17% for most other products and services. 4.3 Over the course of the last five years, the ratio of ICMS to GDP rose with price stabilization in 1994 and peaked in 1996. In 1997, revenues fell in relative terms, and recovered only partially in 1998 (see Table 4.2). 83 For purposes of this legislation, Espirito Santo is considered a northeastern state. 97 Table 4.2: Trends in ICMS and GDP Million 1994 1995 1996 1997 1998 Current Reais . ICMS 508 951 1,184 1,242 1,344 State GDP 7,969 14,003 17,290 19,586 20,809 ICMS/GDP 6.4% 6.8% 6.9% 6.3% 6.5% ISource: Iplance 4.4 The first critical issue for the state is whether the ICMS can be expected to revive. In general, the prospects look good. The fall in ICMS in 1997 was largely due to one-time change in federal policy. That event was the Lei Kandir. The Lei Kandir (L.C. 87/96) went into effect in September of 1996. It granted two exemptions to the ICMS. The first was an exemption on exports. For 1997, Ceara's direct losses due to the export exemption are estimated at R$30.8 million. The export exemption had wider implications. Because the export exemption was granted on the entire value of the product (not merely the value added at the final stage prior to export) exporting firms had ICMS tax credits (representing ICMS paid by suppliers) which could be sold on the secondary market. This further reduced the level of overall tax liabilities. The total value of such credits in 1997 was R$13.7 million. The Lei Kandir's second exemption permitted firms to take a tax credit for purchases of capital equipment. (Formerly, credits against the ICMS could only be taken on inputs incorporated in final output.) This further reduced the tax base by another R$ 47 million. Taken together, total losses due to the Lei Kandir are estimated at R$ 115.1 million. Without the Kandir impact, ICMS revenues would have increased by six percent in real terms. This corresponds to the rate of growth in the economy, and suggests that losses--at least in 1997--were entirely policy-induced. Table 4.3: Losses Arising from Lei Kandir R$ mn % ICMS Desoneragio das exportag6es 44.6 3.6% icms exportag6es 30.8 2.5% Transferencias de credito 13.7 1.1% cr6dito-bens de capita, 47.6 3.8% cr6ditos-energia eletrica 23.0 1.9% Total 115.1 9.0% 4.5 By October 1997, the Lei Kandir's impact on the growth rate of ICMS should have dissipated. ICMS revenues however failed to fully recover. This appears to be due a recession induced by the Government's response to the crisis in Asia. Declines were particularly steep in sectors affected by rising consumer interest rates (receipts from eletrodomesticos and purchases of automobiles both fell 28%.) Overall, receipts from wholesale and retail trade fell 7.6%; from industry, 9% (seeTable 4.4). In May, receipts began to increase. (See chart, below.) Although corresponding data on growth in the economy is not available, the recent upturn suggests that the ICMS may be poised for a recovery. 4.6 If the recent stagnation in ICMS revenues was in fact due to recession, the state can expect a resumption in growth once the economy recovers. The recent experience nevertheless demonstrates the ICMS's vulnerability to changes in federal policy and trends in the economy. (Longer term analysis also demonstrates its vulnerability to inflation. See forthcoming report by Jose Nelson Bessa Maia, of Gabinete do Governador, CE). Prospects for increases in the ICMS will also depend on the 98 sectoral composition of economic growth. The impact of growing tourism will be blunted by the exemption of hotels (diarias) from the ICMS base, for example. Table 4.4: Sectoral Composition of ICMS Receipts 1 st semester 1998 Sector % receipts Real growth 98197* Manufacturing 32 -8.9 Retail and wholesale commerce 32 -7.6 Electdc energy 11 * 48.6 Telecommunications 9 14.7 Fuels 8 -2.9 Transport 2 -14.6 Other 6 Total 100% 0.0 refleds expansion of base and increase in rate 1 st semester 1998/1st semester 1997 4.7 Fiscal impact of industrial incentives. In the short term, the state is also losing significant revenues through tax incentives granted to industrial firms. The impact of industrial incentives is disguised in the accounts. ICMS revenues from industry are reported gross of tax incentives. The incentives are instead reported as an expenditure of the industrial development fund. Comparing these expenditures to gross revenues gives an idea of their impact. 4.8 The largest program, PROVIN, was created in 1979. It provides six years of tax incentive for firms meeting qualifying condition. The incentive consists of a three year grace period on the payment of the state's portion of ICMS taxes--i.e. 75% of the firm's ICMS tax obligation.84 Payment is due at the end of the grace period. During the grace period, the tax obligation is indexed to inflation (variously IPC,IGP and TJLP) and subject to 12% nominal interest. At the end of the period, a percentage of the outstanding amount is forgiven. This varies according to the location of the firm, and can range up to 50%. Levels of forgiveness are typically at the higher end of the range. 4.9 More recently, the state has created two other programs, with the same general terms-a grace period on payment of taxes, subject to indexation and interest charges and eligible for partial forgiveness. The first, PROAPE, is aimed at export firms and grants an exemption of ICMS equal to 10.5% of the value of exports. As the Lei Kandir was enacted shortly after PROAP (and exempted all exports from ICMS), PROAPE is in effect a loan equal to 10.5% of the value of exports, with partial forgiveness. The third program, PDCI, grants an exemption for the import of raw materials not produced in Brazil. 4.10 In cash flow terms, these programs are fairly costly. In 1996, the cost of tax incentives under PROVIN alone totaled R$ 102.2, against receipts of R$25.1 million. In 1997, incentives rose to R$110.6 million, with retornos of R$ 32.7. million. Neither PROAP or PDCI had yet produced any returns.) The net negative cash flow in 1997, was equal to 6.7% of gross ICMS receipts, or 4.5% of net current revenues. Although up to half of the principal will be eventually recovered through repayments, the program will represents a significant cost in cash flow terms as long as it continues. (Note that in 1996, the state securitized the PROVIN tax receivables and sold them for R$103 million. 84 the state is constitutionally required to share 25% of ICMS receipts with municipios. 99 While this increased cash flow in 1996, it has reduced repayments in subsequent years to a trickle. 4.11 Transfers. The other major component of state recurrent revenue is transfers. These are mostly automatic, based on fixed shares of specific taxes. The largest is the Fundo de Participa,co dos Estados. This consists of a fixed share of the federal government's two principal non-social security taxes: the income tax and industrial products tax. As specified in the 1988 Constitution, the federal government is required to transfer 21.5% of the revenues of the two taxes to the states. Of this amount, 85% is distributed to the states of the north, northeast and center-west regions, with the remainder going to the states of the south and southeast. Within each group of states, 95% of the funds are distributed among states on the basis of population and per capita income (with poorer states receiving proportionately more). The remaining five percent is distributed on the basis of geographic area. In the absence of changes under the Reforma Tributaria, this is likely to remain as it is, with Ceara's receipts growing at the rate of receipts of the two federal taxes. Table 4.5: Disbursements and Receipts of Industrial Tax Incentives Million PROVIN PROVIN PROAPE PDCI Total Net Incentives as Current Reais Disbursement Accrued Disbursement Disbursement Disbursement % NCR Receipts 1996 102.2 25.1 0.3 77.4 4.2% 1997 110.6 32.7 4.2 1.1 83.2 4.5% 4.12 The only prospect for growth in transfers lies in the Lei Kandir. In imposing the Lei Kandir, the federal government created a mechanism for compensating states for their tax losses. Under the Lei, if real ICMS revenues in any twelve month period are not at least three percent above their levels during the period July 1995-June 199685, the Federal Government is required to compensate the state for the difference. Because receipts are calculated on the basis of twelve month periods, there was a lag between the time the Lei Kandir began reducing revenues and the time the formula kicked in. In Ceara's case the compensation formula failed to kick in at any time during 1997. While the state has received some Kandir compensation in the first semester of 1998, the amounts have been small. Given the design of the Lei Kandir compensation formula, if Ceara's ICMS taxes begin to grow, compensation payments will fall. This does not appear to be a likely source of future revenue growth. 4.13 Other current revenues. The state's remaining revenues consist largely of interest earned on cash and payments of taxes in arrears. In the late 1980's and early 1990's, interest earnings were a major source of state revenues (contributing up to 30% of the total.) Price stabilization has reduced the opportunities for high returns on the float and the former is no longer a major revenue source. Also included in this category are the repayments of industrial tax incentives. (See discussion below.) Note that the increase in "other current revenues" in 1996 reflects proceeds from the sale of tax receivables, and does not represent a sustainable revenue source. Expenditure Analysis by Economic Category 85 the threshold was increased to 5% in 1997 100 4.14 Personnel expenditures. Personnel is the largest single category of state spending in Ceara. The current level--60% of net current revenue--is still low by Brazilian standards. The wage bill has been contained through a policy of virtually no growth in the number of active staff and tight control over salaries. As shown inTable 4.6, the number of personnel paid out of treasury revenues86 has been falling. It took a big dip in the first semester of 1998, with the closure of four state enterprises, the sale of COELCE and reductions in staff at EMATESE and SEPROCE. The total reduction in staff was 3785. The state has intends to hire a roughly equivalent number of staff, of which 3,500 would be professors; 1000, police and 100, prison guards. Once these are hired, staff levels are prognosticated to stabilize at around 100,000 active staff. 4.15 Salary policy has been tight since a major increase in December of 1994. The December 1994 increase was introduced as an overall adjustment in the salary structure, aimed primarily at decompressing salaries. Increases were given within each grade based on years of service. Since that time, there has been a 25% increase for military police (effective April 1995) and 19% increase for professors (effective, July 1996). The remaining staff have received no increase.87 As cumulative inflation from January 1995 to June 1998 totaled 45%, there has been considerable real erosion in salaries since 1994. The current administration has granted an across the board increase of 4.75% to be effective in August 1998. This will redress a small part of the erosion. Whether salaries among the various grades will then be too low or too high, relative to market conditions, is not clear. (See comparisons in report by 1. Gill, and Brazil CEM.) Table 4.6: Trends in Number of Personnel 6/30/1996 6/30/1997 6/30/1998 Poder executivo No of ativos 101760 99576 *96331 No of inativos 14261 14767 16536 Total 116021 114343 112867 Avg wage 8372 9984 **9666 Outros Poderes No of ativos 5358 No of inativos 1023 Total 119248 *of which 3,304 afastado ** based on May 1998 payroll 4.16 The key personnel issue confronting the state has to do with its pension obligations. Under the Federal Constitution, Ceara is required to concede expensive retirement benefits to its staff. Staff can retire after 35 years of service (five years less for women, and another five years less for teachers of either sex). Retirement benefits are based on 100% of exit salary and are indexed to changes in the salary of the position formerly occupied by the retiree. At present, payments to retirees appear to take a small share of the personnel bill: about 11%. This compares with 33% in the city of Rio de Janeiro and nearly 40% in Rio Grande do Sul. This is ominous. It suggests that retirement spending has not yet reached the equilibrium implicit in the current structure of retirement benefits. Rio and Rio Grande do Sul have reached that equilibrium. In those 86 This includes staff in direct administration and indirect administration, but excludes staff of self-financing state enterprises. 87 Staff do, however, receive an automatic five percent increase in salaries after each five years of active service, and a eligible for merit-based promotions. 101 states, the number of retirees is so large that the death rate of existing retirees offsets the number of new retirees each year. Judging from the Rio and Rio Grande do Sul case, this equilibrium is reached when the number of retirees equals at least half the number of active staff. Ceara is far from these proportions. At present, the number of retirees equals only 17% of active staff. 4.17 To an extent, the problem may be exaggerated due to a weakness in the data. In Ceara, it has traditionally taken up to a decade for staff meeting the length-of service requirement for retirement to actually be declared inativo. In the interim, the staff continue to be registered as ativo, with the special status of an "afastado". This year, the administration is attempting to reduce the processing time to 90 days. To date, this has reduced the number of afastados to 3304. If reclassified as inativos, the proportion of retirees would rise to 21% of the number of ativos, somewhat closer to the equilibrium level but still short of it. 4.18 The state is aware of this problem and has commissioned a study of its pension liabilities. The study has been delayed by data problems (particularly the difficulty of determining the years of service of existing staff) but is expected to produce a report before the end of the calendar year. 4.19 To reduce its pension obligations, the state intends to create a pension fund. This would be capitalized with R$ 400 million from the proceeds of the sale of COELCE. New employees would also be required to contribute a share of their salaries to the fund. Judging from rough calculation, the amount of relief that could be expected from such a fund is limited. If the fund were able to generate a real return of ten percent, this would be sufficient to pay only twenty percent of the state's retirement costs (in 1997). Studies in Rio Grande do Sul suggest that the level of payroll contributions required to fund retirement benefits for new employees may be as high as 50%. While the state should clearly continue to pursue the pension option, it would do well to take full advantage of any reductions in retirement benefits permitted by the proposed Reforma Previdenciaria to the federal Constitution. 4.20 Debt service. Ceara's debt stock is relatively small, cheap and long term. As of December 31, 1997, the overall stock of contractual and bond debt was equal to 102% of net current revenues. The majority of debt consists of rescheduled debt owed to the federal government. This includes foreign debt refinanced by the federal govemment under Law 7976 (1989) and debt to federal financial intermediaries rescheduled under Law 8727 (1993). These bear long term maturities (30 years) and relatively low interest rates (averaging 6.2% in real terms). Also in this category is debt arising from the recent refinancing of the state's bonds, under Law 9496. (Under 9496, the state was allowed to float the R$114 million in bonds currently held in its carteira. The federal government then assumed responsibility for these bonds, in exchange for the state's assuming a R$ 100 million, 30 year loan, at 6% real interest.) All the rescheduled and refinanced debts are subject to a debt service ceiling. If debt service on the loans totals over 11.5% of net current revenues, the state is permitted to defer the excess, capitalizing it into the outstanding stock and servicing it when debt service drops below the 11.5% threshold. At present the state is near that threshold, but has not surpassed it. Table 4.7: Trends in Debt Stock Debt stock as at E094 E095 E096 E097 102 Domestic debt 948 1241 1321 1446 titulos 50 78 100 0 contractual debt 898 1163 1222 1560 7976 na na 641 657 Brady bonds na na 56 64 8727 na na 370 375 9496 114 other domestic na na 155 350 External debt 217 251 336 330 total 1165 1492 1658 1890 as percent RCL 141% 101% 89% 102% 4.21 In addition to its refinanced debt, the state has $306 million in long term (10- 25 year), low interest (5.5%-6.6%) debt owed to theCaixa Economica and the Banco do Nordeste, and R$41 million in slightly shorter term (6-7 year) more expensive (12%) debt owed to BNDES. External borrowing totals R$ 330 million and consists of debt to the IDB and the World Bank. (Until 1997, the state owed another R$90 million to Lloyds Bank of London and the offshore branch of the Banco do Brasil. These debts, on which the state had been in default for several years, were officially pardoned during 1997). Because the terms of its debt are long and the interest rates are low, Ceara's debts constitute a relatively small burden for Ceara. Nominal interest payments in 1997 totaled R$ 120 million. Together with interest charges in the form of indexation, interest payments totaled about twelve percent of net current revenues. Amortization costs, net of the transfer of state bonds to the treasury, totaled about R$ 89 million. The stock of debt is expected to rise in the near future. The state, for example, intends to borrow to finance the costs of privatizing the state bank. (Newspaper estimates put the cost of privatizing BEC at $700 million, although the state anticipates a considerably smaller figure.) To the extent the state borrows to maintain its present level of investment spending, the level of debt is also likely to rise. Table 4.8: Trends in Current and Capital Expenditure Despesas Correntes 1548 1974 2060 Pessoal e encargos sociais 1075 1142 Juros e encargos, divida intema 80 91 101 Juros e encargos da divida externa 15 16 18 Outras despesas correntes 1006 799 plus capitalized interest 200 101 less transfer to municipios 269 320 348 =net current expenditures 1279 1854 1813 Despesas de Capital 408 394 678 investimentos, inv finance; transfer cap excl amort. 313 291 463 amortizaVho divida interna 42 99 208 amortizagio divida externa 53 4 7 =net capital expenditures 408 394 678 4.22 Capital spending. The state has maintained a high level of capital spending over the last several years. As shown in Table 4.8 investment spending has averaged R$ 355 million over the last three years. In 1995 and 1996, much of this--two thirds--was financed out of current savings.88 The contribution of current savings declined in 1997, as receipts from the sale of stock in COELCE became available. 4.23 In 1998, the state will have ample resources from the sale of the remaining shares in COELCE to finance capital spending. Once this is exhausted, the state's ability to maintain its recent level of capital spending is questionable. 88 For purposes of this calculation, interest embedded in indexation is excluded from current expenditures. 103 4.24 In order to provide an estimate of the level of capital spending the state is likely to be able to maintain, a model of the state's fiscal situation was prepared. The model allows the impact of the major determinants of fiscal performance--revenues, personnel spending, debt service, capital spending, new borrowing and asset sales--to be tested simultaneously. The results shown in Table 4.9 assume 3% real growth in revenues, 3% real growth in personnel spending, and no borrowing in 1998 (other than the $350 million required to finance the recapitalization of BEC). The level of borrowing in 1999 and 2000 is set at the level required to maintain the level of debt service debt service below 15% of net current revenues--the traditional ceiling imposed by the federal Senate---assuming a 6% interest rate and 20 years to maturity on new debt. Sale of the remaining shares in BEC is assumed to raise $R 600 million in 1998, net of funds allocated to capitalize the proposed pension fund. Cash flow is forced to zero; i.e., total receipts are required to match total expenditures. Under these assumptions and constraints, the level of capital spending that the state can sustain would equal about ten percent of net current revenues, considerably below scale of capital spending achieved in 1995-1997. Table 4.9: Actual and Projected Fiscal Indicators actual Projected 1995 1996 1997 1998 1999 2000 growth of revenue 7% -6% 3% 3% 3% operac,6es de credit/RCL 7% 6% 8% 13% 5% 5% alienagao de bens/RCL 0% 0% 8%/o 31% 0% 0% current surplus/RCL 13% 11% 8% 7% 6% 7% capital spending/RCL 21% 16% 25% 26% 10% 10% total debt service/RCL*) 13% 11% 18% 12% 14% 13% primary balance/RCL -1% -10% -16% -30% 4% 4% overall balance/RCL na -15% -23% -37% -4% -3% cash flow/RCL -4% -3% -5% 8% 0% 1% *(excl capitalization 4.25 This projection is only as accurate as its assumptions, and there is considerably uncertainty surrounding many of them. Revenues may rise faster than 3% per year. Rising salaries and increasing numbers of retirees could boost the personnel bill by more than 3% per year. It is clear, nevertheless, that the scope for financing a large capital program by borrowing is limited. With debt service already at 12% of revenues (excluding interest capitalized through indexation), debt service already takes a considerable share of the state's resources. Unless the state can identify investments that have an economic rate of return considerably higher than its cost of fundsand are likely to generate a proportionate increase in tax revenues, investment spending may have to be curtailed. Table 4.10: Allocation of expenditure Objects of Major Capital Spending, 1997 Rs Mn DER road construction and maintenance 79.0 Agua, saneamento 49.4 Port construction (PECEM) 39.7 Airport 32.0 Judicial power building program 34.0 School construction 13.3 Note: cost data on from SEPLAN and include expenditures financed own- source revenues of autarchies and foundations. 104 4.26 One way of addressing the state's overall resource constraint is to increase the return on its existing expenditure. Analysis of state expenditure is necessarily limited in a report of this kind. Experience suggests that unless there are conspicuous "white elephant" capital projects or massive subsidies to enterprises that compete with the private sector, expenditure analysis is best done through a careful analysis of individual sectors. 4.27 There do not appear to be egregious examples of white elephants or inappropriate subsidies in Ceara. The state spent R$ 463 million on capital works in 1997. Slightly over half this amount is accounted for by the five activities shownTable 4.10. Subsidies to state enterprises are a relatively small proportion of the 1997 expenditures--R$ 74 million in total. The state is in the process of selling the largest potential claimant on treasury subsidies--the state bank--and has closed the state development company (transferring its industrial park program to the secretariat of industry and commerce). 4.28 One characteristic of the pattern of state expenditure is worth noting, however: the small proportion of spending on what might be considered the state's core functions . As shown in the chart below, basic education accounts for only 14% of state expenditure. Much of this appears to be spent on administrative overhead.89 Only seven percent of total expenditure is devoted to paying the salaries of teachers in the classroom.9" Spending on security is small, compared to the states of the south, although this may be due to the relatively low level of crime in Ceara. Spending on health accounts for eight percent of the total (including SUS financed spending.) Spending on infrastructure--highways, ports and airports--accounted for seven percent of the total net spending (although this proportion may be atypically large, due to the availability of revenues from the sale of shares in COELCE). Together, this core accounts for only one third of expenditure. Given the tendency of governments everywhere to create new programs without extinguishing old ones that have outlived there usefulness, the state government may find it useful to evaluate its overall spending program, with an eye to eliminating extraneous activities and focus more of its spending on its core functions. 4.29 Not reflected in these numbers are significant steps that the State has taken after 1997 to increase the concentration of spending on priority areas, in particular education. The share of education spending has been increasing since 1997, in particular, as the result of the creation of new programs for adult literacy and the creation of FUNDEF, a fund for ensuring minimum spending on basic education using earmarked tax revenues. 89 The chart is based on a breakdown of 1997 expenditures empenhadas by budgetary entity, project and activity. It includes all expenditures financed from the treasury and from the own-source revenues of funds, foundations, and autarchies. It excludes expenditures financed from the own-source revenues of state enterprises. Spending on retired staff is included in the allocation to each budgetary entity. Spending on Constitutionally-mandated transfers to municipios is excluded. 90 To an extent, this may be explained by the important role of municipios in primary education. At present, the state primary schools account for only 36% of the 1,499,570 students enrolled in public primary schools. 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STATISTICAL ANNEX The statistical annex was compiled by Fabio Rolim from the data sources listed for each table. 113 GENERAL Table 1. - Numbers for the State of Ceara GROWTH Table 2. - Ceara: Effective ICMS Tax Rates, 1996 and 1997 Table 3. - Indirect Tax Rates on Hotel Services in the Caribbean Table 4. - Spatial Distribution of Approved Investment Projects Jan-95 / Jun-98 Table 5. - Total Exports, Brazil and Ceara, 1985, 1991-97 Table 6. - Ceara: Export Composition by Product Category, 1985 and 1996 Table 7. - Brazil, Southeast, Norteast by State - Per capita GDP (US$, 1995) Table 8. - Cearense Economy - GDP by the Perspective of the Final Demand Table 9. - Cearense Economy - Geometric Growth Rates (% a.a) Table 10 . - Cearense Economy - Sectoral Composition of GDP and Employment (%) Table 11. - Cearense Economy - Average Labor Productivity Table 12. - Monthly Inflation Rate (%) on the main Northeast Capitals 1992-1997 Table 13. - Ceara - Volume and Share of Public Capital Formation / Direct Investment by Sector Table 14. - Ceara: Annual Value Added Output Growth Rates (%), by Sector Table 15. - Ceara: Annual Employment Growth Rates (%), by Sector Table 16. - Northeast - Industrial Eletricity Consumption - By State (MWh) Table 17. - Indicators of the Economically Active Population Table 18. - The Pecem Port TOURISM Table 19. - Tourism Demand and Indices, 1986-1997 Table 20. - Northeast - Average Hotel Bocking Rate (%) - By State Table 21. - Northeast - Hotel Rooms Taken on Listed Hotels - By State Table 22. - Northeast - Landed Passengers from Domestic Flights - By State Table 23. - Northeast - Landed Passengers from International Flights - By State Table 24. - Northeast - Flow of Tourists - By State AGRICULTURE Table 25. - Land use in 1985 and 1995/96, in ('000) hectares, Ceara. Table 26. - Price Indexes for Major Crops and Livestock Products Table 27. - Change in Cultivated Area and Livestock Figures, for selected products, in Ceara Table 28. - Changes in the production structure (%), Ceara. Table 29. - Number and Area of Farms by Farm Size, 1995/96, Ceara. Table 30. - Evolution of Farm Distribution (Number and Area) by Size, Ceara. Table 31. - Tenancy Distribution (%), in Ceara. Table 32. - Share (%) in value of production by farm size (1995/96), Ceara. Table 33. - Yields of Selected Crops, in kg/ha, and Percent Changes, in Ceara. Table 34. - Percentage of farms with improved agricultural practices or service access Table 35. - Technical Assistance (percentage), by farm size, in Ceara, 1995-1996. Table 36. - Fertilizer Use and Pest Control, in Cear, 1995-1996. Table 37. - Irrigation, percentage figures by farm size, in Ceara, 1995-1996. 114 Table 38. - Harvested irrigated area, by major crops, in Ceara, in 1995-1996. Table 39. - Socioeconomic Profile of Rural Households in Northeastern Brazil. Table 40. - Total Agricultural GDP and Growth Rates, 1990 - 1997, in Ceara Table 41. - Area Harvested by Crop ('000 ha) Table 42. - Livestock figures by product. Table 43. - Ceara exports, selected products - 1995. Table 44. - Real producer prices (in Dec. 1997 R$) Table 45. - Crop price average, Production Value and Shares, Table 46. - Farm Size Distribution by Meso-Region, in hectares Table 47. - Farm Structure: Mini-fundios (MF) by Meso-Region Table 48. - Confronto dos resultados dos censos de 1970, 1975, 1980, 1985 e 1995- 1996 Table 49. - Production Value, Acreage by Product and Farm Size (1995/96). Table 50. - Share in value of production by farm size, and by crop. Table 51. - Crop Yields (kg/ha). Table 52. - Crop Yields by Farm Size, tVha, 1995/96. Table 53. - Laborers by Employment Category and Main Agricultural Activity Table 54. - Labor Productivity by Farm Size Table 55. - Socio-Economic Profile of Rural Households in North-Eastern Brazil. POVERTY Table 56. - Income Distribution by Area. Table 57. POVERTY PROFILE - 1996 - Ceara - Indigence Line Table 58. - POVERTY PROFILE - 1996 - Ceara - Low Poverty Line Table 59. - POVERTY PROFILE - 1996 - Ceara - Metropolitan Core - Indigence Line Table 60. - POVERTY PROFILE - 1996 - Ceara - Metropolitan Core - Low Poverty Line Table 61. - POVERTY PROFILE - 1996 - Ceara - Metropolitan Periphery - Indigence Line Table 62.- POVERTY PROFILE 1996 - Ceara - Metropolitan Periphery - Low Poverty Line Table 63. - POVERTY PROFILE - 1996 - Ceara - Large Urban - Indigence Line Table 64. - POVERTY PROFILE - 1996 - Ceara - Large Urban - Low Poverty Line Table 65. - POVERTY PROFILE - 1996 - Ceara - Medium Urban - Indigence Line Table 66. - POVERTY PROFILE - 1996 - Ceara - Medium Urban - Low Poverty Line Table 67. - POVERTY PROFILE - 1996 - Ceara - Small Urban - Indigence Line Table 68. - POVERTY PROFILE - 1996 - Cearb - Small Urban - Low Poverty Line Table 69. - POVERTY PROFILE - 1996 - Ceara - Rural - Indigence Line Table 70. - POVERTY PROFILE - 1996 - Ceara - Rural - Low Poverty Line EDUCATION Table 71. - Illiteracy Rate (%) and Schools Enrolment (1,000) 1985-1994 Table 72. - Ceara - Evasion and Failure rates (%) - 1996/97 Table 73. - Share of Public and Private Services on Total Education Services (%) HEALTH AND SANITATION Table 74. - Ceara - Basic Sanitation Table 75. - Share of permanent private homes with water facilities as % of total Table 76. - Brazil, Southeast, Norteast by State - Life expectation at Birth (years) Table 77. - Share of Public and Private Services on Total Heath Services (%) 115 Table 78. - Northeast, Distrito Federal and Brazil - Human Development Index FISCAL Table 79. - Ceara - Budget Revenue Compositon (%) Table 80. - Ceara - Expenditure Composition (%) Table 81. - Ceara - Budget performance Table 82. - Ceara - Federal Taxes Collection, 1991-1997 Table 83. - Ceara: Effective ICMS Tax Rates 116 General Figures of Ceara Table 1. - Numbers for the State of Ceara StatelNE StatelBR Area 146348.3 Km2 9.37% 1.71% Population (1,000 hab) 1980 1991 1996 Total 5288.2 6366.7 6,809.80 Urban 2810.3 4,162.10 4,713.30 Rural 2477.9 2,204.60 2,096.50 Geometric Growth Rates % 1980191 1991196 1.70 1.3 Demographic Density (Ha/Km2) Ceara 46.39 Northeast 28.81 Brazil 18.23 Urbanization Rate Ceara 69.21 Northeast 63.00 Brazil 78.98 Main Water Resources Km2 Hundred m3/year Acarau-Coreau 30,500.00 5,270.00 Curu 11,500.00 2,360.00 Fortaleza 14,700.00 2,270.00 Jaguaribe 72,000.00 4,150.00 Main water dams Thousand m3 Or6s 2,100.00 Araras 1,000.00 BanabuiO 1.00 Economic Growth and Production Indicators Table 2. - Ceari: Effective ICMS Tax Rates, 1996 and 1997 Sector ICMS Revenue VA in Current Prices ffective ICMS Tax Rate (%) 1996 (R$ 1997 (R$ 1996 (R$ 1997 (R$ 000) 000) 000) 000) 1996 1997 AGRICULTURE 2153 2021 1211709 1080986 0.18 0.19 Crops 865 842 660853 0.13 Animal Production 1288 1180 550856 0.23 INDUSTRY 471483 487391 4438336 5175799 10.62 9.42 Mining 2070 951 104993 115654 1.97 0.82 Public/ Utilities (Water & Elect.) 91346 99944 349370 395260 26.15 25.29 Construction 4840 7002 750900 974172 0.64 0.72 Manufacturing Industry 373228 379493 3233074 3687932 11.54 10.29 Non-Metalic Minerals 14127 16176 264772 316164 5.34 5.12 Metallurgy 11615 13457 100791 104116 11.52 12.92 Machinery 3519 1631 46029 34462 7.65 4.73 Elect. Machinery & Equipment 5880 8209 22945 25972 25.63 31.61 Transportation Equipment 1192 1278 186919 223593 0.64 0.57 Wood Products 1190 1250 43863 49625 2.71 2.52 Furniture 3836 3947 41474 47864 9.25 8.25 Paper Products 2162 3332 9578 10828 22.58 30.77 Rubber Products 3943 3694 19930 22434 19.79 16.47 Leather 834 762 304096 460682 0.27 0.17 Chemicals 66415 57688 63705 54282 104.25 106.27 Pharmaceuticals Products 5963 7163 33657 43911 17.72 16.31 Perfumery, Soaps, etc. 563 540 27150 35422 2.07 1.52 Plastic Products 9781 9261 65549 70473 14.92 13.14 Textiles 66314 61653 672085 727522 9.87 8.47 Apparel & Footwear 52734 61095 344528 404482 15.31 15.1 Food Products 54766 605525 802594 867950 6.82 6.97 Beverages 65472 65021 102993 101185 63.57 64.26 Tobacco 111 104 2231 2916 4.97 3.56 Editorial, Graphics & Printing 1099 1076 69759 74778 1.58 1.44 Miscellaneous Manufactures 1711 1630 8425 9272 20.3 17.59 SEVICES 1033903 635821 11571509 12639634 8.93 5.03 Commerce 426715 408763 3755544 4093394 11.36 9.99 Transportation 23261 23625 294783 324995 7.89 7.27 Communications 95381 106303 245148 281373 38.91 37.78 Hotel & Food Services 6557 6219 303318 399689 2.16 1.56 Public Administration 55270 89923 1892843 2077674 2.92 4.33 Banks and Financial Institutions 4 4 864488 0 TOTAL 1507539 1125233 17221554 18896419 8.75 5.95 Table 3. - Indirect Tax Rates on Hotel Services in the Caribbean (in %) Hotel Hotel Location rooms services Bahamas 4.0 15.0 Barbados 5.0 10.0 Belize 6.0 10.0 Bermuda 7.3 15.0 British Virgin Islands 7.0 10 0 Cancum, Mexico 10.0 15 0 Cayman Islands 10.0 10 0 Dominica 5.0 10 0 Dominican Republic 13.0 10 0 Haiti 5.0 100 Puerto Rico 7.0 15 0 Santa Lucia 8.0 10 0 St. Marten 5.0 15.0 U.S. Virgin Islands 8.0 15 0 Trinaidad & Tobago 15.0 10.0 Source: Republica Dominicana, Minist6rio de Turismo Table 4. - Spatial Distribution of Approved Investment Projects January 1995 to June 1998 Number of Investment Municipalities firms (R$ million) Direct jobs Sao Gon9alo do Amarante 3.0 841.8 792 Maracanau 47.0 709.5 11714 Horizonte - Pacajus 42.0 195.5 7119 Maranguape 24.0 95.2 3522 Caucaia 77.0 291.8 11223 Fortaleza 25 208.4 5813 Aquiraz 9 202.8 1495 Pacatuba 11 186.6 3869 Eusebio 22 132.1 2086 Crato - Juazeiro do Norte 16 97.2 3181 Quixada 5 63.7 1690 Sobral 8 50 2121 Bardalha 11 29.8 1456 Limoeiro do Norte 2 20 1730 ltapaje 2 11.5 1560 Other municipalities 65 212.3 14810 Source: SICICE Table 5. - Total Exports, Brazil and Ceara, 1985, 1991-97 US$ millions Annual Growth (%) Brazil Ceara 1985 25,639 216 1991 31,636 270 1992 35,861 304 1993 38,783 296 1994 43,558 335 1995 46,506 352 1996 47,747 380 1997 52,986 353 Source: IBGE and IPLANCE Table 6. - Ceara: Export Composition by Product Category, 1985 and 1996 (in %) Product 1985 1996 Basic 68.5 17.0 Semimanufactured 10.4 25.6 Manufactured 19.9 57.4 Total 100.0 100.0 Value (US$ millions) 216.0 380.0 Source: MICTISCE Table 7. - Brazil, Southeast, Norteast by State - Per capita GDP (US$, 1995) 1950-96 Annual Growth (%) 1950 1960 1970 1980 1991 1996 1950-70 1970-96 Brazil 1,223 1,849 2,531 3,257 3,250 3,262 3.7 2.4 Southeast 1,903 2,748 3,237 3,299 3,292 3,332 3.6 2.3 Northeast 492 843 982 1,953 1,946 2,077 3.5 2.9 Maranhgo 274 539 649 1,139 1,794 1,710 4.4 3.8 Piaui 255 356 516 946 923 1,049 3.6 2.8 Ceara 406 638 778 1,570 1,696 1,701 3.3 3.1 R.G. do Norte 561 890 815 1,801 1,637 1,875 1.9 3.3 Parafba 491 1,097 705 1,273 1,195 1,451 1.8 2.8 Pernambuco 706 1,076 1,330 2,222 2,254 2,743 3.2 2.8 Alagoas 512 720 1,009 1,801 1,672 1,850 3.5 2.4 Sergipe 562 809 1,130 1,840 1,766 1,818 3.6 1.8 Bahia 483 961 1,197 2,472 2,529 2,548 4.6 2.9 Source: FGV-lbre (1950-60); IBGE (1970-80); FGV-PEE-EBAP (1996) Table 8. - Cearense Economy - GDP by the Perspective of the Final Demand R$ million - 1996 1970 1980 1986 1996 Consumption 4,434 8,563 10,634 16,780 Investment 1,143 1,968 1,789 2,852 Exports 1,375 2,473 3,058 4,939 Imports 2,983 4,033 3,101 7,379 GDP 3,968 8,971 12,381 17,192 Ratios C/GDP 111.70 95.40 85.90 97.60 I/GDP 28.80 21.90 14.40 16.60 IMP/GDP 75.20 45.00 25.00 42.90 EXPIGDP 34.60 27.60 1.00 28.70 Source: Iplance Table 9. - Cearense Economy - Geometric Growth Rates (% a.a) Agriculture Industry Services Total 1970-1980 3.04 11.97 8.41 8.50 1981-1986 8.03 6.25 3.68 6.45 1987-1997 1.38 5.55 4.30 4.42 1970-1997 1.83 7.27 5.83 5.75 Source: Iplance Table 10. - Cearense Economy - Sectoral Composition of GDP and Employment (%/6) Agriculture Industry Services GDP 1970 15.78 18.57 65.65 1980 9.42 25.44 65.14 1986 8.26 25.12 66.61 1990 9.60 29.50 60.90 1994 10.60 26.20 63.20 1997 5.72 27.39 66.89 Employment 1970 68.42 10.40 21.18 1980 54.25 14.37 31.39 1986 44.03 16.68 39.29 1996 43.18 14.15 42.68 Source: Iplance Table 11. - Cearense Economy - Average Labor Productivity (R$ 1.00 of 1996, GDP per active employee) Agriculture Industry Services Total 1970 614 4,753 8,254 2,663 1980 799 8,153 9,557 4,604 1986 933 7,489 8,431 4,973 1996 954 11,174 9,702 6,133 Source: Iplance Table 12. - Monthly Inflation Rate (%/6) on the main Northeast Capitals 1992-1997 Sao Luis Terezina Fortaleza Natal Joao Pessoa Recife Macei6 Aracaju Salvador 1992 1,538.24 1,286.88 1,274.53 1,103.69 1,578.69 1,021.00 1,361.92 118.29 1,255.80 1993 3,041.61 2,708.94 2,430.47 2,509.17 2,679.04 3,196.18 2,411.14 2,709.73 1994 1,517.65 1,040.09 1,028.08 1,127.96 909.84 1,041.57 1,012.43 995.53 978.83 1995 38.92 26.14 22.01 28.17 34.58 32.80 23.61 13.87 28.19 Jan-96 5.15 1.43 1.79 3.32 2.58 2.32 3.67 2.24 0.92 Feb-96 1.75 0.61 1.01 0.56 (2.58) 1.13 1.67 1.71 0.31 Mar-96 0.60 0.36 0.92 0.42 0.94 0.16 1.16 (0.29) 0.70 Apr-96 1.69 1.17 1.10 0.91 3.96 1.29 1.54 1.41 0.99 May-96 1.47 2.43 1.93 0.88 2.04 0.97 1.81 0.32 0.76 Jun-96 2.80 1.23 0.96 0.81 0.74 0.01 1.18 1.28 1.17 Jul-96 0.78 1.20 0.50 1.48 (0.26) 1.68 1.51 0.35 0.97 Aug-96 0.94 (0.04) 0.49 0.19 (2.12) 0.26 1.30 0.33 0.84 Sep-96 0.78 0.62 (0.08) 0.30 (0.59) 0.22 0.96 0.06 0.06 Oct-96 0.85 1.53 0.73 (0.68) 3.44 0.65 0.06 1.25 0.57 Nov-96 0.58 0.63 0.44 0.86 1.66 0.03 0.49 0.30 0.58 Dec-96 0.91 1.21 0.42 (0.44) 0.76 0.60 (0.13) 0.67 Jan-97 2.96 1.74 1.34 1.71 0.52 0.93 2.12 1.15 0.66 Feb-97 1.80 0.59 0.40 0.71 1.71 0.67 0.81 0.14 0.05 Mar-97 2.18 0.55 0.25 0.22 2.25 0.04 1.24 0.51 0.25 Apr-97 1.11 0.71 0.84 0.82 (0.86) 0.67 0.40 0.55 May-97 0.27 0.95 0.52 0.77 1.54 0.72 0.45 1.77 Jun-97 0.34 1.07 (1.00) 0.20 0.34 0.33 0.93 0.40 Jul-97 0.98 0.10 0.08 (0.10) 0.34 Source: FIPES; FCEPRO; IPLANCE; IDEC; IDEME; FUNDAJ; SEPLAN/AL; SEPLAN/SE; SEI Table 13. - Ceara - Volume and Share of Public Capital Formation /Direct Investment by Sector (R$ 1.00, 1995) 1975 1980 1985 1990 1995 Volume % Volume % Volume % Volume % Volume % Agriculture 8.54E-05 16.44 6.45E-04 9.55 3.11E-02 5.03 2,369 7.75 12,321,863 1.71 Minning 1.71E-04 2.54 1.80E-01 29.05 724 2.37 26,854,964 3.73 Industry 6.91E-06 1.33 7.49E-05 1.11 4.14E-03 0.67 17 0.06 19,083,764 2.65 Eletricity and Water 4.54E-05 8.74 1.04E-03 15.45 7.16E-02 11.58 10,781 35.25 175,638,960 24.42 Construction 4.18E-05 0.62 1.32E-04 0.02 2 0.01 577,318 0.08 Commerce 6.54E-06 1.26 8.OOE-06 0.12 5.53E-05 0.01 3 0.01 449,481 0.06 Transportation & Communications 2.37E-04 45.57 3.03E-03 44.93 1.97E-01 31.82 6,896 22.55 177,396,838 24.66 Financing, Real Estate, and Services 1.38E-05 2.66 3.54E-04 5.25 1.91 E-02 3.08 264 0.86 21,120,050 2.94 Social Services 1.25E-04 24.01 1.38E-03 20.44 1.16E-01 18.73 9,527 31.15 285,886,788 39.74 Total 5.19E-04 100.00 6.75E-03 100.00 6.18E-01 100.00 30,582 100.00 719,330,026 100.00 Source: SUDENE/DPO/IPLUContas Regionais Table 14 - Ceara: Annual Value Added Output Growth Rates (%/l), by Sector Annual Growth Rates (%) * Value Added (R$ Sector 1996) 1970-80 1980-90 1990-96 Agriculture 1,212 3.00 0.80 4.20 Crops 661 (0.60) 1.50 6.80 Animal Production 551 7.20 0.20 1.70 Industry 4,431 12.00 3.50 5.50 Mining 105 23.60 19.30 (2.80) Construction 751 5.20 4.80 (2.70) Electric Energy and Gas 276 15.80 7.80 7.20 Water and Sanitation 73 43.80 14.50 5.60 Manufacturing Industry 3,233 15.40 2.00 8.60 Non-Metalic Minerals 265 20.40 (3.30) 6.50 Basic Metals and Metalworking 101 20.10 2.20 2.60 Transportation Equipment 187 30.80 10.90 17.00 Leather 304 24.20 5.60 41.10 Textiles 672 19.90 10.20 5.70 Apparel & Footwear 345 33.70 8.70 6.70 Food Products 803 13.40 (0.50) 7.20 Machinery and Equipment 46 31.90 (11.10) 16.90 Electric Machinery and Equipment 23 28.50 (0.50) 6.60 Wood Products 44 5.80 (1.90) 12.40 Funiture 42 16.70 (5.70) (2.00) Paper Products 10 17.40 (0.10) 9.40 Rubber Products 20 38.40 (8.00) 20.00 Chemical and Chemical Products 64 (6.20) 4.40 3.30 Phamaceutical Products 34 27.30 (3.20) 19.20 Perfumery, Soaps and Candles 27 15.70 (0.80) 19.20 Plastic Products 66 29.50 4.10 7.40 Beverages 103 15.80 1.20 4.00 Tobacco 2 28.60 (7.50) 2.70 Printing and Graphics 70 12.80 1.90 13.70 Miscellaneous Manufactures 8 16.20 (1.90) 4.10 Services 11,572 8.40 4.30 4.60 Commerce 3,756 5.80 6.80 5.20 Hotel & Food Services 303 14.50 2.70 1.80 Transportation 295 9.20 0.70 6.40 Communication 245 17.80 6.00 16.00 Banks and Financial Institutions 865 12.30 2.30 (5.70) Rental Services ** 2,433 13.00 5.00 3.40 PublicAdministration 1,893 4.90 2.40 11.10 Private Sector Education Services 688 8.30 0.50 9.70 Domestic Services 306 6.20 7.50 5.50 Other Services 789 6.00 3.50 3.30 Total 17,214 8.50 3.80 4.80 * rates computed from value added in constant prices of 1996 ** includes imputed rents from state (national) accounts Source: Estimates based on IPLANCE information Table 15. - Ceari: Annual Employment Growth Rates (°/), by Sector Employment VA/L (R$ Annual Employment Growth (L) curr.) (%) Sector 1996 1996 1970-80 1980-90 1990-96 Agriculture 1,210,315 1,001 0.40 (0.10) 2.50 Crops 684,467 966 (3.30) 0.80 5.60 Animal Production 525,848 1,048 4.60 (0.90) (0.80) Industry 396,513 11,174 6.10 2.60 1.50 Mining 2,301 45,637 0.50 (3.90) 2.80 Construction 150,369 4,994 7.20 1.70 3.50 Electric Energy and Gas 3,563 77,514 4.60 2.80 (6.20) Water and Sanitation 1,489 49,152 33.00 3.90 (2.20) Manufacturing Industry 238,792 13,539 5.50 3.20 0.50 Non-Metalic Minerals 25,022 10,581 5.40 1.80 (2.30) Basic Metals and Metalworking 7,206 13,987 5.70 0.20 (6.70) Transportation Equipment 2,137 87,467 9.40 7.40 (10.20) Leather 7,452 40,806 7.50 5.00 19.50 Textiles 29,735 22,602 3.80 4.10 (0.50) Apparel & Footwear 62,199 5,539 13.90 7.50 3.40 Food Products 54,071 14,843 4.50 1.50 (1.00) Machinery and Equipment 4 11,646 14.40 1.50 (4.40) Electric Machinery and Equipmen 3,243 7,075 10.50 0.20 0,70 Wood Products 2,811 15,603 4.40 1.30 (8.30) Funiture 6,474 6,406 2.60 3.30 0.20 Paper Products 1,230 7,787 8.40 (6.30) 18.00 Rubber Products 676 29,476 16.70 (9.30) 3.60 Chemical and Chemical Products 2,028 31,411 (6.90) (1.70) (0.80) Phamaceutical Products 7,158 4,702 13.20 3.20 26.40 Perfumery, Soaps and Candles 3,152 8,615 4.10 3.40 21.70 Plastic Products 3,684 17,792 19.50 1.70 1.00 Beverages 7,914 13,015 (1.40) 9.60 (1.10) Tobacco 568 3,932 10.70 8.40 (2.60) Printing and Graphics 7,642 9,128 3.20 6.00 1.60 Miscellaneous Manufactures 437 19,273 5.60 (4.20) (13.60) Services 1,196,346 9,672 6.80 5.50 2.30 Commerce 413,548 9,081 5.50 7.10 4.50 Hotel & Food Services 50,680 5,985 13.40 5.90 (1.20) Communication 9,300 26,359 11.50 0.40 8.30 Banks and Financial Institutions 20,466 42,241 11.10 1.90 1.70 Rental Services ** 2,098 1,159,516 13.00 5.00 3.40 Public Administration 142,434 13,289 9.10 3.10 (4.80) Private Sector Education Services 41,068 16,750 4.50 1.80 9.90 Domestic Services 217,729 1,404 6.20 7.50 5.50 Other Services 234,730 3,360 7.30 5.30 2.40 Total 2,803,173 6,141 2.70 2.30 2.20 * rates computed from value added in constant prices of 1996 Source: Estimates based on IMPLANCE information Table 16. - Northeast - Industrial Eletricity Consumption - By State (MWh) 1991 1992 1993 1994 1995 1996 Maranhao 5,807,382 5,897,333 5,878,672 5,911,021 5,936,710 5,959,700 Piaui 86,155 81,830 84,731 91,008 90,054 89,954 Ceara 1,071,763 1,094,294 1,179,569 1,186,170 1,295,013 1,423,130 R. G. do Norte 506,185 502,155 543,254 548,977 609,385 693,860 Paraiba 450,330 411,914 436,671 478,997 526,228 535,877 Pernambuco 1,807,719 1,718,830 1,834,339 1,801,683 1,751,950 1,801,334 Alagoas 1,828,646 1,999,438 1,911,546 1,960,139 1,810,183 1,847,843 Sergipe 664,149 646,136 691,067 692,767 693,844 727,135 Bahia 6,100,580 6,610,279 6,635,252 6,953,973 6,610,585 7,332,703 Northeast 18,322,909 18,962,209 19,195,101 19,624,735 19,323,952 20,411,536 Source: CHESF/DGM/DOME; SUDENER/DPO/IPL/Contas Regionais Table 17. - Indicators of the Economically Active Population 10 years old and above - Ceara 1985 1995 Population at Active Age (1.000 hab) 4160.5 5034.9 Economically Active Population (1.000 hab) 2351.5 3200.7 Occupied Population (1.000 hab) 2300.4 3039.9 EAP Distribution (%) Male 64.84 57.28 Female 35.16 42.72 Activity Rate (%) 56.52 63.57 Unoccupied Rate (%) Total 2.17 5.02 Male 1.99 4.39 Female 2.52 5.87 Occupied Pop. Distribution (%) Agricultural 41 38.51 Non-Agricultural 59 61.49 Occupied Pop. Distribution (%) W/earnings bellow 1 minimun wage. 52.97 38.25 w/earnings rom 1 to 3 minimUn wages 23.7 25.31 w/earnings from 3 to 5 minimun wages 4.63 5.61 Dependents/EAP ratio 1.49 1.1 Table 18. - The Pecem Port Site: 40 Km from Fortaleza Sao Goncalo do Amarante (Distrito de Pecem) Project Characteristics Type: Off-Shore Access Bridge: Length: 2160.0 meters Width: 20.5 meters Pier 1 (raw materials/... products) Loads on Containers and Pallets Plafform: 45 x 350 meters Ships: 65,000 tbp (external side) 125,000 tbp (internal side) Pier 2 (Liquids/Oil derivatives) Platform: 32 x 45 meters Ships: 50,000 tbp 170,000 tbp Artificial Protection Reef Length: 1,770.0 meters Volume: 2.2 millions of cubic meters "Calado" from 15.0 to 16.5 meters Tourism Indicators Table 19. - Tourism Demand and Indices, 1986-1997 Total Tourism No. of commercial flight arrivals passenger demand at airport arrivals at (Arrivals) airport Domestic International Year 1986 668,083 9,895 43 380,795 1987 621,563 10,037 53 349,521 1988 672,046 10,705 75 295,680 1989 716,310 10,698 99 415,094 1990 694,590 10,074 77 439,398 1991 763,702 12,164 97 455,036 1992 649,298 9,910 117 387,893 1993 665,642 10,922 316 431,638 1994 716,098 12,090 294 486,948 1995 761,777 14,006 500 568,596 1996 773,247 14,541 670 595,090 1997 970,000 15,096 690 655,487 Source: SETUR, Sintese do Desempenho Recente do Turismo no Ceara, Fortaleza, Margo 1998 Table 20. - Northeast - Average Hotel Booking Rate (%/o) - By State 1991 1992 1993 1994 1995 1996 Maranhao 42.90 34.20 37.70 41.30 49.50 52.30 Piaui 27.90 25.70 32.30 26.00 CearA 58.10 46.30 53.20 56.60 59.20 56.00 R. G. do Norte 39.00 52.20 57.30 57.50 47.80 Paraiba 60.30 52.20 50.90 52.30 54.50 53.60 Pernambuco 34.60 31.03 35.30 43.90 39.20 43.40 Alagoas 42.70 45.23 52.90 54.10 54.40 51.10 Sergipe 43.70 38.50 42.60 46.40 48.90 52.70 Bahia 44.00 41.60 48.30 51.90 51.90 48.70 Northeast 44.30 39.30 45.00 47.80 51.90 50.70 Source: Empresas de Turismo dos Estados; SUDENE-DPO/IPLUCRG Table 21. - Northeast - Hotel Rooms Taken on Listed Hotels - By State 1991 1992 1993 1994 1995 1996 Maranhao 115,137 103,593 103,085 105,853 145,862 154,391 Piaui 66,591 48,289 60,263 42,604 Ceara 485,770 408,751 460,364 562,282 560,941 579,821 R. G. do Norte 273,087 383,325 466,806 472,374 404,258 Paraiba 150,020 120,887 107,635 123,092 145,572 146,579 Pernambuco 597,439 522,568 443,424 444,738 364,902 1,494,006 Alagoas 271,434 218,724 284,681 318,162 305,924 253,202 Sergipe 183,094 161,021 177,143 151,553 157,350 162,297 Bahia 819,099 876,902 980,916 1,075,339 959,157 Northeast 1,869,485 2,676,019 2,896,822 3,196,006 3,228,264 4,067,693 Source: Empresas de Turismo dos Estados; SUDENE-DPO/IPLJCRG Table 22. - Northeast - Landed Passengers from Domestic Flights - By State 1991 1992 1993 1994 1995 1996 Maranhao 177,436 143,143 136,979 153,496 168,296 183,429 Piaui 93,933 69,085 65,009 70,206 82,084 88,300 Ceara 454,497 373,180 414,409 469,952 546,239 546,434 R. G. do Norte 196,175 171,282 219,731 256,985 296,132 267,922 Paraiba 95,592 75,676 79,308 83,188 92,884 94,737 Pernambuco 732,259 604,843 593,292 622,253 710,665 748,286 Alagoas 227,780 190,445 183,162 187,592 203,631 196,522 Sergipe 131,275 108,788 98,436 101,762 108,916 111,718 Bahia 828,551 664,803 687,655 700,859 865,458 815,053 Northeast 2,937,498 2,401,245 2,477,981 2,646,293 3,074,305 3,080,401 Source: INFRAERO; SUDENE-Contas Regionais Table 23. - Northeast - Landed Passengers from Intemational Flights - By State 1991 1992 1993 1994 1995 1996 Maranhao 361 35 630 792 1,110 Piaul 17 19 Ceark 537 3,914 15,600 16,772 14,461 17,738 R. G. do Norte 634 826 3,121 2,072 1,974 1,064 Paralba 64 263 332 192 1,109 6 Pernambuco 71,033 76,000 82,661 85,468 72,692 78,098 Alagoas 440 11,162 19,206 23,737 10,710 7,278 Sergipe 91 233 14 685 46 2 Bahia 24,169 36,061 52,798 73,249 57,805 53,805 Northeast 97,329 128,494 173,732 202,822 159,608 159,150 Source: INFRAERO; SUDENE-Contas Regionais Table 24. - Northeast - Flow of Tourists - By State 1991 1992 1993 1994 1995 1996 Maranhao 51,757 46,212 51,300 56,092 63,204 65,332 Piaui 70,655 53147 61,265 Ceari 202,151 170,666 174,560 236,076 226,392 220,039 R. G. do Norte 136,364 205,561 247,865 295,269 248,838 Paraiba 56,085 57,770 65,451 78,274 79,448 Pernambuco 325,156 390,164 494,604 658,587 677,965 785,143 Alagoas 147,137 113,897 146,598 143,355 128,712 106,093 Sergipe 74,898 63,712 74,602 70,090 73,726 92,051 Bahia 296,662 379,078 408,787 450,888 489,947 450,794 Northeast 1,168,416 1,409,325 1,675,047 1,928,404 2,033,489 2,047,738 Source: Empresas de Turismo dos Estados; SUDENE-DPO/IPL/CRG Agriculture Indicators Table 25. - Land use in 1985 and 1995/96, in ('000) hectares, Ceara. 1985 1995196 Change (%) Total farm area 11,009 8,964 (18.60) Cultivated Area 4,569 3,281 (28.20) Crops (annual and permanent) 2,376 1,369 (42.40) Improved Pastures 112 197 75.90 Commercial Forests 7 25 257.10 Fallow (em descanso) 808 761 (5.80) Unused productivearea 1,266 929 (26.60) Natural Pastures 3,382 2,435 (28.00) Natural Forests 2,436 2,700 10.80 Unused land 623 548 (12.00) Source: IBGE - Censo Agropecuario, 1995-1996. Table 26. - Price Indexes for Major Crops and Livestock Products, Ceara. Price Index 1990191 1993194 1996/97 Cotton (herbaceo) 100 101.60 107.40 Cotton (arb6reo) 100 99.60 72.80 Rice 100 87.20 70.80 Banana 100 112.20 81.90 Cashew (nut) 100 153.40 51.10 Sugar cane 100 106.50 70.60 Coconut 100 141.60 80.70 Bean 100 99.60 75.00 Cassava 100 148.20 87.00 Maize 100 106.90 70.90 Crops, total 100 115.10 75.60 Beef 100 104.30 77.00 Milk 100 83.00 75.50 Sheep 100 104.80 88.10 Goats 100 60.90 54.50 Pork 100 94.60 72.20 Eggs 100 100.00 61.30 Livestock, total 100 92.80 74.30 Tabulation: World Bank Mission. Source: EMATERCE (adjustment of inflation by FGV) Table 27. - Change in Cultivated Area and Livestock Figures, for selected products, in Ceari. 1985 1985 1986 1994 1995 1995/96 Change (%) Change (%) (Censo) (PAM/PPM) (PAM/PPM) (PAM/PPM) (PAM/PPM) (Censo) (Censo) (PAM/PPM) (A) (B) shares (%) Cotton (HerbAceo) 16.90 14.80 14.90 5.30 4.20 0.60 -97.90 -66.80 Cotton (Arb6reo) 17.00 21.70 17.50 3.30 3.20 0.70 -97.60 -82.80 Rice 3.30 1.80 2.60 3.50 3.70 4.00 -29.70 66.80 Banana 1.00 1.40 1.40 1.70 1.90 2.70 60.40 29.70 Coffee ..... 0.70 0.50 0.40 0.40 -28.70 Cashew (nut) 7.30 10.50 9.60 14.30 14.50 21.30 71.80 48.90 Sugarcane 1.70 2.20 2.50 1 90 1.90 1.60 A46.20 -15.9 Coconut 0.30 1.00 1.00 1.70 1.70 1.60 250.00 78.30 Bean 20.50 18.10 21.00 32.10 31.50 28.40 -18.60 67.70 Cassava 4.30 4.60 5.30 4.10 5.70 3.20 -55.80 1.10 Maize 27.70 21.40 21.90 30.80 30.60 35.80 -24.10 46.70 Other Fruits .... 0.30 0.30 0.40 0.40 ..... ..... 43.60 Crops, total 100.00 100.00 100.00 100.00 100.00 100.00 -41.30 3.70 number of heads Beef 2,475 2,500 2,605 2,186 2,266 2,382 -3.80 -12.80 Sheep 1,635 1,259 1,337 1,333 1,369 1,606 -1.80 4.10 Goats 987 949 1,029 1,080 1,116 796 -19.40 11.10 Pork 1,245 1,245 1,291 1,201 1,211 1,047 -15.90 -4.90 Poultry 17,728 18,087 20,033 19,681 18,718 20,690 16.70 0.70 Tabulation: World Bank Mission. Note: Column (B) reflects the percent change in average harvested area from 1994-95 with respect to 1985-86. Sources: IBGE - Censo Agropecuario 1995-1996; PAM - Pesquisa Agricola Municipal; PPM - Pesquisa Pecuaria Municipal. Table 28. - Changes in the production structure (°/), Ceara. Share of Total Share of Total Agric.GDP Agric.GDP (1990+1991) (1996+1997) Agr. GDP Crop & LS Agr. GDP Crop & LS Cotton (Herbaceo) 0.90 1.30 0.20 0.20 Cotton (Arb6reo) 1.30 1.90 0.90 1.30 Rice 2.90 4.10 3.80 5.40 Banana 1.60 2.30 1.50 2.20 Coffee 0.70 1.00 0.50 0.80 Cashew (nut) 1.70 2.40 1.60 2.20 Sugar cane 4.40 6.20 3.10 4.40 Coconut 2.60 3.70 2.60 3.70 Bean 5.20 7.40 6.90 9.90 Cassava 3.90 5.60 3.30 4.80 Maize 3.00 4.30 4.70 6.80 Other Fruits 1.10 1.60 1.90 2.70 Other Products 2.10 2.90 2.00 2.80 Crops, total 31.40 44.60 33.00 47.30 Beef 3.50 5.00 6.40 9.20 Milk 9.40 13.40 6.70 9.60 Sheep 0.60 0.80 0.60 0.80 Goats 0.60 0.90 0.60 0.80 Pork 1.10 1.50 1.00 1.50 Poultry 9.50 13.50 12.60 18.00 Eggs 4.80 6.90 3.50 5.00 Pescado 9.40 13.40 5.40 7.80 Livestock, total 39.00 55.40 36.80 52.70 Crops and Livestock, total 70.40 100.00 69.90 100.00 Extrativa veg., Agroindustry 6.90 5.50 Agropecuaria, total 77.30 75.40 Services (autonomous + auxiliaries) 22.70 24.60 Agriculture Total 100.00 100.00 Fruits: Avocado, Pineapple, Cashew (fruit), Oranges, Lime, Papaya, Mango, Passion fruit, Watermelon, Melon, Tangerine, and Grape. Notes: (1) Cotton varieties: herbaceo (annual) and arb6reo (shrub). Tabulation: World Bank Mission. Source: IPLANCE Table 29. - Number and Area of Farms by Farn Size, 1995/96, Ceara. Area Number Avg. farm Farm size (ha) '000 ha '000 size ha <10 627.0 245.0 2.6 < 2 376.0 206.0 1.8 < 5 117.0 121.0 1.0 10 - 100 2,438.0 76.0 32.1 100- 1000 4,123.0 17.0 242.5 >1000 1,730.0 0.8 2,162.5 Total 8,918.0 338.8 26.3 Source: IBGE - Censo Agropecuirio 1995-1996 Table 30. - Evolution of Farm Distribution (Number and Area) by Size, Ceara. Number of Area Farm size (ha) 1970 1985 1995 1970 1985 1995 <10 49.0 63.3 72.3 3.9 6.2 7.0 < 2 23.1 20.7 49.4 0.2 0.7 1.3 <5 32.4 47.8 60.8 1.6 3.1 4.2 10- 100 41.5 30.0 22.5 27.5 28.4 27.7 100 - 1000 9.0 6.4 5.0 44.3 45.4 46.0 1000 - 10 000 0.5 0.3 0.2 20.7 19.0 17.5 >10,000 - - - 3.6 2.0 1.8 Total 100.0 100.0 100.0 100.0 101.0 100.0 Tabulation: World Bank Mission. Note: Categories <2 and <5 cannot be added, because they are also part of the category immediately above. Source: IBGE - Censo Agropecuario 1995-1996. Table 31. - Tenancy Distribution (%), in Ceara. Percentage of farms Area (%) 1970 1985 1995 1970 1985 1995 Owner 60.2 50.3 46.5 63.5 67.4 63.8 Tenant 19.4 29.5 27.2 6.3 5.7 4.4 Ocupante 14.9 16.9 22.4 6.9 5.4 6.4 Manager 5.5 3.3 3.9 23.3 21.5 25.4 Total 100 100 100 100 100 100 Tabulation: World Bank Mission. Source: IBGE- Censo Agropecuirio 1995-1996. Table 32. - Share (%) in value of production by farm size (1995/96), Ceara. Farm size <10 10-100 100 - 1000 > 1000 All farms Cotton 0.6 1.0 1.5 0.6 0.9 Rice 11.3 6.5 4.4 0.8 7.8 Banana 10.8 17.6 13.6 3.0 13.0 Cashew (nut) 4.3 10.4 14.1 39.3 10.3 Sugar cane 5.4 10.7 17.2 15.8 9.9 Coconut 3.6 3.8 8.4 19.7 5.6 Bean 23.6 17.1 12.8 4.4 18.3 Cassava 7.8 6.5 5.6 5.2 6.8 Maize 24.9 19.4 20.0 10.8 21.3 Tomatoes 7.7 7.0 2.5 0.6 6.1 Crops, total 100.0 100.0 100.0 100.0 100.0 Beef 16.2 17.7 22.6 37.1 20.1 Milk 26.3 35.7 38.0 47.7 34.8 Sheep 1.6 1.9 2.1 2.0 1.9 Goats 1.4 0.9 0.9 1.1 1.0 Pork 9.1 4.2 2.3 1.9 4.7 Poultry 30.9 25.1 16.0 9.9 22.7 Eggs 14.4 14.5 18.1 0.3 14.8 Livestock, total 100.0 100.0 100.0 100.0 100.0 Tabulation: World Bank Mission. Source: IBGE- Censo Agropecuario 1995-1996. Table 33. - Yields of Selected Crops, in kg/ha, and Percent Changes, in Ceari. 1985 1985 1986 1994 1995 1995/96 1997 Change (%) Change (%) Change (%) (Censo) (PAM) (PAM) (PAM) (PAM) (Censo) (LSPA) (Censo) (PAM) (LSPA) Cotton (herb.) 327 374 195 511 680 687 896 110.0 109.0 51.0 Cotton (arb.) 194 146 74 133 175 87 117 (55.0) 40.0 (24.0) Rice 1,399 2,407 2,489 2,432 2,679 2,145 2,758 53.0 4.0 8.0 Banana (1) 752 1,436 925 814 807 778 721 3.0 (31.0) (11.0) Cashew (nut) 404 328 120 210 243 88 109 (78.0) 1.0 (52.0) Sugar cane 34,398 42,055 42,216 45,337 46,925 49,381 47,695 44.0 9.0 3.0 Coconut (2) 5,336 5,016 3,567 3,569 3,550 3,548 3,312 (34.0) (17-0) (7.0) Bean 192 207 228 363 375 320 290 67.0 69.0 (21.0) Cassava 3,534 8,004 8,927 7,869 7,740 6,415 7,630 82.0 (8.0) (2.0) Maize 500 374 537 690 730 790 571 58.0 56.0 (20.0) Pineapple (2) .... 4,252 4,593 6,556 7,444 .... 8,333 .... 58.0 19.0 Papaya (2) .... 20,140 18,981 23,418 20,735 .... .... 13.0 .... Mango (2) .... 54,450 50,717 48,211 42,496 .... .... (14.0) .... Passion fruit (2) .... .... .... 118,377 118,129 .... .... - Watermelon (2) .... 261 244 1,181 1,503 .... .... 431.0 .... Melon (2) .... .... .... 17,775 17,370 .... .... 111.0 .... Grape .... 2,250 2,250 9,275 24,583 .... .... 652.0 .... Tabulation: World Bank Mission. Note: (1) in cachos/ha, (2) in fruits/ha. Sources: IBGE - Censo Agropecuario 1995-1996; PAM - Pesquisa Agricola Municipal; LSPA - Levantamento Sistematico da ProdugAo Agricola. Table 34. - Percentage of farms with improved agricultural practices or service access, by meso-region, in Ceara. Irrigation Technical Mineral Crop Soil con- Number of assistance fertilizer protection servation farms Noroeste 6.0 2.0 14.7 43.0 7.9 83,305 Norte 6.6 2.9 14.8 36.2 16.0 56,883 Fortaleza 12.7 5.3 28.7 40.9 3.6 10,293 Jaguaribe 21.9 8.4 20.2 77.5 9.8 31,861 Centro-sul 17.3 6.2 19.1 70.7 38.8 34,492 Sul 6.2 3.5 5.6 49.8 26.3 48,880 Sert6es 4.1 3.2 4.1 67.4 47.1 74,488 Total 8.5 3.8 12.5 54.2 23.7 340,202 Source: IBGE - Censo Agropecuario 1995/96 Table 35. - Technical Assistance (percentage), by farm size, in Ceara, 1995-1996. Farms with Source of TA (for farms with TA) TA for Farm size Crop (ha) TA Public Private Other vs. LS <10 2.4 44.5 29.9 25.7 78.4 <5 2 49.1 30.6 19.7 76.9 <2 1.3 58.3 31.8 8.3 72.3 10- 100 6 47.9 37.8 15.5 70.9 100 - 1000 11.2 29.6 55.3 17.6 54.7 > 1000 33.4 19.2 67.9 15.7 52.6 Total 3.8 42.9 37.4 20.6 71.6 Source: IBGE - Censo Agropecuario 1995196 Table 36. - Fertilizer Use and Pest Control, in Ceara, 1995-1996. Farm with fertilizer Farms w. pest/disease Farm size applications control Ha Chemical Organic Livestock Crops <10 6.4 7.4 17 37.3 < 5 5.8 6.6 13.9 36 < 2 4.8 5.5 9.6 32.5 10- 100 7.2 11.7 56.7 46.3 100-1000 7.1 18.2 82.1 48.7 > 1 000 13.8 35 87.7 50.1 Total 6.7 9 29.3 39.3 Tabulation: World Bank Mission. Source: IBGE - Censo Agropecuario 1995196 Table 37. - Irrigation, percentage figures by farm size, in Ceara, 1995-1996. Farms with Irrigated Irrigation area of all area by Farm size (ha) irrigation farm land farm size <10 6.9 4.1 23.8 * 5 6.1 3.8 13.2 <2 5.1 3 3.3 10-100 11.4 1.3 30.1 100-1000 18.8 0.8 30.4 > 10,000 37.4 1 13.6 Total 85.7 14 97.9 Source: IBGE - Censo Agropecuario 1995/96 Table 38. - Harvested irrigated area, by major crops, in Ceara, in 1995-1996. Harvested irrigated Proportion IrrYields (1) (t/ha) Crops area (ha) Harvested irrHarvested arlrrig. No Irrig. Cotton 455 0.7 5.5 1.5 0.6 Rice 11,667 18.4 22.4 4.2 1.4 Banana 5,466 8.6 15.3 0.9 0.7 Cashew(2) 1,261 2 0.3 0.4 0.3 Sugar cane 10,813 17.1 51.9 67.7 45.1 Coconut 5,435 8.6 26.3 7.7 3.1 Coffee 251 0.4 3.8 0.5 0.4 Beans 15,470 24.4 4.1 0.8 0.3 Mandioca 456 0.7 1.1 6.6 6.2 Maize 9,422 14.9 2 1.1 0.8 Oranges 425 0.7 28 41.8 35.5 Tomatoes 2,166 3.4 89.7 30.7 24.3 Total main crops 63,287 100 Tabulation: World Bank Mission. (1) Banana: '000 cachos/ha; Cashew, Coconut, Orange: fruits ('000)/ha (2) Figures for area consider cashew (nuts) and cashew (fruits). Source: IBGE- Censo Agropecuirio 1995-1996. Table 39. - Socioeconomic Profile of Rural Households in Northeastern Brazil. All HH LO Non-LO Income quintiles Low 2 3 4 high HH- size 4.6 4.8 4.4 5.9 4.9 4.3 3.8 3.1 Female head of HH % 16.1 12.3 18.9 8.2 13.1 8.7 23.3 31.6 Age of HH-head yrs 46.5 52.6 42 46.4 44.6 45.4 49 47.4 Homes with electricity % 53.3 47.2 57.8 40.4 51.5 62 60.5 60.2 Real HH-income (mean) R$ 1252 931 1487 330 606 896 1392 5723 Real HH-income (median) R$ 710 572 811 292 561 854 1154 2724 Real per-cap. income (mean) R$ 356 267 421 55 123 211 361 2290 Real per-cap. income (median) R$ 178 143 204 56 122 207 357 919 Per-cap. HH-expenditures (median) R$ 110 101 116 99 96 95 122 169 HH below high poverty line % 55.6 63.6 49.8 100 100 48.9 0 0 HH below indigence line % 17.1 24.6 11.6 61 0 0 0 0 No. of HH 521 220 301 146 99 92 86 98 Real per-cap. income (median) R$ 178 143 204 56 122 207 357 919 Average HH income shares Agricultural income % 27 30 24 16 23 29 32 37 Home food production % 16 19 13 18 17 18 15 8 Wages and benefits, incl. agr. labor % 29 23 34 26 31 28 31 32 Subsidies and pensions % 13 15 11 20 14 11 8 6 Non-farm business income % 2 1 3 -1 2 2 4 7 Remittances % 3 2 3 3 3 3 1 2 Housing (imputed) % 8 4 11 18 9 8 7 6 Other, incl. rental income % 2 1 2 1 1 1 2 3 Note: Per-capita income was calculated using the total number of persons per HH, not adjusted for adult equivalent. Source: Pesquisa sobre Padrao de Vida, 1997. Table 40. - Total Agricultural GDP and Growth Rates, 1990 - 1997, in Ceara 1990 1991 1992 1993 1994 1995 1996 1997 Growth Kate (Million Reais) GDP 911 1,174 993 772 1,206 1,185 1,184 1,026 1.71% GDP Trend (leastsquare regression) 979 1,001 1,023 1,045 1,067 1,089 1,112 1,134 2.12% GDP growth (avg. 1990/91 - 1996/97) 1,043 1,051 1,060 1,069 1,078 1,087 1,096 1,105 0.84% Source: IPLANCE/IBGE * 1995-1997 data are preliminary. Table 41. - Area Harvested by Crop ('000 ha) 1985 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1995/96 1997 1998 (Censo) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (Censo) (LSPA) (LSPA) Cotton herb. 377 306 350 34 172 159 78 73 71 18 122 96 8 21 21 Cotton arb. 380 450 412 268 286 230 199 154 137 76 76 73 9 14 6 Rice 74 37 62 51 70 66 62 77 65 44 80 85 52 65 48 Banana 22 29 33 36 34 35 37 40 41 38 39 42 36 44 45 Coffee N.A. 15 11 11 11 11 10 9 9 9 9 9 N.A. 9 9 Cashew (nut) 163 217 226 232 262 263 267 296 324 327 327 333 280 348 332 Sugarcane 39 45 58 61 65 64 63 66 64 46 42 44 21 46 42 Coconut 6 21 23 24 32 32 35 38 43 38 39 40 21 42 31 Bean 458 375 494 345 623 541 381 641 566 204 736 722 373 513 363 Cassava 95 96 126 118 109 112 125 138 139 126 93 130 42 112 80 Maize 619 444 515 287 606 513 346 597 495 166 705 701 470 466 356 Avocado 1 1 1 1 1 1 1 1 1 1 0 0 0 Pinapple 0 0 0 0 0 0 0 0 0 0 0 0 0 Peanut 1 1 1 1 1 1 1 1 1 1 1 1 1 Sweet potato 1 1 1 1 1 1 1 1 1 1 1 0 0 Fava 9 11 7 6 4 2 2 2 1 2 0 0 0 Tobacco 0 0 0 0 0 0 0 0 0 0 0 0 0 Oranges 2 2 2 2 2 1 2 1 1 1 1 1 1 Lime 0 0 1 1 0 1 1 1 0 0 0 0 0 Papaya 0 0 0 0 0 0 0 1 1 1 1 0 0 Mamona 16 19 10 17 14 11 14 9 1 4 4 2 1 Mango 3 2 2 2 2 2 2 2 2 3 2 0 0 Passion fruit 1 1 1 2 2 2 0 0 Watermelon 1 1 1 1 1 1 1 1 0 1 1 0 0 Melon 0 0 0 0 0 1 1 1 2 2 2 0 0 Black Pepper 0 0 0 0 0 0 0 0 0 0 0 0 0 Tomato 1 2 1 2 2 2 2 2 2 2 2 2 2 Grape 0 0 0 0 0 0 0 0 0 0 0 0 0 Total 2,234 2,069 2,348 1,494 2,301 2,056 1,628 2,158 1,978 1,107 2,288 2,294 1,312 1,682 1,331 Note: PAM - Producao Agricola Municipal; 1997 and 1998 figures were from LSPA - Levantamento Sistematico da producao Agricola - September. Source: IBGE - Censos Agropecuarios 1985 and 1996; IBGE - LSPA Table 42. - Livestock figures by product. 1985 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1995/96 (Censo) (PPM) (PPM) (PPM) (PPM) (PPM) (PPM) (PPM) (PPM) (PPM) (PPM) (PPM) (Censo) Cattle (000 heads) 2,475 2,500 2,605 2,574 2,625 2,674 2,621 2,625 2,602 2,098 2,186 2,266 2,382 Milk (million 1) ... 208 221 222 225 225 294 299 304 243 268 292 ... Sheep (000 heads) 1,635 1,259 1,337 1,350 1,420 1,451 1,470 1,495 1,495 1,274 1,333 1,369 1,606 Goats (000 heads) 987 949 1,029 1,032 1,066 1,101 1,116 1,145 1,161 1,034 1,080 1,116 796 Pork (000 heads) 1,245 1,245 1,291 1,281 1,335 1,356 1,373 1,403 1,425 1,195 1,201 1,211 1,047 Poultry (000 heads) 17,728 18,087 20,033 22,568 23,802 22,981 23,028 24,820 24,454 20,781 19,681 18,718 20,690 Eggs (million dozen) ... 94 104 113 120 104 118 129 128 119 112 102 ... Source: IBGE - Censo Agropecuario 1995-11996; PPM - Pesquisa Pecuaria Municipal. Table 43. - Ceara exports, selected products - 1995. Value (US$ Weight (kg) Avg. Price Products FOB) (US$/kg) Cashew nuts 129,926,894 28,295,191 4.59 Lobster 50,505,719 2,187,586 23.09 Cera Carnauba 38,561,219 6,124,345 6.3 Shrimp 4,687,911 501,012 9.36 Liquid from cashew nuts 2,983,765 19,556,846 0.15 Fish 1,222,647 129,533 9.44 Melons 223,764 521,988 0.43 subtotal 228,111,919 57,316,501 3.98 Other Products 124,019,316 79,664,755 1.56 Total 352,131,235 136,981,256 2.57 Source: Iplance, 1997, Atlas do Ceara, p.48 Table 44. - Real producer prices (in Dec. 1997 R$) Unit 1990 1991 1992 1993 1994 1995 1996 1997 Cotton (herb.) 15 kg 8.42 9.37 8.9 9.61 8.46 8.43 9.2 9.92 Cotton(arb.) 15kg 12.62 11.75 11.56 11.56 12.72 8.04 8.63 9.1 Rice 60 kg 23.85 24.54 24.95 24.9 17.3 14.28 15.5 18.77 Banana 1000 fr 31.96 21.27 24.46 27.4 32.31 26.48 22.64 20.96 Cashew (nut) kg 0.82 0.94 1.24 1.86 0.84 0.47 0.42 0.48 Sugar cane ton 26.98 27.63 35.57 28.26 29.89 18.13 19 19.55 Coconut 100 fr 21.21 43.14 26.75 27.69 63.42 24.05 24.37 27.59 Bean 60 kg 68.49 50.83 55.98 68.49 50.3 44.75 47.92 41.58 Cassava 50 kg 13.25 20.07 37.86 28.88 20.31 8.13 13.17 15.81 Maize 60 kg 19.77 13.16 14.17 22.64 12.56 10.09 12.66 10.7 Beef Cattle kghvivo 1.5 1.27 1.19 1.28 1.61 1.35 1.12 1.02 Milk Liter 0.59 0.46 0.43 0.45 0.42 0.41 0.41 0.39 Sheep kg/vivo 1.34 1.18 0.99 1.12 1.52 1.36 1.17 1.05 Goat kg/vivo 2.16 1.88 1.02 1.05 1.4 1.33 1.13 1.07 Pork kg/vivo 1.99 1.72 1.45 1.61 1.91 1.6 1.18 1.09 Passion Fruit kg 0.64 0.6 0.34 0.41 0.74 0.51 0.23 0.33 Orange 1000 fr 48.35 42.13 34.98 32.72 103.33 136.89 69.31 83.94 Tomatoes kg 0.53 0.41 0.38 0.68 0.49 0.42 0.32 0.34 Note: Producer prices were inflated by IGP-DI/FGV. Source: EMATERCE Table 45. - Crop price average, Production Value and Shares, and Price Indexes for Major Crops and Livestock Products (1990/91, 1993/94 and 1996/97). Crop Price (av.) Weights Price Index 1990/91 1993/94 1996/97 P.V. P.V. 1990/91 1993194 1996/97 share Cofton (herbaceo) 8.9 9.04 9.56 5,134 2.1 100 101.6 107.4 Cofton (arboreo) 12.19 12.14 8.87 9,562 3.9 100 99.6 72.8 Rice 24.2 21.1 17.14 31,301 12.8 100 87.2 70.8 Banana 26.62 29.86 21.8 16,037 6.6 100 112.2 81.9 Cashew (nut) 0.88 1.35 0.45 12,599 5.2 100 153.4 51.1 Sugar cane 27.31 29.08 19.28 39,871 16.3 100 106.5 70.6 Coconut 32.18 45.56 25.98 27,309 11.2 100 141.6 80.7 Bean 59.66 59.4 44.75 42,986 17.6 100 99.6 75 Mandioca 16.66 24.6 14.49 34,734 14.2 100 148.2 87 Maize 16.47 17.6 11.68 24,767 10.1 100 106.9 70.9 Crops, total 244,300 100 100 115.1 75.6 Beef 1.39 1.45 1.07 50,764 25.5 100 104.3 77 Milk 0.53 0.44 0.4 83,028 41.7 100 83 75.5 Sheep 1.26 1.32 1.11 6,101 3.1 100 104.8 88.1 Goats 2.02 1.23 1.1 6,246 3.1 100 60.9 54.5 Pork 1.86 1.76 1.14 10,404 5.2 100 94.6 72.2 Poultry ... ... ... ... ... ... Eggs 0.09 0.09 0.07 42,764 21.5 100 100 61.3 Pesca Livestock, total 199,307 100 100 92.8 74.3 Table 46. - Farm Size Distributfon by Meso-Region, in hectares Farm size Meso-region <10 10 -100 100 - 200 200 - 500 > 500 Total Noroeste 65,009 14,901 1,634 1,058 575 83,177 Norte 42,271 11,623 1,189 721 373 56,177 Fortaleza 8,485 1,382 219 135 65 10,286 Jaguaribe 20,487 9,133 1,058 715 389 31,782 Centro-sul 26,457 6,888 9,472 5,711 2,523 51,051 Sul 37,574 9,737 953 465 132 48,861 Sertoes 45,029 22,535 3,696 2,295 895 74,450 Total 245,312 76,199 18,221 11,100 4,952 355,784 Source: IBGE - Censo Agropecuario 1995-1996. Table 47. - Farm Structure: Mini-fundios (MF) by Meso-Region Number MF in Ceara MF in farms by Meso-region MFs by region (%) Meso-region Noroeste 65,009 26.5 78 Norte 42,271 17.2 75 Fortaleza 8,485 3.5 82 Jaguaribe 20,487 8.4 64 Centro-sul 26,457 10.8 52 Sul 37,574 15.3 77 Sertoes 45,029 18.4 60 Total 245,312 100 Source: IBGE - Censo Agropecuario 1995-1996. Table 48. - Confronto dos resultados dos censos de 1970, 1975, 1980, 1985 e 1995-1996 Condicao do produtor, utilizacao das terras, pessoal ocupado, tratores e efetivos de bovinos, suinos e aves 1970 1975 1980 1985 1995-1996 Estabelecimentos 245 432 251 650 245 878 324 278 339 602 Condi,ao do produtor Proprietario 158 555 159 068 173 688 172 233 168 487 Arrendatario 21 394 2:3 395 26 104 26 005 19 379 Parceiro 27 766 26 272 17 685 70 615 74 428 Ocupante 37 717 42 915 28 401 55 425 77 308 Utilizacao das terras (ha) Areatotal(ha) 12104811 10991 580 11 743270 11 009164 8963842 Lavoura permanente 1 338 799 1 226 517 1 530 800 969 939 476 264 Lavoura temporaria 1 020 644 913 608 1 376 870 1 405 726 892 595 Lavoura em descanso - 99 575 261 513 808 047 760 675 Pastagem natural 3 970 805 3 52 803 3 908 918 3 381 575 2 434 673 Pastagem plantadas 73 007 80645 126 667 111 917 197 448 Matas naturais 3 228 567 2 564 545 3 308 448 2 436 057 2 700 245 Matas plantadas 17 120 2 768 1 514 6 629 24 626 Produtivas nao utilizadas 1 732 859 1 926 553 588 241 1 266 342 928 994 Pessoal Ocupado 1 021 712 999 721 1 069 258 1 271 800 1170 724 Homens 762 731 661 983 799 541 894 582 799 580 Mulheres 258 981 337738 269 717 377218 371 144 Tratores 734 1 419 3 881 4 198 4 528 Efetivo da pecuaria Bovinos 1713110 1949230 2353890 2475423 2382474 Suinos 649 050 1 20C 848 832 598 1 245 467 1 047 451 Aves(milcabecas) 4947 8 137 11 245 17728 20690 Nota: Os dados ate 1985 referem-se a 31.12 , no censo de 1995-1996 os dados referentes a nCimero de estabelecimentos, area total, utilizacao das terras, pessoal ocupado e tratores, referem-se a 31.12.1995 e os efetivos da pecuaria a 31.07.1996. Table 49. - Production Value, Acreage by Product and Farm Size (1995/96). Production Value Acreage Farm size <10 10-100 100 - 1000 > 1000 Total <10 10-100 100-1000 > 1000 ('000 reais) (hectare) Cotton 834 1,029 821 112 2,796 2,635 3,388 1,977 8,000 Rice 15,011 6,654 2,417 155 24,237 31,326 15,119 5,133 51,578 Banana 14,254 18,014 7,501 602 40,371 11,189 17,565 6,792 35,546 Cashew (nut) 5,649 10,652 7,745 7,913 31,959 37,644 92,190 70,949 200,783 Sugar cane 7,108 10,910 9,444 3,186 30,648 3,963 6,747 6,184 16,894 Coconut 4,762 3,856 4,624 3,960 17,202 5,331 5,772 5,376 16,479 Bean 31,276 17,491 7,030 885 56,682 208,343 114,742 44,409 367,494 Mandioca 10,313 6,611 3,081 1,046 21,051 20,889 12,985 5,927 39,801 Maize 32,946 19,803 10,994 2,166 65,909 233,601 144,853 76,433 454,887 Tomatoes 10,186 7,198 1,394 116 18,894 1,288 894 205 2,387 Crops, total 132,339 102,218 55,051 20,141 309,749 556,209 414,255 223,385 1,193,849 Livestock Sales I Slaughtered ('000 reais) Livestock Stocks (no. of heads) Beef 17,739 28,624 32,024 9,679 88,066 481,076 862,567 573,516 1,917,159 Milk 28,791 57,846 53,820 12,434 152,891 Sheep 1,761 3,084 2,936 534 8,315 337,241 611,366 566,032 1,514,639 Goats 1,582 1,451 1,278 295 4,606 272,037 241,380 230,562 743,979 Pork 9,992 6,798 3,320 488 20,598 619,183 316,359 102,899 1,038,441 Poultry 33,811 40,555 22,647 2,576 99,589 7,368,000 6,990,000 5,515,000 19,873,000 Eggs 15,812 23,530 25,629 69 65,040 Livestock, total 109,488 161,888 141,654 26,075 439,105 Source: IBGE - Censo Agropecuario 1995-1996. Table 50. - Share in value of production by farm size, and by crop. Production Value Farm size <10 10-100 100 - 1000 > 1000 Total (Percent) Crops + LS, total 32.8 34.5 25.2 7.3 99.8 Crops, total 40.1 32.5 18.7 8.6 99.9 Cotton 29.8 36.8 29.4 4.0 100.0 Rice 61.9 27.5 10.0 0.6 100.0 Banana 35.3 44.6 18.6 1.5 100.0 Cashew (nut) 17.7 33.3 24.2 24.8 100.0 Sugarcane 23.2 35.6 30.8 10.4 100.0 Coconut 27.7 22.4 26.9 21.4 98.4 Bean 55.2 30.9 12.4 1.6 100.1 Mandioca 49.0 31.4 14.6 5.0 100.0 Maize 50.0 30.0 16.7 3.3 100.0 Tomatoes 53.9 38.1 7.4 0.6 100.0 0.0 Livestock, total 25.2 36.7 32.0 5.9 99.8 Beef 20.0 32.3 36.2 10.9 99.4 Milk 18.8 37.8 35.2 8.1 99.9 Sheep 21.2 37.1 35.3 6.4 100.0 Goats 34.3 31.5 27.7 6.4 99.9 Pork 48.4 32.9 16.1 2.4 99.8 Poultry 34.0 40.7 22.7 2.6 100.0 Eggs 24.3 36.2 39.4 0.1 100.0 Source: IBGE - Censo Agropecuario 1995-1996. Table 51. - Crop Yields (kg/ha). 1985 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1995196 1997 1998 (Censo) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (PAM) (Censo) (LSPA) (LSPA) Cotton herb. 327 374 195 187 527 245 219 489 412 271 511 680 687 896 413 Cotton arb. 194 146 74 88 144 82 95 119 101 83 133 175 87 117 112 Rice 1,399 2,407 2,489 2,214 2,304 2,200 2,010 2,173 1,954 2,348 2,432 2,679 2,145 2,758 2,141 Banana 752 1,436 925 1,022 1,005 961 867 843 815 587 814 807 778 721 699 Cashew (nut) 404 328 120 220 251 223 195 257 139 68 210 243 88 109 145 Sugarcane 34,398 42,055 42,216 40,519 41,271 44,813 43,172 44,103 43,504 34,971 45,337 46,925 49,381 47,695 46,630 Coconut 5,336 5,016 3,567 4,473 4,255 4,047 3,783 3,682 3,779 3,152 3,569 3,550 3,548 3,312 3,742 Bean 192 207 228 145 332 221 201 324 183 200 363 375 320 290 159 Mandioca 3,534 8,004 8,927 8,484 8,710 8,748 8,110 8,597 6,991 3,357 7,869 7,740 6,415 7,630 6,032 Maize 500 374 537 261 701 460 348 623 334 237 690 730 790 571 262 Abacate 18,214 16,050 18,071 18,194 17,975 18,862 18,310 17,458 16,524 15,847 16,286 Abacaxi 4,252 4,593 4,315 5,941 8,000 13,650 12,818 6,222 5,222 6,556 7,444 8,333 9,222 Amendoim 1,204 1,335 651 1,034 846 795 1,031 650 502 1,138 1,138 1,143 954 Batata Doce 8,853 8,513 8,048 8,261 8,391 8,320 8,744 8,303 8,118 8,210 8,488 Fava 402 404 177 216 173 175 183 182 164 346 236 Fumo 272 340 236 621 670 683 689 726 751 779 789 799 810 Laranja 52,000 61,892 54,537 57,544 56,494 57,060 67,770 70,791 61,713 65,125 59,881 58,907 53,832 Limao 222,119 220,622 221,730 221,057 176,823 171,172 168,745 173,400 166,209 165,730 165,641 Mamao 20,140 18,981 19,460 19,963 19,684 25,317 28,099 26,383 25,715 23,418 20,735 Mamona 735 920 326 791 633 503 798 216 300 809 827 628 386 Manga 54,450 50,717 51,929 52,951 52,987 54,747 55,119 52,829 40,921 48,211 42,496 Maracuja 117,911 118,103 118,647 115,661 118,377 118,129 Melancia 261 244 679 640 520 858 668 1,340 1,570 1,181 1,503 Melao 8,333 8,333 13,753 13,726 12,680 16,355 17,752 17,775 17,370 Pimenta do Reino 174 167 313 294 263 238 200 200 188 100 100 Tomate 31,649 28,933 25,883 29,229 29,869 33,574 36,695 36,284 35,378 34,821 35,072 34,704 34,222 Uva 2,250 2,250 2,333 2,333 26,391 25,375 18,833 15,632 5,867 9,275 24,583 Source: IBGE - Censo Agropecuario 1995-1996. Table 52. - Crop Yields by Farm Size, t/ha, 1995196. <10 10-100 100-1000 >1000 Average Cotton (arboreo) 0.64 0.62 0.83 1.14 0.69 Rice 2.24 2 2.05 1.35 2.14 Banana (1) 0.83 0.77 0.71 0.88 0.78 Cashew (nut) 0.4 0.29 0.27 0.23 0.29 Sugar cane 50.25 50.3 56.1 35.95 49 Coconut (2) 4.08 2.96 3.48 3.76 3.55 Bean 0.31 0.33 0.34 0.33 0.32 Mandioca 6.29 6.5 6.85 6 6.41 Maize 0.8 0.77 0.81 0.74 0.79 (1) Cachos ('000)lha (2) Frutos ('000)/ha. Source: IBGE - Censo Agropecuario 1995-1996. Table 53. - Laborers by Employment Category and Main Agricultural Activity incl. children > 14 yrs. < 14 yrs. No. Percent No. Percent Non-paid family members 941,488 80.4 783,493 78 Permanent Workers 45,522 3.9 43,301 4.3 Temporary Workers 159,367 13.6 157,308 15.7 Parceiros + others 24,347 2.1 23,368 2.3 Total 1,170,724 1,004,438 Annual crops 428,000 36.5 Permanent crops 140,000 12 Mixed Farming (crops and L 302,000 25.8 Livestock 261,000 22.3 Source: IBGE - Censo Agropecuario 1995-1996. Table 54. - Labor Productivity by Farm Size No. of No. of non- Production Variable prod. Prod. Value 1 Gross- laborers paid fam. costs, margins*inon- (total) laborers value incl.salaries laborer paid laborer '000 o000 million RS million R$ R$ R$ <10 745 664 302 103 450 300 10- 100 308 229 317 117 1,030 873 100 - 1000 100 45 231 112 2,314 2,644 1000 - 10 000 15 3 53 [52 ???] 3,527 ??? >10,000 3 0 14 6 5,575 266,667 Average farm 1,170 941 919 392 786 560 Source: IBGE - Censo Agropecuario 1995-1996. * GM = PV - var. costs Table 55. - Socio-Economic Profile of Rural Households in North-Eastem Brazil All HH LO Non-LO LO < 10 ha by farm size Non-LO by income terciles Income quintiles <2 ha 2-5ha 5-10ha low med. high low 2 3 4 high HH- size no. 4.6 4.8 4.4 4.3 5.1 4.9 5.3 4.3 3.3 5.9 4.9 4.3 3.8 3.1 Female head of HH % 16.1 12.3 18.9 17.2 9.4 14.7 12.8 17.6 28 8.2 13.1 8.7 23.3 31.6 Age of HH-head years 46.5 52.6 42 51.6 50.1 54.4 41.5 41 43.6 46.4 44.6 45.4 49 47.4 Homes with electricity % 53.3 47.2 57.8 50.6 34 50 48.7 63.7 63.4 40.4 51.5 62 60.5 60.2 Real HH-income (mean) R$ 1252 931 1487 [.;.i 828 980 439 982 3298 330 606 896 1392 5723 Real HH-income (median) R$ 710 572 811 505 612 591 413 922 2497 292 561 854 1154 2724 Real per-cap. income (mean) R$ 356 267 421 [ 214 305 83 238 1027 55 123 211 361 2290 Real per-cap. income (median) R$ 178 143 204 147 136 176 84 237 726 56 122 207 357 919 Per-cap. HH-expenditures (median) R$ 110 101 116 98 105 94 98 100 157 99 96 95 122 169 HH below high poverty line % 55.6 63.6 49.8 63.2 71.4 58.8 100 36.3 0 100 100 48.9 0 0 HH below indigence line % 17.1 24.6 11.6 25.3 26.4 26.5 29 0 0 61 0 0 0 0 No. of HH 521 220 301 87 53 34 117 91 93 146 99 92 86 98 Real per-cap. income (median) R$ 178 143 204 147 136 176 84 237 726 56 122 207 357 919 Average HH income shares Agricultural income % 27 30 24 27 30 35 16 26 32 16 23 29 32 37 Home food production % 16 19 13 18 21 20 15 16 7 18 17 18 15 8 Wages and benefits, incl. agr. labor % 29 23 34 24 24 19 36 32 34 26 31 28 31 32 Subsidies and pensions % 13 15 11 18 12 11 15 11 6 20 14 11 8 6 Non-farm business income % 2 1 3 1 2 2 -1 2 9 -1 2 2 4 7 Remittances % 3 2 3 2 2 1 4 3 2 3 3 3 1 2 Housing (imputed) % 8 4 11 10 8 11 17 4 7 18 9 8 7 6 Other, incl. rental income % 2 1 2 0 1 2 1 1 3 1 1 1 2 3 (1) Data not reliable [...] (2) Per-capita income was calculated using the total number of persons per HH, not adjusted for adult equivalent. Poverty Indicators CESEM Statistical Annex.xis 5. POBREZA - 8/16/00 11:38 AM Table 56. - Income Distribution by Area. Income Percentile Family Income Per Capita Ceara Fortaleza Fortaleza Cities above Cities 20,000- Cities less than Rural Areas Municipality Periphery 100,000 100,00 20,000 1 1.5 7.18 4.78 4.69 10.3 2.66 1.5 2 5.28 18.12 10.5 7.57 11.28 5.54 3.21 3 6.37 23.89 13.59 8.21 11.57 6.97 4.5 4 8.4 27.61 16.5 16.46 13.46 8.82 5.5 5 10.56 29.97 18.43 17.97 18.35 11.46 6.03 6 11.56 33.02 20.44 22.88 23.62 12.94 6.81 7 13.14 35.1 21.15 25.98 25.03 14.98 7.67 8 14.51 39.3 23.82 42.19 25.09 18.1 8.77 9 15.46 41.5 25.07 42.23 26.56 18.37 9.73 10 17 44.47 25.99 43.12 28.38 19.59 10.61 11 17.89 46.23 27.76 44.4 29.45 20.47 11.1 12 18.78 47.85 29.99 45.16 30.48 21.18 11.83 13 20.04 50.32 30.72 47.3 31.43 22.91 12.7 14 21.18 52.73 31.54 47.47 31.92 24.37 13.19 15 22.07 54.53 33.27 49.11 32.23 24.9 14.11 16 23.27 56.4 33.76 49.81 34.02 25.37 14.51 17 24.33 58.15 34.56 54.24 34.55 25.79 14.92 18 25.13 59.67 35.38 55.08 35 26.35 15.21 19 26.15 61.29 37.18 55.77 35.68 26.82 16.22 20 27.24 62.69 38.1 56.99 37.37 27.91 16.52 21 28.7 64.55 39.89 60.32 37.74 28.56 17.01 22 29.57 66.64 40.34 61.69 39.48 29.01 17.26 23 30.52 68.14 41.36 61.75 39.63 29.69 17.69 24 31.38 69.41 42.31 63.56 39.68 30.67 18.41 25 32.22 70.99 44.02 64.54 40.34 33 18.91 26 33.48 72.68 44.86 65.08 40.36 34.37 19.22 27 34.46 74.01 45.41 66.72 42.47 34.7 20.29 28 35.46 75.27 46.72 69.22 43.43 35.58 20.97 29 36.77 76.99 47.39 70.32 44.15 36.99 21,37 30 37.95 79.26 50.48 70.85 45.02 37.57 21.84 31 39.48 81.06 51.13 71.16 45.25 38.85 22.07 32 40.36 83.22 52.54 72 46.16 41.08 22.89 33 41.84 84.59 53.3 75.19 47.77 41.79 23.14 34 43.05 86.59 54.24 76.14 50.99 42.58 23.83 35 43.92 88.03 55.81 76.61 51.15 43.48 24.43 36 44.78 90.29 56.62 86.05 52.03 44.78 25.14 37 45.64 92.72 57.46 89.45 55.26 45.65 26.04 38 46.92 94.71 59.8 90.79 56.21 46.07 26.69 39 47.92 96.15 60.84 91.84 57.14 47.73 27.78 40 49.26 98.48 62.51 94.82 57.38 49.48 28.7 41 50.77 101.03 63.38 95.65 57.79 51.94 29.37 42 52.4 102.24 64.56 98.8 59.12 53.39 29.85 43 53.9 103.86 65.26 101.39 59.37 53.84 30.39 44 55.64 106.5 67.11 103.83 61.45 55.6 30.84 45 57.03 109.48 68.32 104.66 61.62 56.79 31.17 46 58.53 111 89 69.16 106.57 64.75 57.4 31.76 47 59.97 113.99 70.34 108.8 67.73 59.07 32.22 48 61.6 116.8 72.15 109 68.52 60.42 32.81 49 62.69 11947 73.11 111.94 70.19 60.92 33.48 50 64.56 121.87 74.38 113.23 70.59 61.79 34.12 51 66.71 126.7 76.16 116.29 72.8 63.32 35.13 52 68.25 128.84 76.74 116.3 74.15 642JESEMStatistic.Jfnnex.xIs Alltogether-8/16/00 11:38AM Income Percentile Family Income Per Capita Ceara Fortaleza Fortaleza Cities above Cities 20,000- Cities less than Rural Areas Municipality Periphery 100,000 100,00 20,000 53 69.71 132.27 78.8 121.7 76.26 66.73 36.75 54 71 135.29 81.16 122.57 77.05 67.65 37.78 55 73 137.22 82.79 122.6 77.57 69.13 38.32 56 74.25 142.29 85.18 124.17 79.81 71 39.53 57 76.13 144.99 87.02 124.65 80.58 72.9 40.12 58 77.48 147.92 88.04 125.34 83.75 74.68 40.85 59 79.62 153.19 89.77 126.35 85.02 76.23 42.24 60 81.64 158.04 91.21 135.17 88.6 76.73 43.39 61 83.84 161.42 91.99 139.22 95.47 78.3 43.81 62 85.95 166.56 92.92 148.54 97.42 79.62 44.43 63 88.06 171.46 95.67 150.23 101.37 81.05 44.78 64 90 176.14 97.07 151.17 104.52 84.24 45.32 65 92.63 180.06 98.94 154.18 107.87 88.24 46.6 66 95.19 185.15 100.55 158.6 110.82 89.27 47.49 67 97.74 189.99 104.73 179.94 111.8 90.77 48.59 68 100.47 194.55 106.71 188.25 114.78 92.64 49.16 69 103.14 200.59 108.47 189.39 116.49 95.92 49.91 70 105.88 208.08 110.97 192.58 117.37 97.74 51.28 71 109.23 215.8 112.8 198.4 119.89 98.92 52.87 72 112.16 226.09 l 14.2 205.51 120.48 102.53 54.06 73 116.03 231.68 117.41 215.69 121.26 105.1 55.92 74 119.15 238.53 119.3 222.19 124.01 107.95 58.53 75 122.57 250.77 122.36 224.83 126.37 110.09 59.5 76 125.16 262.81 126.26 230.49 133.18 112.86 62.02 77 130.17 275.45 129.76 231.44 140.86 117.52 63.17 78 134.27 280.67 133.35 240.57 145.55 121.8 66.49 79 139.99 290.9 136.07 294.47 147.78 124.79 68.13 80 145.04 302.77 140.99 326.42 155.27 127.15 69.88 81 151.17 325.29 1,42.46 329.89 160.8 131.01 72.56 82 158.6 334.68 146.22 342.49 165.96 136.72 74.15 83 166.08 354.18 154.39 356.95 169.63 143.99 75.49 84 173.29 373.59 155.5 368.74 188.43 155.38 78.28 85 182.37 392.06 164.89 386.24 190.69 158.63 80.97 86 190.65 416.95 169.54 412.25 194.64 166.79 82.52 87 199.62 437.3 174.88 543.61 205.5 172.02 84.71 88 215.39 462.71 181.08 702.78 224.5 184.27 86.76 89 230.43 520.46 189.31 927.55 237.69 190.4 88.75 90 246.2 564.18 198.63 1884.63 256.63 197.93 92.67 91 266.78 593.62 205.44 3620.58 278.74 214.79 95.85 92 288.08 637.58 220.15 - 305.72 241.15 102.42 93 316.7 685.75 231.72 - 316.08 258.92 105.52 94 352.25 738.43 247.6 - 366.04 277.38 112.08 95 386.92 796.59 262.51 - 398.08 292.31 121.45 96 442.33 899.59 284.9 - 561.88 313.4 124.69 97 550.59 1023.53 325.62 - 636.59 369.17 132.57 98 671.77 1195.02 357.09 - 864.4 425.48 141.3 99 807.52 1443.31 449.14 - 3687.58 522.81 168.57 100 1226.14 1801.02 526.41 - - 741.3 200.76 101 7158.85 7158.85 2458.5 - - 2118.83 704.56 CESEM Statistical Annex.xls All together - 8/16/00 11:38 AM Table 57. POVERTY PROFILE - 1996 CEARA With Inputed Rent Indigence Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita PO P1 P2 Population P0 P1 P2 Household Population Earnings (n) (%) () (*%) (%) (%) (%) .................... ................... .....- .................................................................I....................................................................................................................................._,, Total 6812575 131.71 49.25 23.68 14.57 100.00 100.00 100.00 100.00 .......... ...........................................Me.t..o po...t.anC.re................................................9 8-3.34...................-..66.........................2....................6...4.....................3....7..................28..6....6.7....46. Zone Metropolitan Core 1948334 251.66 20.06 6.49 3.07 28.60 11.65 7.64 6.03 Metropolitan Periphery 590095 107.07 41.86 16.23 8.59 8.66 7.36 5.94 5.11 Large Urban 293577 166.95 30.87 11.09 6.36 4.31 2.70 2.02 1.88 Medium Urban 468956 132.19 47.68 18.58 9.44 6.88 6.66 5.40 4.46 Small Urban 1117074 106.84 51.14 23.32 13.87 16.40 17.02 16.15 15.61 Rural 2394539 47.37 76.51 42.21 27.73 35.15 54.60 62.66 66.91 Dependency Ratio 1 457660 340.81 2.34 0.49 0.14 6.72 0.32 0.14 0.07 14 1588861 46.41 83.23 49.53 33.65 23.32 39.41 48.78 53.88 Other/Not Specified 137744 15.04 97.53 79.02 67.58 2.02 4.00 6.75 9.38 ................. ............................................................................................................................................................................................................................................................................................................. Housing Own House already Paid vith Own L 3992676 140.41 44.77 20.61 12.33 58.61 53.28 51.00 49.60 Own House already Paid without Ow 864459 64.12 69.28 38.14 25.55 12.69 17.85 20.44 22.26 Own House Still Paid 275082 270.21 17.29 5.70 2.88 4.04 1.42 0.97 0.80 Rent 686730 199.81 30.44 10.66 5.06 t0.08 6.23 4.54 3.50 Ceded 967915 67.64 71.99 37.64 23.94 14.21 20.77 22.58 23.35 Other 20939 159.87 61.40 32.23 22.26 0.31 0.38 0.42 0.47 Not Specified 4774 184.37 55.49 18.12 5.92 0.07 0.08 0.05 0.03 Water Canalized 3524287 204.85 27.26 9.98 5.31 51.73 28.64 21.81 18.85 No Canalized 3286589 53.18 72.86 38.38 24.50 48.24 71.36 78.19 81.15 Other/Not Specified 1699 316.08 0.00 0.00 0.00 0.02 0.00 0.00 0.00 ..............................................................................................................I......................................................................................................................................I......... Sanitailon SewageSystem 330445 217.17 23.78 7.00 3.24 4.85 2.34 1.43 1.08 Concrete Cesspit 1 253349 368.08 12.60 4.10 2.07 3.72 0.95 0.64 0.53 ConcreteCesspit2 1106984 273.03 20.13 6.73 3.20 16.25 6.64 4.62 3.57 Rudimental Cesspit 2690507 118.15 41.29 16.90 9.38 39.49 33.11 28.19 25.44 Drain 49330 66.18 66.24 23.16 9.17 0.72 0.97 0.71 0.46 Riveror Lake 9796 66.56 69.57 25.37 11.28 0.14 0.20 0.15 0.11 Other 4981 240.42 42.54 20.45 9.83 0.07 0.06 0.06 0.05 Not Specified 2367183 45.21 78.98 43.74 28.83 34.75 55.72 64.19 68.77 ......................................................... ..................................................... ....................................................................................................*...................................................................... ................................ Eletricity Yes 5040557 163.25 37.62 16.06 9.25 73.99 56.52 50.19 47.00 No 1767670 41.73 82.39 45.41 29.74 25.95 43.40 49.76 52.97 Other/Not Specified 4348 150.21 60.93 19.89 6.50 0.06 0.08 0.05 0.03 ............................................................................. ................................... ....................... ................................................................................................................................................................... Garbage .............. Collected Directly 2789447 218.35 24.78 9.01 4.66 40.95 , 20.60 15.58 13.09 Collected Indirectly 476692 153.36 32.08 10.23 4.67 7.00 4.56 3.02 2.24 Burned 1079491 67.74 72.02 38.01 24.43 15.85 23.17 25.43 26.57 Unused Plot of Land 2378863 57.08 70.72 36.93 23.63 34.92 50.14 54.46 56.64 Other/Not Specified 88082 70.09 58.64 27.59 16.29 1.29 1.54 1.51 1.45 Source: PNAD - IBGE CESEM Statistical Annex.xls CETO IND - 8/16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Indigence Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (°) (%) (°) (%) Gender Men 5657663 128.13 51.61 25.47 15.83 83.05 87.02 89.31 90.28 Women 1154912 149.23 37.70 14.93 8.36 '16.95 12.98 10.69 9.73 Race Indigenous 8586 62.02 80.22 28.02 9.78 0.13 0.21 0.15 0.08 White 2003795 202.75 37.64 17.15 10.40 29.41 22.48 21.30 21.00 Black 4798064 102.17 54.07 26.41 16.32 70.43 77.32 78.56 78.92 Yellow 1065 122.36 0.00 0.00 0.00 0.02 0.00 0.00 0.00 Not Specified 1065 113.12 0.00 0.00 0.00 0.02 0.00 0.00 0.00 Age 24Yers or Les 29551 9 1 00.82 47.46 23.71i15.2564.34 4.18 4.344.54 25 to 44Years 3077880 120.30 55.14 28.59 18.21 45.18 50.58 54.55 56.47 45 to 64Years 2535778 142.27 49.26 22.34 13.39 37.22 37.23 35.12 34.21 65 Years orMore 903398 151.05 29.75 10.71 5.25 13.26 8.01 6.00 4.78 Years of Schooling Lessthan 1Year.2822113. 6045 66.90 33.43 20.82 4.43 56.27 58.48 59.20 1 to 4 Years 1584607 74.40 60.17 29.38 18.25 23.26 28.42 28.86 29.14 4to8Years 1225633 130.71 34.61 14.11 8.18 17.99 12.64 10.72 10.10 8to12Years 946724 273.25 9.35 3.26 1.61 13.90 2.64 1.91 1.54 More thar 12 Years 233498 813.21 0.46 0.22 0.10 3.43 0.03 0.03 0.02 Immigration No Immigrant 3750899 104.46 58.12 29.41 18.53 55.06 64.97 68.39 70.03 Oto5Years 379927 136.36 41.10 19.73 11.86 5.58 4.65 4.65 4.54 6 to 9 Years 276273 135.28 44.38 18.71 10.66 4.06 3.65 3.20 2.97 More Than 10 Years 2041951 159.79 38.59 16.31 9.35 29.97 23.49 20.65 19.25 Other/No Sp cified 363525 247 55 29.92 13.82 8.78.5....3.24.3.11 3.22 Working Class Inactive 1255962 144.16 39.40 16.91 10.30 18.44 14.75 13.17 13.04 Unemployed 143729 76.41 71.86 41.12 28.22 2.11 3.08 3.66 4.09 Formal Emploees 828205 151.12 28.30 8.98 3.84 12.16 6.99 4.61 3.21 Informal Employees 1029581 75.83 66.91 31.96 18.90 15.11 20.53 20.40 19.61 Self-Employed 2621031 96.08 58.12 30.35 19.42 38.47 45.40 49.30 51.29 Employer 304983 349.79 26.73 11.90 7.21 4.48 2.43 2.25 2.21 Public Servant 392115 324.56 19.77 6.79 3.04 5.76 2.31 1.65 1.20 Unpaid 234201 67.98 64.42 33.98 22.52 3.44 4.50 4.93 5.31 ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,2768,11481,30.78,16. ,,8, 9.37 0.04t 0.03 0 114 0.03 EmploymentTenure OYears 1399691 137.21 42.73 19.40 12.14 20.55 17.83 16.83 17.13 1 Years or More 755803 108.77 51.96 23.52 13.71 11.09 11.70 11.02 10.44 1 to 3 Years 699936 138.12 42.51 18.74 10.27 10.27 8.87 8.13 7.25 3to5Years 412630 157.10 36.98 15.46 8.08 6.06 4.55 3.95 3.36 Morethan5Years 3509608 130.91 53.79 27.28 17.31 51.52 56.26 59.34 61.22 Other/NotSpecified7 59.73 76.58 33.61 17.16 0.51 0.80 0.73c_ 3 7 0.60 Enterprise Size 1 76726 264.75 11.33 1.60 0.33 1.13 0.26 0.08 0.03 2 a 5 371840 189.80 39.66 14.80 7.25 5.46 4.39 3.41 2.72 6 a 10 122259 230.66 32.61 8.62 3.22 1.79 1.19 0.65 0.40 >11 23064 987.96 0.00 0.00 0.00 0.34 0.00 0.00 0.00 Other/Not Specified 6218686 121.47 50.80 24.87 15.46 91.28 94.16 95.86 96.86 ....................................I..........................................I........................................................................................................ ............................ ....................... ........................................................................................ Sector of Activity Agriculture 2199675 52.03 78.06 43.26 28.50 32.29 51.17 58.99 63.17 Manufacturing 594445 112.41 51.31 22.05 12.10 8.73 9.09 8.12 7.25 Construction 514905 106.91 37.63 13.49 6.40 7.56 5.77 4.31 3.32 Services 1767865 203.36 27.17 9.62 4.65 25.95 14.31 10.54 8.29 Public Sector 335994 325.63 18.21 5.80 2.50 4.93 1.82 1.21 0.85 Other/Not Specif!ed 1399691 137 21 42.73 19.40 12.14 . 0........ 2351683 Source: PNAD - IBGE stie.. . . . . .. . . . . . . . . . . . . . . .1 Table 58. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Low Poverty Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita PO P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) Total 6812575 131.71 76.44 44.71 30.96 100.00 100.00 100.00 100.00 Zone Metropolitan Core 1948334 251.66 51.76 22.52 12.43 28.60 19.36 14.41 11.47 Metropolitan Periphery 590095 107.07 76.72 39.44 24.64 8.66 8.69 7.64 6.89 Large Urban 293577 166.95 66.07 30.47 18.30 4.31 3.72 2.94 2.54 Medium Urban 468956 132.19 76.61 41.31 26.68 6.88 6.90 6.36 5.93 Small Urban 1117074 106.84 80.41 46.06 31.34 16.40 17.25 16.89 16.59 Rural 2394539 47.37 95.85 65.84 49.88 35.15 44.07 51.76 56.58 ....... ............................................ ........................... ....I.............. ........................................................................................................................................................................ ...... ....................... Dependency Ratio 1 457660 340.81 35.42 7.26 2.52 6.72 3.11 1.09 0.55 14 1588861 46.41 95.15 70.55 55.83 23.32 29.03 36.80 42.02 Other/Not Specified 137744 15.04 99.38 88.94 81.18 2.02 2.63 4.02 5.30 ....... ......................."'l q ...................................................................................................................... ........................................ ..................................................................................... ........................... Housing Own House already Paid with Own L 3992676 140.41 74.44 41.66 28.02 58.61 57.07 54.62 53.00 Own House already Paid without Ow 864459 64.12 91.15 60.71 45.61 12.69 15.13 17.23 18.68 Own House Still Paid 275082 270.21 46.47 19.41 10.68 4.04 2.45 1.75 1.39 Rent 686730 199.81 61.29 29.19 17.41 10.08 8.08 6.58 5.67 Ceded 967915 67.64 90.88 61.07 45.42 14.21 16.89 19.41 20.83 Other 20939 159.87 78.64 51.75 38.76 0.31 0.32 0.36 0.38 Not Specified 4774 184.37 55.49 37.06 24.76 0.07 0.05 0.06 0.06 ........................................................................................................................................................................................................................................................................................................................... Water Canalized 3524287 204.85 59.41 27.82 16.53 51.73 40.20 32.19 27.59 No Canalized 3286589 53.18 94.75 62.84 46.50 48.24 59.80 67.81 72.41 Other/Not Specified 1699 316.08 0.00 0.00 0.00 0.02 0.00 0.00 0.00 Sanit ton Se wageSystem 330445 217.17 55.72 23.87 13.17. 4.85.3.54.259.2.06 Concrete Cesspit 1 253349 368.08 37.87 14.55 7.79 3.72 1.84 1.21 0.93 ConcreteCesspit2 1106984 273.03 49.60 21.79 12.25 16.25 10.54 7.92 6.42 Rudimental Cesspit 2690507 118.15 75.70 39.53 25.10 39.49 39.11 34.92 31.99 Drain 49330 66.18 95.69 54.16 34.10 0.72 0.91 0.88 0.80 River or Lake 9796 66.56 95.65 50.18 33.56 0.14 0.18 0.16 0.16 Other 4981 240.42 42.54 31.65 23.55 0.07 0.04 0.05 0.06 Not Specified 2367183 45.21 96.46 67.25 51.35 34.75 43.84 52.27 57.58 I W .................. ............................................... ...............................................................I................................................................................................................................. ......................................... .................... Eletricity Yes 5040557 163.25 69.04 36.14 23.25 73.99 66.82 59.82 55.53 No 1767670 41.73 97.60 69.14 53.04 25.95 33.13 40.13 44.42 Other/Not Specified 4348 150.21 60.93 40.70 27.18 0.06 0.05 0.06 0.06 .........................e ............. ...... .............. ........... ......... ........... ......: Garbage Collected Directly 2789447 218.35 56.36 25.80 15.11 40.95 30.19 23.63 .9.97 Collected Indirectly 476692 153.36 71.74 32.75 18.66 7.00 6.57 5.13 4.21 Burned 1079491 67.74 91.02 61.44 45.83 15.85 18.87 21.78 23.44 Unused Plot of Land 2378863 57.08 93.67 61.33 45.10 34.92 42.79 47.90 50.83 Other/Not SP cified 88082 70.09 93.97 54.34 37.05 1.9 1.59 1.57 1.55 Source: PNAD - IBGE CESEM Statistical Annex.xis CETO PL - 8/16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Low Poverty Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) .........................I..........................................................I....................................................................................... ...................................................................................................I................................................. Total 6812575 131.71 76.44 44.71 30.98 100.00 100.00 100.00 100.00 Gender Men 5657663 128.13 77.75 46.50 32.68 83.05 84.47 86.37 87.59 Women 1154912 149.23 70.03 35.94 22.69 18.95 15.53 13.83 12.42 ace Indigenous 8586 .02 92.57 60.25 39.70 0.13 0.15 0.17 0.16 White 2003795 202.75 64.61 34.85 23.37 29.41 24.86 22.93 22.18 Black 4798064 102.17 81.35 48.81 34.16 70.43 74.95 76.90 77.66 Yellow 1065 122.36 '100.00 7.28 0.53 0.02 0.02 0.00 0.00 NotSpecified 1065 113.12 101.00 14.43 2.06 0.02 0.02 0.01 0.00 Age 24 Years or Less 295519 100.82 81.75 46.81 31.94 4.34 4.64 4.54 4.47 25 to 44 Years 3077880 120.30 78.23 48.70 35.28 45.18 46.23 49.22 51.44 45 to 64 Years 2535778 142.27 75.00 43.98 30.06 37.22 36.52 36.62 36.11 65 Years orMore 903398 151.05 72.69 32.45 18.65 13.26 12.61 9.62 7.98 Years of Schooling Lessthan 1Year 2822113 60.45 92.21 58.39 42.00 41.43 49.97 54.11 56.15 1 to 4 Years 1584607 74.40 87.72 53.44 37.71 23.26 26.69 27.80 28.31 4 to 8 Years 1225633 130.71 70.95 34.82 21.61 17.99 16.70 14.01 12.55 8 to12 Years 946724 273.25 35.20 12.81 6.55 13.90 6.40 3.98 2.94 More than 12 Yr ar 233498 13.21 5.46 i.31 0.48 3.43 0.24 0.10 0.05 Immigration No Immigrant 3750899 104.46 83.39 51.67 36.99 55.06 60.06 63.63 65.74 O to 5 Years 379927 136.36 75.29 41.36 27.34 5.58 5.49 5.16 4.92 6 to 9 Years 276273 135.28 72.09 39.43 25.98 4.06 3.82 3.58 3.40 More Than 10 Years 2041951 159.79 68.32 36.11 23.41 29.97 26.79 24.21 22.65 OtherlNot Specified 363525 247.55 54.89 28.70 19.12 5.34 3.8 3.43 3.29 Working Class Inactive 1255962 144.16 73.72 38.24 24.72 18.44 17.78 15.77 14.71 Unemployed 143729 76.41 90.30 62.44 48.00 2.11 2.49 2.95 3.27 Formal Emploees 828205 151.12 68.36 30.20 16.73 12.16 10.87 8.21 6.56 Informal Employees 1029581 75.83 89.23 57.27 40.72 15.11 17.64 19.36 19.86 Self-Employed 2621031 96.08 81.53 51.42 37.38 38.47 41.03 44.25 46.42 Employer 304983 349.79 49.96 26.51 17.21 4.48 2.93 2.65 2.49 Public Servant 392115 324.56 43.04 18.80 10.95 5.76 3.24 2.42 2.03 Unpaid 234201 67.98 88.82 56.79 41.79 3.44 3.99 4.37 4.64 Other/NotSpecified 2768 114.81 46.17 26.23 19.01 0.04 0.02 0.02 0.02 EmploymentTenure OYears 1399691 137.21 75.42 40.72 27.11 20.55 20.27 18.71 17.98 1YearsorMore 755803 108.77 79.39 46.10 31.39 11.09 11.52 11.44 11.24 1 to3Years 699936 138.12 73.63 40.13 26.27 10.27 9.90 9.22 8.71 3to5Years 412630 157.10 69.21 35.28 22.46 6.06 5.48 4.78 4.39 More than 5 Years 3509608 130.91 77.46 47.89 34.28 51.52 52.20 55.18 57.00 Other/Not Specified 34907 59.73 92.99 57.78 41.05 0.51 0.62 0.66 0.68 Enterprise Size 1 76726 264.75 52.11 18.85 8.36 1.13 0.77 0.47 0.30 2 a 5 371840 189.80 69.30 36.98 23.04 5.46 4.95 4.52 4.06 6 a 10 122259 230.66 58.09 28.87 16.37 1.79 1.36 1.16 0.95 >11 23064 987.96 5.54 2.12 0.81 0.34 0.02 0.02 0.01 Other/Not Specified 6218686 121.47 77.79 45.96 32.14 91.28 92.90 93.84 94.68 SectorofActivity Agriculture 2199675 52.03 94.99 66.47 50.72 32.29 40.12 48.01 52.86 Manufacturing 594445 112.41 82.39 46.68 30.87 8.73 9.40 9.11 8.69 Construction 514905 106.91 80.65 39.89 23.30 7.56 7.97 6.74 5.68 Services 1767865 203.36 57.39 26.63 15.75 25.95 19.48 15.45 13.19 Public Sector 335994 325.63 42.59 17.86 10.02 4.93 2.75 1.97 1.59 Other/Not Specified 1399691 137.21 75,42 40.72 27.11 20.55.j?/738 Source: PNAD - IBGE Table 59. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Metropolitan Core Indigence Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita PO P1 P2 Population PO P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) .................. ......................................................................................................................I...................................................................... ...........................I................................................................................ Total 1948334 251.66 20.06 6.49 3.07 100.00 100.00 100.00 100.00 ii ; ~ k~ .....................i .......................................I....... ..........I.................................................I......,........................I................I _ . Dependency Ratio 1 139691 592.29 0.31 0.04 0.01 7.17 0.11 0.04 0.01 111 14055 1309.70 0.00 0.00 0.00 0.72 0.00 0.00 0,00 Other/Not Specified 1699181 242.02 19.70 6.50 3.10 87.21 85.67 87.39 87.93 Sectorof Activity Agriculture 10223 450.39 20.84 8.65 3.59 0.52 0.55 0.70 0.61 Manufacturing 202731 192.61 22.69 4.96 1.66 10.41 11.77 7.95 5.63 Construction 229573 137.81 29.13 9.61 4.39 11.78 17.11 17.45 16.85 Services 817101 274.35 15.17 4.21 1.72 41.94 31.72 27.21 23.45 Public Sector 161848 443.96 8.03 2.57 0.92 8.31 3.32 3.29 2.49 Other/Not Specified 526858 225.85 26.36 10.41 5.79 27.04 35.53 43.38 50.97 Source............. P.................... G E....C....S....M...Statistica.........................................CECA...................8/16/00...........11:....38.....AM.. Siou r"c"e:PNAD-I BGE CESEM Statistical Annex.xIs CECA IND -8/16/00 11:38 AM Table 60. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Metropolitan Core Low Poverty Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) Total 1948334 25 1.66 20.06 6.49 307 10.00 100.00 100.00 100.00 Dependency Ratio 1 139691 592.29 0.31 0.04 0.01 7.17 0.11 0.04 0.01 14 290483 90.43 56,31 21.49 10.19 14.91 41.85 49.36 49.45 .OtherlNot Specified 40249 29.64 93.12 59.70 41.61 2.07 9.59 19.00 27.99 Housing Own House already Paid with Own L 1145274 256.85 19.04 6.34 3.10 58.78 55.80 57.40 59.25 Own House already Paid without Ow 213381 131.91 32.94 9.75 4.06 10.95 17.98 16.45 14.48 Own House Still Paid 141828 394.57 3.00 0.68 0.26 7.28 1.09 0.77 0.63 Rent 331782 281.98 17.07 5.20 2.30 17.03 14.50 13.65 12.76 Ceded 102012 147.40 33.82 12.62 6.84 5.24 8.83 10.18 11.67 Other 12992 235.98 54.10 15.07 5.56 0.67 1.80 1.55 1.21 Not Specified 1065 350.04 0.00 0.00 0.00 0.05 0.00 0.00 0.00 ..... ....................................................................................................................................................................................................................... ................................ Water Canalized 1648281 280.29 15.98 4.87 2.22 84.60 67.41 63.49 61.22 No Canalized 299414 94.05 42.53 15.42 7.75 15.37 32.59 36.51 38.78 Other/Not Specified 639 228.03 0.00 0.00 0.00 0.03 0.00 0.00 0.00 ........................................................................ ............................ ....................... .. .............. ................... .......... .........I...................................................................................................... Sanitation Sewage System 142028 284.16 19.79 6.17 2.86 7.29 7.19 6.93 6.79 Concrete Cesspit 1 139490 472.39 9.01 2.80 1.28 7.16 3.22 3.08 2.97 Concrete Cesspit2 604370 364.61 10.22 3.28 1.59 31.02 15.80 15.68 16.08 Rudimental Cesspit 948511 163.52 23.55 7.13 3.27 48.68 57.17 53.45 51.88 Drain 4259 57.12 55.01 17.07 5.38 0.22 0.60 0.57 0.38 River or Lake 9157 69.98 67.45 22.04 8.33 0.47 1.58 1.60 1.28 Other 213 1705.96 0.00 0.00 0.00 0.01 0.00 0.00 0.00 Not Specified 100306 73.26 56.27 23.55 12.30 5.15 14.44 18.68 20.61 .................... i ............... ....... ........... I....................................-........... .............I.............................................................................. ............... ........... .................................................................... Eletricity Yes 1932362 253.10 19.75 6.34 2.99 99.18 97.66 96.93 96.58 No 15333 71.03 59.73 25.28 13.33 0.79 2.34 3.07 3.42 Other/Not Specified 639 228.03 0.00 0.00 0.00 0.03 0.00 0.00 0.00 ..............................I...................................... ............................................................................................................. ...............I,.......................................... ......................... Garbage Collected Directly 1624633 277.99 17.20 5.67 2.73 83.39 71.50 72.90 74.21 Collected Indirectly 239796 126.36 30.82 9.48 4.39 12.31 18.91 17.97 17.59 Burned 14480 155.41 36.76 14.51 6.32 0.74 1.36 1.66 1.53 Unused Plot of Land 59202 88.16 43.88 13.37 6.00 3.04 6.65 6.26 5.93 Other/Not Specified 10223 89.04 60,41 14.96 4.33 0.52 1.58 1.21 0.74 ..................................................................................... ...................................................................................................... ........................................................................................................................................ Source: PNAD - IBGE CESEM Statistical Annex.xis CECA PL - 8/16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Metropolitan Core Indigence Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Eamings (#) (%) (#) (%) (%) (%) (N) ............ ..........................................................................................................I.................I...................................................................................................... ............................................................................... Total 1948334 251.66 20.06 6.49 3.07 100.00 100.00 100.00 100.00 ......................ii .. ............................. ..................... ...............................................................................................................I.......................................... ........................................................................... Gender Men 1470260 258.52 20.25 6.68 3.18 75.46 76.18 77.70 78.01 Women 478074 230.54 19.47 5.90 2.75 24.54 23.81 22.30 21.99 ..................... ..................................................................................................................................................................................I.............................................................................................................. Race Indigenous 638 260.59 0.00 0.00 0.00 0.03 0.00 0.00 0.00 White 697419 376.41 11.48 3.19 1.39 35.80 20.49 17.57 16.22 Black 1250277 182.06 24.85 8.34 4.01 64.17 79.51 82.43 83.78 Age 24 Years or Less 90288 164.99 18.87 5.40 2.52 4.63 4.36 3.86 3.81 25 to 44 Years 920601 233.18 23.02 7.53 3.63 47.25 54.22 54.83 55.82 45 to 64 Years 726194 278.85 20.06 6.55 3.08 37.27 37.28 37.62 37.40 65 Years or More 211251 275.72 7.66 2.20 0.84 10.84 4.14 3.68 2.97 ...........................................................................................................................................................................................................................--.......... --........................................... Yearssot Schooling Lessthan 1Year 372471 99.30 35.96 11.47 5.46 19.12 34.28 33.78 33.98 1 to 4 Years 320294 124.67 31.78 10.61 5.02 16.44 26.05 26.87 26.85 4 to 8 Years 523016 159.04 23.29 7.50 3.58 26.84 31.17 31.03 31.32 8 to12 Years 552608 318.28 6.01 1.91 0.85 28.36 8.50 8.33 7.85 More thar 12 Years 179945 857.63 0.00 0.00 0.00 9.24 0.00 0.00 0.00 Immigration No Immigrant 633956 248.22 20.76 7.52 3.80 32.54 33.68 37.70 40.25 Oto5Years 86884 253.18 16.67 5.56 2.57 4.46 3.71 3.82 3.73 6 to 9 Years 100516 210.52 29.45 8.18 3.12 5.16 7.57 6.51 5.24 More Than 10 Years 945113 235.76 20.01 6.28 2.93 48.51 48.40 46.91 46.24 .orking Class OSher/NotSpecified 181865 368.22 14.29 3.52 1.49 9.33 6.65 5.06 4.53 orking Cass inactive 457221 245.09 22.08 7.92 4.14 23.47 25.83.28.3 31.61 Unemployed 69637 99.50 54.44 26.79 16.64 3.57 9.70 14.76 19.36 Formal Emploees 471687 188.92 21.13 5.01 1.69 24.21 25.50 18.68 13.28 Informal Employees 216781 161.87 29.08 9.45 4.52 11.13 16.13 16.21 16.38 Self-Employed 455738 230.87 16.50 5.02 2.10 23.39 19.24 18.09 15.99 Employer 72833 727.06 3.22 0.12 0.01 3.74 0.60 0.07 0.01 Public Servant 193788 451.42 3.74 1.17 0.43 9.95 1.85 1.79 1.40 Unpaid 7881 145.91 45.95 22.74 11.67 0.40 0.93 1.42 1.54 Other/Not Sp cified 2768 11481 30. 78 16. 98 9.37 0.14 0.22 0.37 0.43 EmploymentTenure 0 Years 526858 225.85 26.36 10.41 5.79 27.04 35.53 43.38 50.97 1 Years or More 253193 169.13 28.43 8.16 3.42 13.00 18.42 16.35 14.48 1to 3 Years 250225 232.55 20.09 5.74 2.30 12.84 12.86 11.36 9.62 3 to 5 Years 140127 265.59 15.66 3.88 1.52 7.19 5.61 4.30 3.57 More than 5 Years 773034 300.97 13.72 3.87 1.54 39.68 27.14 23.64 19.88 Other/NotSpecified 4897 88.56 34.80 25.11 18.12 0.25 0.44 0.97 1.48 Enterprise Size 1 16400 484.92 0.00 0.00 0.00 0.84 0.00 0.00 0.00 2 a 5 146935 227.17 21.45 6.75 3.33 7.54 8.06 7.84 8.18 6 a 10 71763 269.39 34.13 8.40 3.24 3.68 6.27 4.77 3.89 >11 14055 1309.70 0.00 0.00 0.00 0.72 0.00 0.00 0.00 Other/NotSpecified 1699181 242.02 19.70 6.50 3.10 87.21 85.67 87.39 87.93 ................................... ................................. ............................................ ........................................... ............ . ..... 1 ..........! ........ . 7 ........... .......... Sector of Activity Agriculture 10223 450.39 20.84 8.65 3.59 0.52 0.55 0.70 0.61 Manufacturing 202731 192.61 22.69 4.96 1.66 10.41 11.77 7.95 5.63 Construction 229573 137.81 29.13 9.61 4.39 11.78 17.11 17.45 16.85 Services 817101 274.35 15.17 4.21 1.72 41.94 31.72 27.21 23.45 Public Sector 161848 443.96 8.03 2.57 0.92 8.31 3.32 3.29 2.49 Other/NotSoecified 526858 225.85 26.36 10.41 5.79 27.04 35.53 43.38 50.97 ................................... ...................... .......................................................... ........................................................2................. Source: PNAD - IBGE CESEM StaUstical Annex.xls CECA P1-83/16/00 11:38 AM Table 61. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Metropolitan Periphery Indigence Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) ......... .........................................I........I .....................................................................................................................................................................................................I........................................................ Total 590095 107.07 41.86 16.23 8.59 100.00 100.00 100.00 100.00 ........... ................................................. ................. ...................................................................... ................................................................................................................................................ ............ Dependency Ratio 1 27043 324.22 0.00 0.00 0.00 4.58 0.00 0.00 0.00 14 133946 50.32 78.54 35.55 19.75 22.70 42.59 49.72 52.18 Other/Not Specified 18738 24.30 96.59 67.07 50.91 3.18 7.33 13.12 18.81 Housing Own Huse already Paid with Own L 322836 106.57 39.18 15.12 8.02 54.71 51.21 50.97 51.03 Own House already Paid without Ow 44082 55.04 77.78 30.59 14.97 7.47 13.88 14.08 13.01 Own House Still Paid 120536 145.37 28.45 9.35 5.15 20.43 13.88 11.77 12.24 Rent 46208 101.95 36.40 12.64 6.03 7.83 6.81 6.10 5.50 Ceded 56433 72.99 62.26 28.97 16.38 9.56 14.22 ................1 7.07 ...4 18.23 Water Canalized 356910 133.75 27.98 9.40 4.59 60.48 40.43 35.03 32.30 No Canalized 233185 66.25 63.10 26.68 14.72 39.52 59.57 64.97 67.70 ................................. ii ................................................,,,,,............... , .................. . . .............. 4 6 ............. . .i ........ ..............8.5,i............................... Sanittion Sewage System 86871 161.06 28.26 8.96 4.58 14.69 9.91 8.11 7.83 ConcreteCesspit1 52387 121.92 28.86 11.24 6.47 8.88 6.12 6.15 6.68 Concrete Cesspit 2 53027 129.61 40.56 16.21 8.34 8.99 8.71 8.98 8.73 Rudimental Cesspit 326880 99.08 40.39 14.28 7.04 55.39 53.45 48.73 45.36 Drain 6389 62.44 76.66 25.45 10.24 1.08 1.98 1.70 1-29 River or Lake 639 17.45 100.00 73.18 53.55 0.11 0.26 0.49 0.67 Not Specified 64102 49.42 75.42 38.61 23.29 10.86 19.57 25.84 29.44 Eletricity Yes 567310 109.29 40.47 15.51 8.12 96.14 92.93 91.87 90.86 No 22785 51.93 76.63 34.17 20.35 3.86 7.07 8.13 9.14 Garbage Collected Directly 280674 132.16 29.29 11.23 6.21 47.56 33.28 32.91 34.38 Collected Indirectly 29171 112.50 47.44 12.39 6.06 4.94 5.60 3.77 3.49 Burned 96254 73.53 60.62 26.25 13.21 16.31 23.62 26.39 25.07 Unused Plot of Land 168663 85.62 52.78 20.26 10.78 28.58 36.04 35.69 35.86 Other/Not Specified 15333 84.07 23.60 7.76 3.97 2.60 1.47 1.24 1.20 Source: PNAD - IBGE CESEM Statistical Annex.xls CEPE INO - 8/16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Metropolitan Periphery Indigence Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) ....................................................................................... 9 0 9 .............10 7...................................................................................................................................... Total 590095 1~~~~~ ~ ~~~~~~~~~~~~~~~~~~~~~~070 41.86 16.23 8.59 100.00 100.00 100.00 100.00 Gender Men 474885 105.81 43.77 17.24 9.13 80.48 84.14 85.50 85.52 Women 115210 112.27 34.01 12.05 6.37 19.52 15.86 14.50 14.48 ~ ~ ~ ~ ~~~~~~~~~~~~~~ ...............................................................................................................................................................I................................................................................................................................ Race White 176961 120.63 34.54 13.30 7.01 29.99 24.74 24.58 24.45 Black 411004 101.18 45.23 17.57 9.32 69.65 75.26 75.42 75.55 Yellow 1065 122.36 0.00 0.00 0.00 0.18 0.00 0.00 0.00 Not Specified 1065 113.12 0.00 0.00 0.00 0.18 0.00 0.00 0.00 ........................... ~ ..... ........... .......................................................................................................................... ......................................................................................... .....q............... .............................. Age 24 Years orLess 28966 101.12 36.03 12.22 6.27 4.91 4.22 3.70 3.58 25to44Years 297065 105.97 44.95 19.24 10.45 50.34 54.05 59.69 61.19 45 to 64 Years 204649 106.12 40.69 13.52 6.66 34.68 33.71 28.88 26.89 65 Years or More 59415 118.79 33.33 12.46 7.12 10.07 8.02 7.73 8.34 Yea of Schooling Less than i Year 163972 67.77 58.44 2265 11.18 27.79 38.79 38.79 36.14 1 to4Years 148434 86.17 52.94 21.90 12.35 25.15 31.81 33.94 36.16 4to8Years 165036 109.66 33.94 12.45 6.78 27.97 22.67 21.45 22.08 8 toc2 Years 100902 169.99 i4.54 4.74 2.45 16.12 6.29 5.29 5.16 More than 12 Years 5751 523.49 18.52 8.78 4.16 0.97 0.43 0.53 0.47 immigration No Immi grant 7057 94. 87 52. 31 20. 0 130.4828.91 36.12 .3615.35.24 0 to 5 Years 108389 107.83 32.61 14.96 8.52 18.37 14.31 16.93 18.20 6 to 9 Years 71978 113.45 44.08 13.23 5.38 12.20 12.85 9.94 7.63 More Than 10 Years 215941 104.07 40.23 15.97 8.98 36.59 35.17 36.02 38.22 Other/Not Specified 23211 201.44 16.51 3.94 1.54 3.93 1.55 0.96 0.70 Working Class Inactive 118192 98.62 37.48 14.40 8.53 20.03 17.93 17.78 19.88 Unemployed 22357 98.22 80.00 39.90 25.47 3.79 7.24 9.31 11.23 Formal Emploees 146088 108.74 32.65 9.97 4.00 24.76 19.31 15.21 11.51 Informal Employees 94127 82.68 55.20 19.65 9.03 15.95 21.04 19.32 16.76 Self-Employed 141186 120.49 40.42 18.19 10.49 23.93 23.10 26.81 29.20 Employer 10646 194.12 12.01 4.48 1.67 1.80 0.52 0.50 0.35 Public Servant 51535 123.22 42.98 15.14 7.18 8.73 8.97 8.15 7.30 Unpid 596 3.227.57 4.85 3.11.01 1.90 2.592 , .4, 3.782,? E_mploymentTenure OYears 140549 98.56 44.24 18.46 11.22 23.82 25.17 27.09 31.11 1 Years or More 88172 91.38 44.44 15.60 7.67 14.94 15.86 14.36 13.33 1 to 3 Years 112649 86.25 47.64 18.62 9.71 19.09 21.72 21.90 21.57 3 to 5 Years 45572 137.36 32.24 14.46 7.51 7.72 5.95 6.88 6.75 Morethan5Years 200171 125.66 37.23 13.53 6.53 33.92 30.17 28.28 25.79 Other/Not Specified 2982 48.58 92.86 47.75 24.77 0.51 1.12 1.49 1.46 .................................................................................................................................................... ......................... .................................................... ...... .............................. ............................................................. ............ .................... Enterprise Size 1 5749 123.82 22.23 8.30 3.10 0.97 0.52 0.50 0.35 2 a 5 41097 105.02 49.74 15.93 6.83 6.96 8.27 6.84 5.54 6 a 10 10221 107.32 20.82 4.72 1.20 1.73 0.86 0.50 0.24 Other/Not Specified 533028 107.05 41.87 16.56 8.93 90.33 90.35 92.16 93.87 .. ......................................................................... ........ ............................................................ .............................. ........... ....... ........A ......~ 9 0 3 ..... 0 3 2 1 3 8 Sector of Activity Agriculture 37478 53.85 73.87 31.06 16.88 6.35 11.21 12.16 12.47 Manufacturing 83691 87.70 47.84 18.80 9.68 14.18 16.21 16.43 15.98 Construction 63891 93.67 35.67 10.40 4.83 10.83 9.22 6.94 6.09 Services 216570 128.20 34.51 13.23 6.48 36.70 30.26 29.93 27.65 Public Sector 47916 129.89 40.89 14.89 7.09 8.12 7.93 7.45 6.70 Other/Not Specified 140549 98.56 44.24 18.46 11.22 23.82 25.17 27.09 31.11 ........................ ......I............................................................................... ... ................................................ .......................I........... ....................I................................. .......................... Source: PNAD - IBGE CESEM Statistical Annex.xls CEPE IND - 8/16t00 11:38 AM Table 62.- POVERTY PROFILE - 1996 CEARA With Inputed Rent Metropolitan Periphery Low Poverty Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita PO P1 P2 Population P0 P1 P2 Household Population Eamings (%) (%) (%) (%) (%) (%) (e) ........................I......I..........................................................- .............................................................I.................................................................................................................................I................................ Total 590095 107.07 76.72 39.44 24.64 100.00 100.00 100.00 100.00 Dependency Ratio 1 27043 324.22 16.54 1.83 0.38 4.58 0.99 0.21 0.07 14 133946 50.32 96.03 64.18 45.63 22.70 28.41 36.94 42.03 Other/Not Specified 18738 24.30 97.73 82.20 70.75 3.18 4.04 6.62 9.12 Housing Ow House already Paid with Own L 322836 106.57 77.38 38.60 23.67 54.71 55.17 53.54 52.54 Own House already Paid without Ow 44082 55.04 94.20 59.16 40.32 7.47 9.17 11.21 12.22 Own House Still Paid 120536 145.37 62.19 28.58 16.65 20.43 16.56 14.81 13.80 Rent 46208 101.95 78.80 36.99 21.63 7.83 8.04 7.35 6.87 Ceded 56433 72.99 88.68 54.03 37.51 9.56 11.05 13.10 14.5 Water Canalized 356910 133.75 67.60 30.16 17.13 60.48 53.29 46.25 42.05 No Canalized 233185 66.25 90.69 53.64 36.14 39.52 46.71 53.75 57.95 Sanitation Sewage System 86671 161.06 60.20 27.16 15.93 14.69 11.52 10.12 9.50 Concrete Cesspit 1 52387 121.92 64.64 29.79 17.83 8.88 7.48 6.71 6.43 Concrete Cesspit 2 53027 129.61 66.67 37.14 23.83 8.99 7.81 8.46 8.69 Rudimental Cesspit 326880 99.08 80.91 39.42 23.51 55.39 58.42 55.37 52.85 Drain 6389 62.44 83.33 54.32 36.18 1 08 1.18 1.49 1.59 RiverorLake 639 17.45 100.00 86.78 75:30 0.11 0.14 0.24 0.33 Not Specified 64102 49.42 95.02 63.93 46.77 10.86 13.45 17.61 20.62 Eletricity Yes 567310 109.29 75.94 38.56 23.89 96.14 95.16 94.01 93.20 No 22785 51.93 96.26 61.18 43.42 3.86 4.84 5.99 6.80 Garbage Collected Directly 280674 132.16 66.39 30.00 17.94 47.56 41.16 36.18 34.63 Collected Indirectly 29171 112.50 78.83 41.30 24.43 4.94 5.08 5.18 4.90 Bumed 96254 73.53 88.50 53.68 35.87 16.31 18.81 22.20 23.75 Unused Plot of Land 168663 85.62 85.35 46.48 29.75 28.58 31.80 33.69 34.51 OtherlNot Specified 15333 84.07 93.05 41.72 21.03 2.60 3.15 2.75 2.22 Source: PNAD - IBGE CESEM Statistical Annex.xis CEPE PL - 8M16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Metropolitan Periphery Low Poverty Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) Total 590095 107.07 76.72 39.44 24,64 100.00 100.00 100.00.100.00 Gender Men 474885 105.81 76.77 40.35 25.55 80.48 80.53 82.34 83.44 Women 115210 112.27 76.53 35.68 20.91 19.52 19.47 17.66 16.56 ace White 176961 120.63 71.12 34.08 20.77 29.99 27.80 25.92i 25.2 Black 411004 101.18 79.02 41.89 26.43 69.65 71.73 73.98 74.70 Yellow 1065 122.36 100.00 7.28 0.53 0.18 0.24 0.03 0.00 Not Specified 1065 113.12 101.00 14.43 2.06 0.18 0.24 0.07 0.02 Age 24 Years or Less 28966 10112 73.53 34.33 20.21 4.91 4.70 4.27 4.03 25 to 44 Years 297065 105.97 76.85 41.72 27.13 50.34 50.42 53.26 55.42 45 to 64 Years 204649 106.12 78.05 37.89 22.51 34.68 35.28 33.32 31.68 65 YearsorMore 59415 118.79 73.12 35.84 21.73 10.07 9.60 9.15 8.88 Years of Schooling Less than i Year 163972 67.77 90.39 51.49 33.20 27.79 32.74 36.28 37.44 1 to4Years 148434 86.17 84.94 47.61 31.11 25.15 27.85 30.37 31.76 4 to 8 Years 165036 109.66 73.42 34.17 20.44 27.97 26.76 24.23 23.19 8 to12 Years 106902 169.99 52.39 19 09 9 79 18.12 12.37 8.77 7.20 More than 12 Years 5751 523.49 22.22 14.27 10.24 0.97 0.28 0.35 0.41 immigration No Immigrant 170576 94.87 80.78 45.56 29.57 28.91 30.43 33.39 34.68 0 to 5 Years 108389 107.83 74.66 37.09 22.83 18.37 17.87 17.28 17.02 6to9Years 71978 113.45 72.19 35.97 21.60 12.20 11.48 11.13 10.69 More Than 10 Years 215941 104.07 78.30 39.08 24.23 36.59 37.35 36.26 35.99 Other/Not Specified 23211 201.44 55.97 19.51 10.10 3.93 2.87 1.95 1.61 orking Class inactive 118192 98.62 78.02 38.47 23.73 20.03 20.37 19.54 19.29 Unemployed 22357 98.22 88.57 62.83 47.66 3.79 4.37 6.04 7.33 Formal Emploees 146088 108.74 75.95 33.35 18.50 24.76 24.51 20.94 18.59 Informal Employees 94127 82.68 87.78 47.93 29.95 15.95 18.25 19.39 19.39 Self-Employed 141186 120.49 71.19 38.61 25.23 23.93 22.20 23.42 24.50 Employer 10646 194.12 40.00 17.75 9.47 1.80 0.94 0.81 0.69 Public Servant 51535 123.22 70.66 36.43 22.55 8.73 8.04 8.07 7.99 Unpaid 5964 39.22 100.00 70.29 54.09 1.01 1.32 1.80 2 .22 Employment Tenure 0 Years 140549 98.56 79.70 42.35 27.54 23.82 24.74 25.57 26.62 1 Years or More 88172 91.38 81.16 40.57 24.66 14.94 15.81 15.37 14.96 1 to3Years 112649 86.25 86.96 45.83 28.58 19.09 21.64 22.19 22.14 3 to 5 Years 45572 137.36 63.55 31.14 19.99 7.72 6.40 6.10 6.27 More than 5 Years 200171 125.66 69.68 34.72 21.00 33.92 30.81 29.87 28.91 Other/Not Specified 2982 48.58 92.86 70.62 53.76 0.51 0.61 0.90 1.10 Enterprise Size 1 5749 123.82 51.85 27.06 16.02 0.97 0.66 0.67 0.63 2a5 41097 105.02 79.79 41.66 25.43 6.96 7.24 7.36 7.19 6 a 10 10221 107.32 62.50 24.80 12.14 1.73 1.41 1.09 0.85 Other/Not Specified 533028 107.05 77.03 39.68 24.91 90.33 90.69 90.88 91.33 ....................................................................................... ........................... ................................-................................................. ................................................................................................................. .......... Sector of Activity Agriculture 37478 53.85 97.73 60.39 41.44 6.35 8.09 9.73 10.68 Manufacturing 83691 87.70 84.23 43.87 27.73 14.18 15.57 15.78 15.96 Construction 63891 93.67 87.33 38.52 20.63 10.83 12.32 10.57 9.07 Services 216570 128.20 66.77 33.37 20.44 36.70 31.94 31.05 30.44 Public Sector 47916 129.89 69.33 35.43 21.95 8.12 7.34 7.29 7.23 Other/Not Specified 140549 98.56 79.70 42.35 27.54 23.82 24.74 25.57 26.62 .........................................................-1...............I................... ................. ...........................................................I............................. ........................................................................................................................... Source: PNAD - IBGE CESEM Statistical Annex.xls CEPE PL - 8/16/00 11:38 AM Table 63. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Large Urban Indigence Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita P0 P1 PZ Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) ................................................... .................................................................................................................................................................................I.............. .......................................I............................ Total 293577 166.95 30.87 11.09 6.36 100.00 100.00 100.00 100.00 .. .............. ........................... ............................................................................................................... ..............................................."............I............................................................................................... Dependency Ratio 1 20665 434.83 0.00 0.00 0.00 7.04 0.00 0.00 0.00 14 34974 82.40 57.58 27.02 14.92 11.91 22.22 29.04 27.96 Other/Not Specified 7419 9.09 100.00 86.03 76.55 2.53 8.19 19.61 30.43 ................................................... ~....... ..........I......................................................................................................................................................................................................... Housing Own House already Paid with Own L 147850 196.82 26.16 6.33 3.41 50.36 42.69 28.74 27.03 Own House already Paid without Ow 38684 45.78 75.34 43.25 30.17 13.18 32.16 51.40 62.53 Rent 73126 169.11 23.19 6.92 2.15 24.91 18.71 15.55 8.44 Ceded 33917 170.33 17.19 4.14 1.11 11.55 6.43 4.31 2.01 Water Canalized 278738 172.37 30.04 9.77 5.22 94.95 92.40 83.70 77.93 No Canalized 14839 65 . ....... ........ 46.43 35.75 27.75 5.0 7.60 16.30 22.06 Sanitation SewageSystem 33382 105.96 31.75 3.67 0.67 11.37 11.69 3.76 1.19 Concrete Cesspit 1 28615 334.91 14.81 2.12 0.30 9.75 4.68 1.86 0.46 Concrete Cesspit 2 20669 400.89 0.00 0.00 0.00 7.04 0.00 0.00 0.00 RudimentalCesspit 180175 143.97 28.82 11.41 6.60 61.37 57.31 63.15 63.75 Not Specified 30736 ........54.23 77.59 33.06 21.01 10.47 26.32 31._22 34.60 .................... 9......................................................... .............................................................................I...................... .................. .............................. ... .......... Eletricity Yes 281919 172.72 28.01 9.16 4.66 96.03 87.13 79.30 70.41 No , 11.658........ 27.47 1.00 57.78 47.38 3.97 12.87.9? Garbage . Collected Directly 183882 140.21 26.23 7.71 4.08 62.64 53.22 43.53 40.21 Collected Indirectly 39745 243.62 14.67 2.62 0.52 13.54 6.43 3.20 1.10 Burned 18019 600.84 0.00 0.00 0.00 6.14 0.00 0.00 0.00 Unused Plot of Land 51931 52.40 70.41 33.39 21.09 17.69 40.35 53.28 58.69 Source: PNAD - IBGE CESEM Statistical Annex.xis CEUG IND - 8/16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Large Urban Indigence Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%N (%) (%) (%) (%) (%) .. ..................................................... I............................................................................................................. .................................. ............ . ................... .............. 6 .01 0 0 0 . 00 . 0 Total. 293577 166 95 3087 11.09 6.36 100.00 100.00100.00100.00 Gender Men 225218 192.90 22.12 8.37 4.76 76.72 54.97 57.90 57.45 Women 68359 81.48 59.69 20.05 11.62 23.28 45.03 42.10 42.54 ce........................................ .................................................................................................... 0.... .................. 272.................................. ".62........ -5 2 ... . ......6 5 ...........1 7 ........... -0 64, 1 7 Race White 77902 272.85 18.37 8.62 5.22 26.54 15.79 20.64 21.77 Black 215675 128.70 35.38 11.98 677 73.46 84.21 79.37 78.23 ...................................... ............................................................. I................ ......................................... .............................. I..................................... ... .................................. .......... Age 24 Years or Less 9009 222.95 17.65 4.82 1.32 3.07 1.75 1.33 0.64 25 to 44Years 136720 128.32 26.36 13.27 9.22 46.57 39.77 55.72 67.56 45 to 64 Years 126653 184.50 36.40 8.65 3.32 43.14 50.87 33.67 22.53 65 Years or More 21195 287.51 32.50 14.24 8.17 7.22 7 60 9.27 9.28 ................ .... ....................................................................................................................... ........................................................................I............ Years of Schooling Less than 1 Year 94853 73.68 50.28 17.93 10.39 32.31 52.63 52.25 52.79 1 to4Years 65716 99.27 53.23 17.83 8.84 22.38 38.60 35.99 31.11 4to8Years 56701 167.82 14.02 6.75 5.30 19.31 8.77 11.76 16.10 8 iu1u2 Years 64i18 296.25 0.00 o.00 o.o0 21.84 0.00 0.00 0.00 More than 12 Years 12189 573.52 0.00 0.00 0.00 4.15 0.00 0.00 0.00 .................................................. .................................................................. .............................. .......... ............................................................ .......... Immigration No Immigrant 133011 158.26 32.27 12.72 7.35 45.31 47.37 51.99 52.40 0 to 5 Years 12719 164.88 54.16 41.17 35.18 4.33 7.60 16.09 23.98 6 to 9 Years 16427 149.81 41.94 10.15 2.97 5.60 7.60 5.12 2.61 More Than 10 Years 97503 177.40 29.89 7.77 3.69 33.21 32.16 23.26 19.28 Other/Not Specified 33917 180.11 14.06 3.39 0.95 11.55 5.26 3.54 1.73 ..., ............................................................................................................................... .................................................................................................................................................. ............................................. Working Class Inactive 74718 92.32 48.23 18.59 10.92 25.45 39.77 42.67 43.72 Unemployed 12189 60.60 78.26 65.87 55.66 4.15 10.53 24.67 36.36 Formal Emplooes 46103 154.35 22.99 5.36 1.56 15.70 11.70 7.59 3.84 Informal Employees 20137 94.44 21.05 0.17 0.00 6.86 4.68 0.11 0.00 Self-Employed 98564 136.28 26.88 7.23 2.77 33.57 29.24 21.89 14.63 Employer 24908 621.01 0.00 0.00 0.00 8.48 0.00 0.00 0.00 Public Servant 15369 214.84 24.14 6.53 1.77 5.24 4.09 3.08 1.45 Unpaid 1589 98.81 0.00 0.00 0.00 0.54 0.00 0.00 0.00 .........................................................................................................................................................................I.......................................... .............................................................................. ............................ Employment Tenure 0 Years 86907 87.87 52.44 25.22 17.20 29.60 50.29 67.33 80.07 1 Years or More 31796 269.95 23.33 9.08 5.28 10.83 8.19 8.87 9.00 1 to3Years 31792 186.93 18.33 3.94 1.26 10.83 6.43 3.85 2.14 3 to 5 Years 22785 147.44 0.00 0.00 0.00 7.76 0.00 0.00 0.00 More than 5 Years 120297 195.28 26.43 5.40 1.36 40.98 35.09 19.95 8.79 .............................................................................................................................................................................I..................................................I.......................I I............................................... .................. Enterprise Size 1 10069 96.76 0.00 0.00 0.00 3.43 0.00 0.00 0.00 2 a 5 22789 581.86 0.00 0.00 0.00 7.76 0.00 0.00 0.00 6 a 10 4239 653.30 0.00 0.00 0.00 1.44 0.00 0.00 0.00 Other/Not Specified 256480 124.81 35.33 12.69 7.28 87.36 100.00 100.00 100.00 ..................................... - ............................................................................................. ..., I......................... ..............I........................................................................................................................................... Sector of Activity Agriculture 6890 334.08 0.00 0.00 0.00 2.35 0.00 0.00 0.00 Manufacturing 37628 109.26 38.03 9.90 2.72 12.82 15.79 11.45 5.47 Construction 13250 97.10 36.00 12.14 4.10 4.51 5.26 4.94 2.91 Services 136184 227.91 19.07 3.89 1.58 46.39 28.65 16.28 11.54 Public Sector 12718 207.61 0.00 0.00 0.00 4.33 0.00 0.00 0.00 Other/Not Specified 86907 87.87 52.44 25.22 17.20 29.60 50.29 67.33 80.07 Source: PNAD - IBGE CESEM Statistical Annex.xis CEUG IND - 8/16/00 11:38 AM Table 64. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Large Urban Low Poverty Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita PO Pi P2 Population PO P1 P2 Household Population Eamings (%) (%) (%) (%) (%) (%) (%) Tota 29357 166956603041.0 10.0 1 .0 10.00.0 Dependency Ratio 1 20665 434.83 17.95 2.78 0.54 7.04 1.91 0.64 0.21 14 34974 82.40 83.34 52.12 35.67 11.91 15.03 20.38 23.23 Other/Not Specified 7419 9.09 100.00 93.11 87.32 2.53 3.83 7.72 12.06 Housing Own House already Paid with Own L 147850 196.82 62.72 26.90 14.48 50.36 47.81 44.46 39.87 Own House already Paid without Ow 38684 45.78 100.00 65.31 50.17 13.18 19.95 28.24 36.13 Rent 73126 169.11 61.60 23.61 12.67 24.91 23.22 19.30 17.25 Ceded 33917 170.33 51.57 21.08 10.68 11.55 9.02 7.99 6.74 Waer Canalized 278738 172.37 64.64 29.12 17.04 94.95 92.89 90.74 88.43 No Canalized 14839 65.27 92.86 55.80 41.86 5.05 7.10 9.26 11.56 .....................................................................................................................*.................................................................................................... ..............................................--............................ ............... Sanitation Sewage System 33382 105.96 82.54 34.14 16.06 11.37 14.21 12.74 9.98 Concrete Cesspit 1 28615 334.91 37.03 12.66 5.70 9.75 5.46 4.05 3.04 Concrete Cesspit 2 20669 400.89 69.23 12.57 3.53 7.04 7.38 2.90 1.36 Rudimental Cesspit 180175 143.97 62.35 29.24 17.92 61.37 57.92 58.90 60.11 Not Specified 30736 54.23 94.83 62.31 44.58 10.47 15.03 21.41 25.51 i i i .................... ............................... .......................................................................................I........................................................................I.................................................. ...................................... Eletricity Yes 281919 172.72 64.66 28.46 16.32 96.03 93.99 89.68 85.65 No 11658 27.47 100.00 79.18 66.10 3.97 6.01 10.32 14.35 Garbage Collected Directly 183882 140.21 61.10 26.91 15.14 62.64 57.92 55.31 51.84 Collected Indirectly 39745 243.62 66.66 16.12 6.50 13.54 13.66 7.16 4.81 Burned 18019 600.84 26.47 11.32 5.11 6.14 2.46 2.28 1.71 Unused Plot of Land 51931 52.40 96.94 60.73 43.07 17.69 25.96 35.25 41.64 .... ........................ ........ Source: PNAD - IBGE CESEM Statistical Annex.xis CEUG PL - 8/16/00 11 38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Large Urban Low Poverty Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita PO Pi P2 Population PO P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) ........ ............................................................................................................................................................. ... ........................... ........ ...I........................1 R ....... R 2 ........! :9 ......... 9 9 Total,,,,,29,,577,,,166.95,,,,,66.07,,,,30.47,,,,,16.30,,,,100.00,,,,,100.00,,,,100.00,,,, 100.006 9 Gender Men 225218 192.90 60.00 25.79 14.75 76.72 69.67 64.92 61.83 Women 68359 81.48 86.05 45.90 29.99 23.28 30.33 35.08 38.17 e~ ~ ~ ~ ~~~~~~~o ! White ,,79,2,,,,,,.....,,,7,,,,2,,,,.............,,,,,.......,,8,6.....,,..35,..9......43.......................11...24........... Race White 77902 272.85 54.42 21.17 12.58 26.54 21.86 18.43 18.24 Black 215675 128.70 70.27 33.83 20.38 73.46 78.14 81.57 81.76 Age 24 Years or Less 9009 222 95 47.06 25.82 14.42 3.07 2.19 2.60 2.42 25to44Years 136720 128.32 68.22 29.63 18.73 46.57 48.09 45.29 47.69 45to64Years 126653 184.50 64.43 31.08 17.56 43.14 42.08 44.00 41.42 65YearsorMore 21195 287.51 70.00 34.22 21.49 7.22 7.65 8.11 8.48 ............ -............................................ .............................................I.......................... .............................................. ................................. ...... .....I............................................................................ Years of Schooling Less than 1 Year 94853 73.68 92.74 45.99 28.60 32.31 45.35 48.77 50.50 1 to 4 Years 65716 99.27 76.61 43.85 28.11 22.38 25.96 32.21 34.39 4to8Years 56701 167.82 46.73 18.03 10.66 19.31 13.66 11.43 11.26 8 to12 Years 64118 296.25 41.32 9.88 3.10 21.84 13.66 7.08 3.70 More than 12 Years 12189 573S.2 21.73 3.78 0.66 4.15 i.37 O.52 0.15 ..... .............................................................................I.......................... ............................I................................................................................I.................................... ........................................................ ............. Immigration No Immigrant 133011 158.26 79.28 36.12 21.31 45.31 54.37 53.71 52.78 O to 5 Years 12719 164.88 70.83 53.87 45.48 4.33 4.64 7.66 10.77 6 to 9 Years 16427 149.81 64.52 30.52 17.50 6.60 5.46 6.60 5.35 More Than 10 Years 97503 177.40 60.33 25.99 14.66 33.21 30.33 28.32 26.62 Other/Not Specified 33917 180.11 29.68 12.41 7.10 11.55 5.9 4.71 4.48 Working Class Inactive 74718 92.32 78.72 41.15 26.67 25.45 30.33 34.37 37.09 Unemployed 12189 60.60 86.96 76.32 68.58 4.15 5.46 10.40 15.56 Formal Emploees 46103 154.35 68.97 24.13 11.74 15.70 16.39 12.43 10.08 Informal Employees 20137 94.44 84.21 33.94 15.43 6.86 8.74 7.64 5.78 Self-Employed 98564 136.28 57.53 26.00 14.42 33.57 29.24 28.65 26.45 Employer 24908 621.01 40.43 10.79 4.19 8.48 5.19 3.00 1.94 Public Servant 15369 214.84 48.27 17.83 10.14 5.24 3.83 3.06 2.90 Unpaid 1589 98.81 100.00 25.13 6.32 0.54 0.82 0.45 0.19 J ................................................ .......................................................I...... ................................................................. ............-....................................................I................................ ...................I................. EmploymentTenure 0 Years 86907 87.87 79.88 46.08 32.54 29.60 35.79 44.77 52.66 1 Years or More 31796 269.95 53.33 24.22 15.01 10.83 8.74 8.61 8.88 I to 3 Years 31792 186.93 45.00 17.82 8.89 10.83 7.38 6.33 5.26 3 to 5 Years 22785 147.44 58.14 18.55 7.24 7.76 6.83 4.72 3.07 Morethan5Years 120297 195.28 66.52 26.45 13.45 40.98 41.26 35.57 30.13 ..........I........................................ ................... ..........................................................................................................I.........................................................................I............................................................. Enterprise Size 1 10069 96.76 100.00 26.68 10.35 3.43 5.19 3.00 1.94 2 a 5 22789 581.86 34.88 9.63 3.89 7.76 4.10 2.45 1.65 6 a iO 4239 653.30 0.00 0.00 0.00 1.44 0.00 0.00 0.00 Other/Not Specified 256480 124.81 68.60 32.98 20.19 87.36 90.71 94.54 96.41 ...........I........ .............................. .................................................................................................................................................................................................................................................................. Sector of Activity Agriculture 6890 334.08 69.23 32,34 15.11 2.35 2.46 2.49 1.94 Manufacturing 37628 109.26 90.14 39.62 21.42 12.82 17.49 16.66 15.00 Construction 13250 97.10 80.00 36.82 20.26 4.51 5.47 5.45 5.00 Services 136184 227.91 50.20 19.32 9.87 46.39 35.24 29.40 25.02 Public Sector 12718 207.61 54.16 8.60 1.62 4.33 3.55 1.22 0.38 Other/Not Specified 86907 87.87 79.88 46.08 32.54 29.60 35.79 44.77 52.66 ..................................... ..... .................... ..... ....................................I.............................................. ..... ...........................I........................ ..I................................. .......... .................... Source: PNAD - IBGE CESEM Statistical Arinex.xls CEUG PL - 8/16/00 11:38 AM Table 65. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Medium Urban Indigence Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) ..........................................I..............................................................................................................................................I..........................................I................................................................................ ........... Total 468956 132.19 47.68 18.58 9.44 100.00 100.00 100.00 100.00 .... ............................................................ ........................I ................................................................I................................................................................................................................................................ Dependency Ratio 1 33916 340.53 4.69 0.51 0.06 7.23 0.71 0.20 0.04 14 100156 39.90 91.53 42.95 24.36 21.36 41.00 49.38 55.12 Other/Not Specified 2120 10.30 100.00 84.16 70.84 0.45 0.95 2.05 3.39 Housing Own House already Paid with Own L 314224 143.56 45.70 15.68 7.17 67.01 64.22 56.56 50.90 Own House already Paid without Ow 23315 58.37 68.18 40.50 27.62 4.97 7.11 10.84 14.55 Own House Still Paid 9539 74.40 61.11 24.71 10.23 2.03 2.61 2.71 2.20 Rent 60410 123.56 50.00 17.59 7.53 12.88 13.51 12.20 10.27 Ceded 55640 130.80 40.00 19.09 10.48 11.86 9.95 12.19 13.18 Other 5828 11.57 100.00 82.22 67.60 1.24 2.61 5.50 8.90 Water Canalized 294099 178.63 31.89 10.79 4.89 62.71 41.95 36.41 32.47 No Canalized 174857 54.08 74.24 31.68 17.10 37.29 58.05 63.58 67.53 Sanitation Sewage System 11130 225.66 23.81 6.33 1.68 2.37 1.19 0.81 0.42 Concrete Cesspit 1 1060 606.83 0.00 0.00 0.00 0.23 0.00 0.00 0.00 ConcreteCesspit2 117110 181.21 19.91 9.12 4.96 24.97 10.43 12.26 13.12 Rudimental Cesspit 242691 133.15 50.00 15.89 6.54 51.75 54.26 44.26 35.86 Drain 11126 94.62 61.91 18.45 7.38 2.37 3.08 2.36 1.85 Not Specified 85839 49.49 80.86 40.91 25.14 18.30 31.04 40.31 48.74 Eletricity Yes 426566 141.04 43.35 15.87 7.60 90.96 82.70 77.69 73.23 No 42390 43.09 91.25 45.86 27.95 9.04 17.30 22.31 26.77 Garbage Collected Directly 276077 158.23 38.58 14.35 6.85 58.87 47.63 45.47 42.71 Collected Indirectly 48223 145.65 21.98 7.59 3.03 10.28 4.74 4.20 3.30 Burned 40270 134.95 68.42 24.67 10.56 8.59 12.32 11.40 9.61 Unused Plot of Land 102267 56.55 75.13 32.10 18.68 21.81 34.36 37.68 43.15 Other/Not Specified 2119 32.03 100.00 50.78 25.79 0.45 0.95 1.24 1.23 Source: PNAD - IBGE CESEM Statistical Annex.xis CEUM IND - 8/16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Medium Urban Indigence Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita PO P1 P2 Population PO P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) ........... ..........................I............I............. .........................................................................................I..........................................I............................................................ ...................................................I............... Total 468956 132.19 47.68 18.58 9.44 100.00 100.00 100.00 100.00 ...................... ..........................I...................................................: II..........................................................................I................................................................................................................................ Gender Men 385764 136.46 46.98 17.67 8.28 82.26 81.04 78.23 72.13 Women 83192 112.41 50.96 22.80 14.83 17.74 18.96 21.77 27.87 .................................................................................................................................. .................................. .............. ............. ....... .............. ........I I..................................... Race Indigenous 3179 42.47 100.00 34.74 12.07 0.68 1.42 1.27 0.87 White 145722 141.70 42.55 16.34 8.41 31.07 27.73 27.34 27.67 Black 320055 128.75 49.50 19.43 9.88 68.25 70.85 71.40 71.46 Age 24 Years or Less 30731 96.37 36.20 19.26 10.32 6.55 4.98 6.80 7.16 25 to 44 Years 213025 128.25 59.45 24.45 13.38 45.43 56.64 59.80 64.39 45to64Years 166384 136.77 40.44 14.11 6.27 35.48 30.09 26.95 23.55 65 Years or More 58816 152.24 31.53 9.56 3.69 12.54 8.29 6.45 4.90 .........I..............................I............ ...... ............................I........................ ..........................................................................I.............................. .................................................................................. Years of Schooling Less than 1 Year 135115 68.14 69.02 26.41 12.59 28.81 41.70 40.96 38.43 1to4Years 145189 75.00 55.11 22.80 12.21 30.96 35.78 38.01 40.03 4 to 8 Years 102273 128.22 35.75 13.64 7.58 21.81 16.35 16.01 17.50 8 to12 Years 75251 204.59 18.31 5.81 2.38 16.05 6.16 5.02 4.05 More than 12 Years 11128 1202.90 0.00 0.00 0.00 2.37 0.00 0.00 0.00 immigration No Immigrant 335426 125.64 53.55 20.83 10.72 71.53 80.33 80.22 81.25 Oto5Years 29144 133.18 47.27 11.34 3.98 6.21 6.16 3.79 2.62 6 to 9 Years 15367 91.16 48.29 17.90 7.53 3.28 3.32 3.16 2.61 More Than 10 Years 77360 138.09 27.40 13.70 7.46 16.50 9.48 12.16 13.04 Other/Not Specified 11659 333.22 13.64 4.96 1.80 2.49 0.71 0.66 0.48 Working Class Inactive 98024 92.45 51.89 27.25 17.67 20.90 22.75 30.66 39.13 Unemployed 11657 44.27 86.36 41.76 21.03 2.49 4.50 5.59 5.54 Formal Emploees 41865 89.74 36.71 15.24 7.74 8.93 6.87 7.32 7.32 Informal Employees 81076 76.61 62.74 21.44 9.74 17.29 22.75 19.96 17.83 Self-Employed 135124 113.22 47.45 16.71 7.29 28.81 28.67 25.91 22.26 Employer 39210 260.88 32.43 4.41 0.71 8.36 5.69 1.98 0.63 Public Servant 40805 365.04 23.38 7.62 2.79 8.70 4.27 3.57 2.57 Unpaid 21195 95.38 47.51 20.58 9.87 4.52 4.50 5.01 4.73 .......................I..................................... ......... ... ............................................................................................ ........................... ....... . ......................... : .......... : 2 ........4 55 0 14 7 Employment Tenure 0 Years 109681 87.33 55.56 28.79 18.03 23.39 27.25 36.25 44 66 1 Years or More 60944 98.86 57.39 18.31 8.19 13.00 15.64 12.81 11.27 1 to3Years 51937 113.54 46.94 16.88 6.79 11.08 10.90 10.06 7.96 3 to 5 Years 22787 125.37 37.21 14.83 6.61 4.86 3.79 3.88 3.40 More than 5 Years 212479 173.25 41.39 13.55 6.00 45.31 39.33 33.05 28.79 Other/Not Specified 11128 73.92 61.91 30.93 15.53 2.37 3.08 3.95 3.90 ........................................ ................... ........ ................ ..........................................................................I...................... ................................................................................I..................................................... Enterprise Size 1 18545 289.25 40.00 4.06 0.42 3.95 3.32 0.86 0.18 2 a 5 30204 153.52 56.14 21.58 10.47 6.44 7.58 7.48 7.14 6alO 14838 148.24 0.00 0.00 0.00 3.16 0.00 0.00 0.00 Other/Not Specified 405369 122.83 49.15 19.70 10.12 86.44 89.10 91.65 92.68 ................."........ ...............I......................... ....................................................................I..........................I..............................I............................................................................I..................................................... Sectorof Activity Agriculture 64645 97.42 66.40 22.63 9.41 13.78 19.19 16.79 13.74 Manufacturing 56168 86.54 54.71 21.68 10.08 11.98 13.74 13.98 12.79 Construction 38685 85.84 47.94 16.90 7.67 8.25 8.29 7.51 6.70 Services 164270 141.56 40.32 12.83 5.72 35.03 29.62 24.19 21.22 Public Sector 35507 413.45 11.94 3.16 1.10 7.57 1.90 1.29 0.88 Other/Not Specified 109681 87.33 55.56 28.79 18.03 23.39 27.25 36.25 44.66 .......................................................I..................................I........... .............................. ..........................................................................................................................I.................................I............................... Source: PNAD - IBGE CESEM Statistical Annex.xis CEUM IND - 8/16/00 11:38 AM Table 66. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Medium Urban Low Poverty Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (') (%) (%) (%) (%) (%) (%) ........................... .................... ............................................................................................................................................................................................................................... Total 468956 132.19 76.61 41.31 26.68 100.00 100.00 100.00 100.00 Dependency Ratio 1 33916 340.53 31.25 6.61 2.51 7.23 2.95 1.16 0.68 14 100156 39.90 100.00 69.77 51.61 21.36 27.88 36.07 41.31 Other/Not Specified 2120 10.30 100.00 92.19 84.99 0.45 0.59 1.01 1.44 Housing Own House already Paid with Own L 314224 143.56 76.22 39.32 24.30 67.01 66.67 63.77 61.02 Own House already Paid without Ow 23315 58.37 86.37 55.92 44.60 4.97 5.60 6.73 8.31 Own House Still Paid 9539 74.40 83.33 45.62 30.82 2.03 2.21 2.25 2.35 Rent 60410 123.56 73.68 41.05 26.11 12.88 12.39 12.80 12.60 Ceded 55640 130.80 74.28 40.78 26.62 11.86 11.50 11.71 11.84 Other 5828 11.57 100.00 91.23 83.23 1.24 1.62 2.74 3.88 Water Canalized 294099 178.63 64.87 30.08 17.74 62.71 53.10 45.66 41.69 No Canalized 174857 54.08 96.36 60.21 41.72 37.29 46.90 54.34 58.31 Sanittion SewageSystm 11130 225.66 23.81 15.19 9.69 2.37 0.74 0.87 0.86 Concrete Cesspit 1 1060 606.83 0.00 0.00 0.00 0.23 0.00 0.00 0.00 ConcreteCesspit2 117110 181.21 48.42 19.63 12.12 24.97 15.78 11.87 11.35 Rudimental Cesspit 242691 133.15 85.37 44.60 26.75 51.75 57.67 55.87 51.89 Drain 11126 94.62 90.47 46.42 28.16 2.37 2.80 2.67 2.50 Not Specified 85839 49.49 96.30 64. .68 18.30 23.01 28.72 33.40 Eletricity Yes 426566 141.04 74.66 38.53 24.04 90.96 88.64 84.83 81.97 No 42390 43.09 96.25 69.33 53.21 9.04 11.36 15.17 18.03 Garbage Collected Directly 276077 158.23 68.71i 34.93i21.67 58.87 52.80 49.77647.82 Collected Indirectly 48223 145.65 75.82 28.20 14.61 10.28 10.18 7.02 5.63 Burned 40270 134.95 89.47 50.55 33.36 8.59 10.03 10.51 10.74 Unused Plot of Land 102267 56.55 92.75 60.40 42.62 21.81 26.40 31.88 34.84 OtherlNot Specified 2119 32.03 100.00 75.73 57.35 0.45 0.59 0.83 0.97 Source: PNAD- IBGE CESEM Statistical Annex.xis CEUM PL - 8/16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Medium Urban Low Poverty Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) ............................................................................................................................................................................................................................ Total 468956 132.19 76.81 41.31 26.68 100.00 100.00 100.00 100.00 ............ .................................................... ......................................................................................................... ............................................... , 96..........0 ,,5.8382 2 1 5 1 0 9 6 Gender Men 385764 136.46 75.96 40.69 25.83 82.26 81.56 81.01 79.64 Women 83192 112.41 79.62 44.22 30.63 17.74 18.44 18.99 20.36 .. ......................................................... ........ ......................................... I................................................................. ............................ ....... . ... f 6 ........ ................................ Race Indigenous 3179 42.47 100.00 67.82 46.00 0.68 0.86 1.11 1.17 White 145722 141.70 70.55 36.21 23.17 31.07 28.61 27.23 26.99 Black 320055 128.75 79.14 43.38 28.09 68.25 70.50 71.65 71.84 .......................................................................... ....... ........................6 i .......... W ~ ......I....... ..........................................................................................................................-.............. Age 24 Years or Less 30731 96.37 84.48 42.34 27.03 6.55 7.23 6.72 6.64 25 to 44 Years 213025 128.25 83.58 48.38 32.86 45.43 49.56 53.19 55.95 45 to 64 Years 166384 136.77 70.70 36.30 22.23 35.48 32.74 31.18 29.56 65 Years or More 58816 152.24 63.96 29.37 16.70 12.54 10.47 8.92 7.85 Years of Schooling Less than 1 Year 135115 68.14 89.41 54.49 36.38 28.81 33.63 38.00 39.29 1 to 4 Years 145189 75.00 90.15 48.50 31.90 30.96 36.43 36.35 37.01 4to8Years 102273 128.22 72.02 34.68 21.34 21.81 20.50 18.30 17.44 8 to12 Years 75251 204.59 42.96 18.60 10.36 16.05 9.00 7.22 6.23 Morethan12Years 11128 1202.90 14.29 2.18 0.33 2.37 044 0.13 0.03 immigration No immigrant 335426 12564 81.04 45.25 29.69 71.53 75.66 78.34 79.58 o to 5 Years 29144 133.18 67.27 31.69 19.03 6.21 5.46 4.77 4.43 6 to 9 Years 15367 91.16 89.66 41.10 25.18 3.28 3.84 3.26 3.09 More Than 10 Years 77360 138.09 65.07 32.09 19.74 16.50 14.01 12.81 12.20 Other/NotSpecified 11659 333.22 31.81 13.57 7.40 2.49 1.03 0.82 0.69 Working Class inactive 98024 92.45 78.38 48.12 34.44 20.90 21.38 24.35 26.98 Unemployed 11657 44.27 100.00 66.46 48.50 2.49 3.24 4.00 4.52 Formal Emploees 41865 89.74 84.81 39.27 23.15 8.93 9.88 8.49 7.74 Informal Employees 81076 76.61 88.23 51.22 32.82 17.29 19.91 21.43 21.26 Self-Employed 135124 113.22 78.43 39.41 24.68 28.81 29.50 27.48 26.65 Employer 39210 260.88 51.35 22.45 11.85 8.36 5.60 4.54 3.71 Public Servant 40805 365.04 49.35 21.72 12.40 8.70 5.61 4.57 4.04 Unpaid 21195 95.38 8250 4692 30.02 4.52 4.87 5.13 5.09 Employment Tenure 0 Years 109681 87.33 80.68 50.07 35.93 23.39 24.63 28.35 31.50 1 Years or More 60944 98.86 85.22 45.74 28.57 13.00 14.46 14.39 13.92 1to3Years 51937 113.54 76.53 41.69 26.01 11.08 11.06 11.18 10.80 3 to 5 Years 22787 125.37 76.75 35.37 21.95 4.86 4.87 4.16 4.00 More than 5 Years 212479 173.25 71.07 35.58 21.57 45.31 42.03 39.02 36.62 Other/NotSpecified 11128 7392 95.24 50.63 35.63 2.37 2.95 2.91 3.17 Enterprise Size 1 18545 289.25 51.43 23.55 12.55 3.95 2.65 2.25 1.86 2 a 5 30204 153.52 78.95 46.85 30.74 6.44 6.64 7.30 7.42 6 a 10 14838 148.24 39.28 11.65 3.57 3.16 1.62 0,89 0.42 Other/Not Specified 405369 122.83 78.95 42.80 27.87 86.44 . 89.08 89.55 90,30 Sector of Activity Agriculture 64645 97.42 90 99 50 3 Manufacturing 56168 86.54 8585 49.14 31.58 11.98 13.42 14.25 14.17 Construction 38685 85.84 82.19 44,11 27.11 8.25 8.85 8.81 8.38 Services 164270 141.56 71.29 34.14 20.61 35.03 32.60 28.94 27.06 Public Sector 35507 413.45 41.80 14.64 7.11 7.57 4.13 2.68 2.02 Other/Not Specified 109681 87.33 80.68 50.07 35.93 23.39 24.63 28.35 31.50 .. ....................... .............I......... ...... ................ .............................................3........ ........_....................................... .......... ..................... ................ ........... ..................................... ................. Source: PNAD - IBGE CESEM Statistical Annex.xis CEUM PL - 8/16/00 11:38 AM Table 67. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Small Urban Indigence Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) ........ ..................................................................... .......................... .............. ....I I7..7 4 ................I...4..............................................2.3.3................ .............. ................... ...................................................... Total 1117074 106.84 51.14 23.32 13.87 100.00 100.00 100.00 100.00 Dependency Ratio 1 102800 260.98 4.12 1.17 0.34 9.20 0.74 0.46 0.22 14 192888 64.11 80.49 51.41 35.27 17.27 27.18 38.06 43.92 Other/Not Specified 20668 7.75 100.00 88.09 78.52 1.85 3.62 6.99 10.48 Housing Own House already Paid with Own L 688899 122.35 43.54 18.24 10.21 61.67 52.50 48.23 45.42 OwnHousealreadyPaidwithoutOw 127710 42.17 79.67 47.37 34.15 11.43 17.81 23.22 28.16 Own House Still Paid 3179 42.77 100.00 34.27 11.74 0.28 0.56 0.42 0.24 Rent 165337 112.72 48.72 18.73 10.03 14.80 14.10 11.88 10.70 Ceded 130360 80.17 65.85 32.46 18.40 11.67 15.03 16.24 15.49 Other 529 104.76 0.00 0.00 0.00 0.05 0.00 0.00 0.00 Not Specified 1060 369.17 0.00 0.00 0.00 0.09 0.00 0.00 0.00 Water Canalized 819257 121.30 44.57 19.34 11.55 73.34 63.91 60.81 61. No Canalized 296757 65.98 69.46 34.41 20.32 26.57 36.09 39.19 38.93 OtherlNot Specified 1060 369.17 0.00 0.00 0.00 0.09 0.00 0.00 0.00 Sanitation Sewage System 57234 199.11 22.22 8.14 3.96 5.12 2.23 1.79 1.46 Concrete Cesspit 1 31797 337.91 0.00 0.00 0.00 2.85 0.00 0.00 0.00 Concrete Cesspit2 265488 156.52 32.73 9.80 4.44 23.77 15.21 9.98 7.61 Rudimental Cesspit 455205 85.98 53.90 24.01 14.31 40.75 42.95 41.94 42.04 Drain 11129 40.93 100.00 37.09 14.03 1.00 1.95 1.58 1.01 Other 2649 287.86 0.00 0.00 0.00 0.24 0.00 0.00 0.00 Not Specified 293572 52.09 73.29 39.67 25.26 26.28 37.66 44.70 47.87 Eletricity Yes 966045 116.50 46.68 20.66 12.08 86.48 78.94 76.61 75.33 No 149969 42.72 80.21 40.63 25.48 13.43 21.06 23.39 24.67 Other/Not Specified 1060 369.17 0.00 0.00 0.00 0.09 0.00 0.00 0.00 Garbage Collected Directly 412288 120.74 41.13 17.19 9.66 36.91 29.69 27.21 Collected Indirectly 116578 194.42 39.09 14.50 6.95 10.44 7.98 6.49 5.23 Burned 113409 74.73 67.29 29.48 16.57 10.15 13.36 12.83 12.13 Unused Plot of Land 464730 81.22 58.27 29.00 18.45 41.60 47.40 51.72 55.35 Other/Not Specified 10069 67.67 89.47 45.20 24.19 0.90 1.56 1.75 1.57 Source: PNAD - IBGE CESEM Statistical Annex.xls CEUP IND - 8/16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Small Urban Indigence Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) ' otal......................................................................................1 7074.....................I........... "'l,.................................................................................................................................................................. Total 1117074 106.84 51.14 23.32 13.87 100.00 100.00 100.00 100.00 ........................................................................................... --._..........................................................................................I................................................................................................ Gender Men 927371 107.18 52.40 24.05 14.30 83.02 85.06 85.61 85.63 Women 189703 105.16 44.97 19.77 11.73 16.98 14,93 14.39 14.36 ......................... ........................................................................................................................................................................................................................................................................... Race White 309472 157.20 31.51 11.07 5.98 27.70 17.07 13.15 11.95 Black 807602 87.54 58.66 28.02 16.89 72.30 82.93 86.84 88.05 X i... .............................................................7................................................................8-9........................9.......................6...2.7............................................ Age 24 Years or Less 43452 70.94 68.29 37.58 25.60 3.89 5.19 6.27 7.18 25 to 44 Years 447789 92.00 57.51 29.05 17.63 40.09 45.08 49.94 50.98 45 to 64 Years 449373 109.37 53.77 22.76 13.39 40.23 42.30 39.26 38.84 65 Years or More 176460 146.89 24.02 6.70 2.64 15.80 7 42 4.54 3.01 ...................................................................................................................................................................................................................................................................... Years of Schooling Less than 1 Year 545291 66.95 64.33 30.82 18.84 48.81 61.41 64.51 66.31 1 to 4 Years 261247 75.55 55.98 25.15 14.67 23.39 25.60 25.22 24.74 4to8Years 177528 138.07 37.31 13.66 7.22 15.89 11.60 9.31 8.27 8 to12 Years 110222 246.33 7.21 2.27 0.96 9.87 1.39 0.96 0.68 More than 12 Years 22786 502.07 0.00 0.00 0.00 2.04 0.00 0.00 0.00 ..................................................... ................ !~.................................................................................... .......................................... ... ... ...................I...................................... ...................... Immigration No Immigrant 765731 100.21 54.26 26.22 16.20 68.55 t(. t3 77.05 80.09 O to 5 Years 69951 126.90 43.18 22.54 13.37 6.26 5.29 6.05 6.04 6to9Years 15899 119.87 10.00 3.57 1.27 1.42 0.28 0.22 0.13 More Than 10 Years 218328 120.96 46.12 15.58 7.64 19.54 17.62 13.06 10.77 Other/Not Specified 47165 114.96 49.44 19.99 9.78 4.22 4.08 3.62 2.98 ....... ............................................................................... .................................................................. ............................ .......... .......4 441 99.74 224 03 62 ...........2 8 Working Class Inactive 258593 96.50 46.93 21.15 13.49 23.15 21.24 20.99 22.53 Unemployed 20669 21.48 100.00 66.99 50.86 1.85 3.62 5.31 6.79 Formal Emploees 43986 111.38 18.07 11.74 7.76 3.94 1.39 1.98 2.20 Informal Employees 141490 68.70 69.66 32.17 17.51 12.67 17.25 17.47 16.00 Self-Employed 493358 89.37 55.42 25.24 14.74 44.17 47.87 47.79 46.93 Employer 42925 395.86 14.82 2.87 0.64 3.84 1.11 0.47 0.18 Public Servant 81074 177.36 32.02 12.05 6.21 7.26 4.54 3.75 3.25 Unpaid 34979 110.54 48.49 16.53 9.44 3.13 2.97 2.22 2.13 Employment Tenure 0 Years 279262 90.94 50.85 24.54 16.26 25.00 24.86 26.31 29.31 1 Years or More 88499 82.04 49.10 23.99 14.67 7.92 7.61 8.15 8.38 1 to 3 Years 87443 98.21 41.21 18.83 9.90 7.83 6.31 6.32 5.59 3to5Years 78430 119.28 47.97 19.03 10.06 7.02 6.59 5.73 5.09 Morethan5Years 583440 117.83 53.50 23.89 13.71 52.23 54.64 53.49 51.63 .......I...... ....... ........................ ................................ ..... ............................... ................ .................I.........................................................I...................................................I.......................................I.............. Enterprise Size 1 11657 294.44 0.00 0.00 0.00 1.04 0.00 0.00 0.00 2 a 5 76311 152.54 49.31 20.27 10.48 6.83 6.59 5.94 5.16 6 a 10 9009 239.34 29.40 13.62 6.31 0.81 0.46 0.47 0.37 >11 9009 486.00 0.00 0.00 0.00 0.81 0.00 0.00 0.00 Other/NotSpecified 1011088 96.67 52.52 24.12 14.47 90.51 92.95 93.59 94.47 ............... ... ........... ................................................................................................................................................... ..........i.................................................................................................... Sectorof Activity Agriculture 299406 73.53 73.80 34.12 20.39 26.80 38.68 39.21 39.40 Manufacturing 41868 102.55 73.42 40.41 25.51 3.75 5.38 6.49 6.89 Construction 96973 88.27 39.89 16.74 8.69 8.68 6.77 6.23 5.44 Services 332267 138.55 37.00 15.72 8.18 29.74 21.52 20.04 17.55 Public Sector 67298 193.81 23.62 6.61 3.21 6.02 2.78 1.71 1.40 OtherNot Specified 279262 90.94 50.85 24.54 16 .26 25.00 24.86 26.31 29.31 ...................................... ..........................................................................................I.........................I.............................................................................................. Source: PNAD - IBGE CESEM Statistical Annex.xls CEUP IND - 8/16/00 11 138 AM Table 68. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Small Urban Low Poverty Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita P0 P1 P2 Population PO Pi P2 Household Population Earnings (%) (%) (%) (%) (%) (#) (%) ......................................-.............................................................................................................................................._....I........................I............... .......................... .....................I..................................... Dependency Ratio 1 102800 260.98 45.87 9.44 3.38 9.20 5.25 1.89 0.99 14 192888 64.11 87.91 '67.99 55.64 17.27 18.88 25.49 30.65 Other/Not Specified 20668 7.75 100.00 94.13 88.82 1.85 2.30 3.78 5.24 Housing Own House already Paid with Own L 688899 122.35 76.39 40.76 26.34 61.67 58.58 54.58 51.83 Own House already Paid without Ow 127710 42.17 97.93 69.84 54.84 11.43 13.92 17.33 20.01 Own House Still Paid 3179 42.77 100.00 67.59 45.69 0.28 0.35 0.42 0.41 Rent 165337 112.72 79.49 42.80 27.57 14.80 14.63 13.75 13.02 Ceded 130360 80.17 85.77 54.85 39.53 11.67 12.45 13.90 14.72 Other 529 104.76 100.00 20.62 4.25 0.05 0.06 0.02 0.01 .No Specified 1060 369.17 0.00 0.00 0.00 0.09 0.00 0.00 0.00 Watr Canaliz ed 819257 121.30 75.10 40.96 27.10 73.34 68.50 65.22 63.2 No Canalized 296757 65.98 95.36 60.30 43.16 26.57 31.50 34.78 36.58 ,,,,,,,,,,,,,,,,,,,,,,, ,,,,,,,,,.Other/Not Specified 1060 369.17 0.00 0.00 0.00 0.09 0.00 0.00 0.00 Sanitation Sewage System 57234 199.ii 62.04 24.90 13.46 5.12 3.95 2.77 2.20 Concrete Cesspit 1 31797 337.91 43.34 7.86 2.19 2.85 1.53 0.49 0.20 Concrete Cesspit 2 265488 156.52 66.67 32.52 18.55 23.77 19.70 16.78 14.07 Rudimental Cesspit 455205 85.98 84.28 47.48 32.30 40.75 42.71 42.01 42.00 Drain 11129 40.93 100.00 68.99 47.65 1.00 1.24 1.49 1.51 Other 2649 287.86 0.00 0.00 0.00 0.24 0.00 0.00 0.00 ,,,,,,,,,,,,,,,,,,,,,,,,,,,N,,,o,t Specified, ...... . . , , , ,,,,,,,,, 293572 . . 52.09 94.40 63.91 47.73 26.28 30.85 36.46 40.02 Eletricity Yes 966045 116.50 77.62 42.72 28.46 86.48 80.21 78.54 No 149969 42.72 98.94 67.89 50.10 13.43 16.52 19.79 21.46 Other/Not Specified 1060 369.17 0.00 0.00 0.00 0.09 0.00 0.00 0.00 Garbage Collected DIrecty 412288 120.74 75.71 38.80 24.92 36.91 i 47 10 93 Collected Indirectly 116578 194.42 65.91 35.90 22.41 10.44 8.55 8.13 7.46 Burned 113409 74.73 83.18 53.50 37.86 10.15 10.50 11.79 12.26 Unused Plot of Land 464730 81.22 87.34 52.76 37.25 41.60 45.19 47.66 49.45 Other/NotSpecified 10069 67.67 89.47 67.64 51.47 0.90 1.00 1.32 1.48 '~ o urce N A D IB G E...... .. .......................................................1 ............................................................................................. ........., Source: PNAD - IBGE CESEM Staflstical Annex.xis CEUP PL - 8/16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Small Urban Low Poverty Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita P0 Pi P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) ............................................................................................. I...............................................................................................I..................... ............................................................................................................. Total 1117074 106.84 8041 4606 3134 100.00 100.00 100.00 100.00 Gender Men 927371 107.18 80.57 46.63 31.99 83.02 83.19 84.04 84.73 Women 189703 105.16 79.61 43.29 28.19 16.98 16.81 15.96 15.27 Race White 309472 157.20 70.03 32.14 19.09 27.70 24.13 19.33 16.88 Black ' ' ' , 8,,0,,76,0,,2,,,,,,,,,,,,,,,,,,,87.545 9. 75.87 80.67 83.12 Age 24 Years or Less 43452 70.94 91.46 59.06 44.44 3.89 4.42 4.99 5.52 25 to 44 Years 447789 92.00 79.41 49.91 35.87 40.09 39.59 43.44 45.88 45to64Years 449373 109.37 82.19 47.46 31.96 40.23 41.12 41.45 41.02 65 Years or More 176460 146.89 75.68 29.52 15.05 15.80 14.87 10.12 7.58 Years of Schooling Less than 1 Year 545291 66.95 92.71 56.72 39.94 48.81 56.28 60.11 62.21 1 to 4 Years 261247 75.55 86.41 49.84 33.84 23.39 25.13 25.30 25.25 4to8Years 177528 138.07 74.63 35.64 21.58 15.89 14.75 12.30 10.94 8to12 Years 110222 246.33 31.25 10.67 5.08 9.87 3.83 2.29 1.60 More than 12 Years 22786 502.07 0.00 0.00 0.00 2.04 0.00 0.00 0.00 Immigration No Immigrant 765731 100.21 02.15 48.75 344.U6 68.55 70.03 72.55 74.50 0 to 5 Years 69951 126.90 74.24 42.35 28.98 6.26 5.78 5.76 5.79 6to9Years 15899 119.87 66.67 22.51 9.91 1.42 1.18 0.70 0.45 More Than 10 Years 218328 120.96 75.97 39.89 24.76 19.54 18.47 16.93 15.44 Other/Not Specified 47165 114.96 86.52 44.42 28.40 4.22 4.54 4.07 3.83 Working Class Inactive 258593 96.50 85.86 45.40 29.97 23.15 24.72 22.82 22.13 Unemployed 20669 21.48 100.00 83.73 71.56 1.85 2.30 3.36 4.22 FormalEmploees 43986 111.38 71.09 33.26 19.15 3.94 3.48 2.84 2.41 Informal Employees 141490 68.70 91.01 58.91 41.32 12.67 14.34 16.20 16.70 Self-Employed 493358 89.37 81.85 48.34 33.36 44.17 44.96 46.36 47.01 Employer 42925 395.86 24.69 11.85 6.44 3.84 1.18 0.99 0.79 Public Servant 81074 177.36 66.01 29.61 18.09 7.26 5.96 4.67 4.19 Unpaid 34979 110.54 78.79 40.71 25.47 3.13 3.07 2.77 2.55 .................I........................................................................................................................................... ...........................................................................................................................1........... ............................ Employment Tenure 0 Years 279262 90.94 86.91 48.23 33.05 25.00 27.02 26.18 26.36 1 Years or More 88499 82.04 82.64 45.68 31.14 7.92 8.14 7.86 7.87 1 to 3 Years 87443 98.21 78.79 40.38 26.27 7.83 7.67 6.86 6.56 3to5Years 78430 119.28 73.65 41.27 26.92 7.02 6.43 6.29 6.03 Morethan5Years 583440 117.83 78.11 46.57 31.91 52.23 50.74 52.81 53.18 ....... -1. .,................................................................. .................... .....................................................I............................................................I............................I.................. .................. ........... ......................... Enterprise Size 1 11657 294.44 36.36 10.76 3.84 1.04 0.47 0.24 0.13 2a5 76311 152.54 75.69 44.77 29.37 6.83 6.43 6.64 6.40 6 a 10 9009 239.34 47.05 27.70 18.00 0.81 0.47 0.49 046 >11 9009 486.00 0.00 0.00 0.00 0.81 0.00 0.00 0.00 Other/Not Specified 1011088 96.67 82.29 47.14 32.20 90.51 92.63 92.63 93.01 Sector of Activity Agriculture 299406 73.53 90.62 59 89 43.20 26.80 ' 30.21 34.85 36.95 Manufacturing 41868 102.55 87.34 61.30 46.88 3.75 4.07 4.99 5.61 Construction 96973 88.27 87.98 44.30 26.73 8.68 9.50 8.35 7.40 Services 332267 138.55 66 35 34.93 2237 29.74 24.54 22.56 21.23 Public Sector 67298 193.81 62.21 23.48 12.75 6.02 4.66 3.07 2.45 Other/Not Specified 279262 90.94 86.91 48.23 33.05 25.00 27.02 26.18 26.36 Source PNAD - IBGE CESEM Statistical Annex.xis CEUP PL - 8/16/00 11:38 AM Table 69. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Rural Indigence Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) Total 2394,'5,3,,9, 47.37'76.51 42.2127.73100.00 100.00100.00100.00 Dependency Ratio 1 133545 128.09 3.33 0.61 0.20 5.58 0.24 0.08 0.04 14 836414 25.70 94.04 62.80 45.54 34.93 42.93 51.97 57.37 Other/NotSpecified 48550 3.59 100.00 94.48 89.37 2.03 2.65 4.54 6.54 .. ........ ................................... ............................... .......................................I..................................... .............................................................................................................. ........................................ Housing Own House already Paid with Own L 1373593 53.54 69.95 37.64 24.24 57.36 52.45 51.15 50.14 Own House already Paid without Ow 417287 39.15 83.29 50.03 34.48 17.43 18.97 20.66 21.67 Rent 9867 48.58 79.52 34.71 16.34 0.41 0.43 0.34 0.24 Ceded 589553 38.68 87.05 47.62 31.43 24.62 28.01 27.77 27.90 Other 1590 99.87 0.00 0.00 0.00 0.07 0.00 0.00 0.00 Not Specified 2649 43.82 100.00 32.65 10.66 0.11 0.14 0.09 0.04 Water Canalized 127002 96.60 43.25 16.28 8.27 5.30 3.00 2.05 1.58 No Canalized 2267537 44.62 78.38 43.67 28.82 94.70 97.00 97.95 98.42 ................... ...................................................... ............. ............................................................463...... .......................85........ .....................3 - ..........20 ,,...... .... 2 ...........I ''........... ''' ..... *.....0 2............0.57...... Sanitation Concrete CesspitZ 46320 85.18 63.39 20.18 8.20 1.93 1.80 0.92 0.57 Rudimental Cesspit 537045 61.45 62.71 32.06 19.64 22.43 18.38 17.03 15.88 Drain 16427 67.81 45.16 17.61 7.65 0.69 0.40 0.29 0.19 Other 2119 33.79 100.00 48.07 23.11 0.09 0.12 0.10 0.07 Not Specified 1792628 42.01 81.25 46.04 30.85 74.86 79.49 81.66 83.28 .........................................................................................................................................................................................,................................................................................................. Eletricity Yes 866355 58.14 65.84 35.32 23.12 36.18 31.13 30.27 30.16 No 1525535 41.26 82.53 46.15 30.38 63.71 68.72 69.64 69.80 .OtherlNotSpecitied 2649 43.82 ~~~~~~~ ~~~~~~~~~~~ ~~~~~100.00 32.65 10.66 0.11 0.14 0.09 0.04 Other/NotSPe,c!f!,ed,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,~~~~~..~K ff ................ , , ,, ........... & .~ .................. 6 6 ................... ,.i ..........4. ............. 2 Garbage Collected Directly 11893 93.17 43.77 24.81 15.48 0.50 0.28 0.29 0.28 Collected Indirectly 3179 48.43 100.00 25.57 6.54 0.13 0.17 0.08 0.03 Burned 797059 4901 76.52 42.60 28.48 33.29 33.29 33.59 34.19 Unused Plot of Land 1532070 45.61 77.22 42.53 27.71 63.98 64.57 64.46 63.94 Other/Not Specified 033 .............64.503386.61.05 31.69 20.48 2.10 1.68 1.58 1.55 Source: PNAD - IBGE OtherlN.otSpeC M cxN0 CESEM Statistical Annex.xls CERUIND -8/16/00 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Rural Indigence Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%/6) (%) (%) (%) (%) (%) Total 2394539 47.37 76.51 42.21 27.73 100.00 100.00 100.00 100.00 ...................... ..................I.................I..................................................................... ........................I...................-1-.............................................................................................................I.............................. Gender Men 2174165 45.58 78.08 43.72 29.00 90.80 92.65 94.04 94.96 Women 220374 65.01 61.09 27.32 15.19 9.20 7.35 5.96 5.04 Race Indigenous 4769 48.49 77.77 27.28 9.57 0.20 0.20 0.13 0.07 White 596319 53.41 73.66 39.07 25.40 24.90 23.97 23.05 22.81 Black 1793451 45.36 77.46 43.30 28.55 74.90 75.82 76.82 77.12 Age 24 Years or Less 93073 42.08 75.63 41.87 28.53 3.89 3.84 3.86 4.00 25 to 44 Years 1062680 35.82 87.66 52.05 35.37 44.38 50.85 54.72 56.61 45 to 64 Years 862525 47.85 77.13 41.10 26.51 36.02 36.31 35.07 34.44 65 Years or More 376261 80.23 43.83 17.07 8.73 15.71 9.00 6.35 4.95 Years of Schooling Less.thana1 Year 1510411 46.22 77.24 42.55 27.76 63.08 63.67 63.59 63.15 1 to 4 Years 643727 43.54 79.51 44.82 29.97 26.88 27.94 28.55 29.05 4to8Years 201079 58.59 67.47 35.40 23.23 8.40 7.41 7.04 7.04 8 to12 Years 37623 82.20 47.88 22.17 13.49 1.57 0.98 0.83 0.76 More than 12 Years 1699 430.13 0.00 0.00 000 0.07 0.00 0.00 0.00 immigrationj No immigrant 1712199 45.76 77.15 42.83 28.22 71.50 72.10 72.55 72.77 Oto5Years 72840 44.85 76.11 40.64 25.52 3.04 3.03 2.93 2.80 6 to 9 Years 56086 40.66 80.90 51.62 36.71 2.34 2.48 2.86 3.10 More Than 10 Years 487706 54.54 74.03 38.37 24.17 20.37 19.71 18.51 17.76 Other/Not Specified 65708 44.63 75.00 48.32 36.10 2.74 2.69 3.14 3.57 ...................................................................... ..................... ................................................................................ .......................................................................... Working Class Inactive 249214 65.94 56.71 25.65 16.06 10.41 7.71 6.32 6.03 Unemployed 7220 21.95 100.00 66.26 49.01 0.30 0.39 0.47 0.53 Formal Emploees 78476 55.88 67.71 28.21 13.61 3.28 2.90 2.19 1.61 Informal Employees 475970 36.49 88.28 47.71 30.18 19.88 22.93 22.46 21.64 Self-Employed 1297061 43.77 79.18 45.69 30.79 54.17 56.05 58.62 60.15 Employer 114461 78.36 51.39 28.64 18.56 4.78 3.21 3.24 3.20 Public Servant 9544 89.73 93.31 27.90 10.01 0.40 0.49 0.26 0.14 Unpaid 162593 52.24 71.06 39.89 27.37 6.79 6.31 6.42 6.70 ~~~~~~~~~~~~~~~~~~~~~....................................................... ,~~ .......... i ............. EmploymentTenure OYears 256434 64.70 57.92 26.80 16.99 10.71 8.11 6.80 6.56 1 Years or More 233199 40.58 83.91 46.33 29.40 9.74 10.68 10.69 10.33 1 to 3 Years 165890 50.30 76.80 41.80 25.70 6.93 6.95 6.86 6.42 3 to 5 Years 102929 56.13 67.87 32.50 17.87 4.30 3.81 3.31 2.77 More than 5 Years 1620187 44.79 78.71 44.79 30.13 67.66 69.61 71.79 73.53 Other/Not Specified 15900 43.01 96.67 35.45 16.59 0.66 0.84 0.56 0.40 ....................................... ..............................................................i 5 -.......................1". --.......................... .................................................................................................................................................... Enterprise Size 1 14306 131.28 0.00 0.00 0.00 0.60 0.00 0.00 0.00 2a5 54504 61.32 75.08 30.43 14.83 2.28 2.23 1.64 1.22 6 a 10 12189 52.98 86.96 22.93 7.52 0.51 0.58 0.28 0.14 Other/Not Specified 2313540 46.50 76.96 42.85 28.31 96.62 . 97.19 98.08 98.65 ........................................................................................................ ............................ .................................................................................................................... ........................ Sector of Activity Agriculture 1781033 43.35 79.91 46.17 31.05 74.38 77.69 81.34 83.30 Manufacturing 172359 41.58 83.09 42.03 25.00 7.20 7.82 7.17 6.49 Construction 72533 58.70 58.04 22.56 10.79 3.03 2.30 1.62 1.18 Services 101473 71.39 65.53 28.01 15.25 4.24 3.63 2.81 2.33 Public Sector 10707 90.45 79.19 24.59 8.90 0.45 0.46 0.26 0.14 Other/Not Specified 256434 64.70 57.92 26.80 16.99 10.71 8.11 6.80 6.56 ............. ............ ......... ................... ... ............................................-................................................................I....................................................I......................................... ........................ Source: PNAD - IBGE CESEM Statistical Annex.xis CERU IND - a116/00 11:38 AM Table 70. - POVERTY PROFILE - 1996 CEARA With Inputed Rent Rural Low Poverty Line Contribution to Total Poverty Average Characteristics of the Sub-Groups Total Per Capita P0 P1 P2 Population P0 P1 P2 Household Population Earnings (%) (%) (%) % % (%) ...................................................................................................................................................................................................47...7..................95 ..........6 -4.........49 8 0 0 1 . 01 0 0 0 . 0 Total 2394539 47.37 95.85 65.84 49.88 100.00 100.00 100.00 100.00 Dependency Ratio i 133545 128.09 68.17 14.66 5.10 5.58 3.97 1.24 0.57 1cd=<1.5 182854 86.54 91.25 40.73 21.64 7.64 7.27 4.72 3.31 1.5 4 836414 25.70 99.49 80.60 67.39 34.93 36.26 42.77 47.20 Other/Not Specified 48550 3,59 100.00 97.28 94.66 2.03 2.12 3.00 3.85 .......... .........." ........................................................................................................6 ................................................................................................................................... .................................................. Housing Own House already Paid with Own L 1373593 53.54 94.01 61.77 45.63 57.36 56.26 53.82 52.48 Own House already Paid without Ow 417287 39.15 97.21 71.23 56.43 17.43 17.67 18.85 19.72 Rent 9867 48.58 94.63 63.32 44.10 0.41 0.41 0.40 0.36 Ceded 589553 38.68 99.17 71.64 55.38 24.62 25.47 26.79 27.34 Other 1590 99.87 100.00 24.33 5.92 0.07 0.07 0.02 0.01 Not Specified 2649 43.82 100.00 66.80 44.62 0.11 0.12 0.11 0.10 ..... ..................................................................... .............................................................................................................................................................. ........... Water Canalized 127002 96.60 79.89 41.53 25.56 5.30 4.42 3.35 2.72 No Canalized 2267537 44.62 96.75 67.20 51.24 94.70 95.58 96.66 97.28 .. ............................................................ ...........................I.....................................................................I................................................................................. Sanitation ConcreteCesspit2 46320 85.18 81.70 45.29 29.24 1.93 1.65 1.33 1.13 Rudimental Cesspit 537045 61.45 92.46 57.65 40.78 22.43 21.63 19.64 18.34 Drain 16427 67.81 100.00 48.62 28.36 0.69 0.72 0.51 0.39 Other 2119 33.79 100.00 74.40 55.35 0.09 0.09 0.10 0.10 Not Specified 1792628 42.01 97.19 68.97 53.33 74.86 75.91 78.42 80.04 Eletricity Yes 866355 58.14 92.71 59.44 43.43 36.18 34.99 32.66 31.50 No 1525535 41.26 97.63 69.47 53.55 63.71 64.89 67.23 68.40 Other/NotSpecified 2649 43.82 100.00 66.80 44.62 0.11 0.12 0.11 0.10 .................................................................... ..ii ii ; .......................................................I............. ......................... -6 ...... i . ................I..................................................................................... Garbage Collected Directly 11893 93.17 94.63 52.71 34.12 0.50 0.49 0.40 0.34 Collected Indirectly 3179 48.43 100.00 63.30 40.07 0.13 0.14 0.13 0.11 Burned 797059 49.01 94.14 65.56 50.11 33.29 32.69 33.15 33.44 Unused Plot of Land 1532070 45.61 96.75 66.43 50.23 63.98 64.58 64.56 64.43 OtherlNot Specified 50338 64.06 95.79 55.56 39.86 2.10 2.10 1.77 1.68 P A D I B G E................................................................................................................................................................................................ ....................................................................................................... Source: PNAD - IBGE CESEM Statistical Annex.xls CERU PL - 8/16100 11:38 AM POVERTY PROFILE - 1996 CEARA With Inputed Rent Rural Low Poverty Line Contribution to Total Poverty Average Head of the Sub-Groups Total Per Capita PO P1 P2 Population PO P1 P2 Household Population Earnings (%) (%) (%) (%) (%) (%) (%) .. ............................................................................................................ ......................................................... ..................... 4. 37958..............1 0. 0 00 0010 .0 Total 2394539 47.37 95.85 65.84 49.88 100.00 100.00 100.00 100.00 Gender Men 2174165 45.58 96.50 67.04 51.19 90.80 91.41 92.45 93.19 Women 220374 65.01 89.42 54.00 36.92 9.20 8.59 7.55 6.81 Race Indigenous 4769 48.49 100.00 63.26 40.80 0.20 0.21 0.19 0.16 White 596319 53.41 93.76 62.74 46.94 24.90 24.36 23.73 23.44 Black 1793451 45.36 96.54 66.87 50.88 74.90 75.43 76.08 76.40 Age 24 Years or Less 93073 42.08 100.00 68.12 50.86 3.89 4.06 4.02 3.96 25 to 44 Years 1062680 35.82 98.30 73.59 58.49 44.38 45.51 49.61 52.04 45 to 64 Years 862525 47.85 95.50 65.74 49.25 36.02 35.89 35.97 35.57 65 Years or More 376261 80.23 88.70 43.57 26.74 15.71 14.54 10.40 8.42 ................................................................................................................................. ......................................................................................I.................................................... Years of Schooling Less than 1Year 1510411 46.22 96.10 66.06 50.10 63.08 63.24 63.30 63.36 i to 4 Years 643727 43.54 97.53 68.40 52.38 26.88 27.35 27.93 28.23 4 to 8 Years 201079 58.59 92.89 60.42 44.26 8.40 8.14 7.71 7.45 8 to12 Years 37623 82.20 77.46 44.67 30.45 1.57 1.27 1.07 0.96 More than 12 Years 1699 430.13 0.00 0.00 0.00 u.07 0.00 0.00 0.00 .. ..... .................I.............. ..............................................................................................................................................,.,.,,............... , Immigration No Immigrant 1712199 45.76 96.44 66.49 50.46 71.50 71.94 72.21 72.34 O to 5 Years 72840 44.85 98.55 66.78 49.37 3.04 3.13 3.09 3.01 6 to 9 Years 56086 40.66 93.39 70.32 56.75 2.34 2.28 2.50 2.66 More Than 10 Years 487706 54.54 93.76 62.78 46.58 20.37 19.92 19.42 19.02 Other/Not Specified 65708 44.63 95.16 66.73 53.92 2.74 2.72 2.78 2.97 .................................................................................................................................................................I............................................................................................................... Working Class Inactive 249214 65.94 95.11 51.88 35.19 10.41 10.33 8.20 7.34 Unemployed 7220 21.95 100.00 83.37 70.74 0.30 0.31 0.38 0.43 Formal Emploees 78476 55.88 95.95 58.41 38.89 3.28 3.28 2.91 2.56 Informal Employees 475970 36.49 99.44 72.45 55.57 19.88 20.62 21.88 22.15 Self-Employed 1297061 43.77 96.15 68.20 52.72 54.17 54.34 56.11 57.26 Employer 114461 78.36 83.33 51.45 36.45 4.78 4.16 3.74 3.49 Public Servant 9544 89.73 93.31 61.06 40.36 0.40 0.39 0.37 0.32 Unp,aid 162593 52.24 92.83 62.22 47.42 6.79 6.58 6.42 6.46 ................................................................................................................................................................................................................................................................................... Employment Tenure 0 Years 256434 64.70 95.25 52.77 36.19 10.71 10.64 8.58 7.77 1 Years or More 233199 40.58 96.59 69.85 53.67 9.74 9.81 10.33 10.48 1 to 3 Years 165890 50.30 94.82 66.05 49.49 6.93 6.85 6.95 6.87 3 to 5 Years 102929 56.13 96.91 59.77 41.78 4.30 4.35 3.90 3.60 More than 5 Years 1620187 44.79 95.84 67.67 52.08 67.66 67.65 69.55 70.65 Other/Not Specified 15900 43.01 100.00 67.41 46.86 0.66 0.69 0.68 0.62 .........................................................................-..... .............................................................................................................................................................................................................. ............................ Enterprise Size 1 14306 131.28 66.66 25.28 9.70 0.60 0.42 0.23 0.12 2 a 5 54504 61.32 91.25 59.26 40.63 2.28 2.17 2.05 1.85 6 a 10 12189 52.98 100.00 59.86 37.17 0.51 0.53 0.46 0.38 Other/Not Specified 2313540 46.50 96.12 68.27 50.41 96.62 96.89 97.26 97.65 ...............................................................................I..................... .......I..... ......:.........................................................................................I.................I............................. ............... Sector of Activity Agriculture 1781033 43.35 96.22 68.66 53.19 74.38 74.66 77.57 79.32 Manufacturing 172359 41.58 98.16 68.72 50.78 7.20 7.37 7.51 7.33 Construction 72533 58.70 96.35 55.91 35.52 3.03 3.04 2.57 2.16 Services 101473 71.39 86.94 52.34 36.46 4.24 3.84 3.37 3.10 Public Sector 10707 90.45 94.03 57.35 36.55 0.45 0.44 0.39 0.33 Other/Not Specified 256434 64.70 95.25 52.77 36.19 10.71 10.64 8.58 7.77 ..................................... ................. I........... ........ ... ............ ............................................................................................................................................................... Source: PNAD - IBGE CESEM Statistical Annex.xis CERU PL - 8116100 11:38 AM Education Table 71. - Illiteracy Rate (%/q) and Schools Enrolment (1,000) 1985-1994 Ceara Nordeste Brazil 1985 1990 1985 1994 1985 1994 Illiteracy rate 7 to 14 years old 54.44 36.51 53 35.69 28.24 17.33 15 years old and above 40.39 31.5 39.66 30.49 20.69 15.58 School Enrolment (1,000) Prn-Escola 123 593 862 2591 2493 5687 1° Grau 814 1360 7439 9539 24769 31102 2° Grau 78 144 695 1019 3016 4510 College 41 37 226 264 1368 1661 Enrolmente / Prof. Ratio Pre-Escola 22.67 19.76 25.15 20.27 23.23 20.71 1° Grau 20.48 25.75 25.58 26.27 23.8 23.29 2° Grau 15.37 17.7 15.14 15.66 14.63 15.26 College 14.04 10.88 10.81 10.21 12.05 10.66 Source: IBGE - Anuirio Estatistico do Brasil, 1988,1995, PNAD - 1995, SUDENE - DPO-IPLIEst. Table 72. - Ceara - Evasion and Failure rates (°/) - 1996/97 1996 1997 Fundamental School Evasion rate (%) 10.4 8.9 State network 12.7 11.8 Municipalities network Failure rate (%) State network 13 11.9 Municipalities network 14.9 14.3 Secondary School Evasion rate (%) State network 21.4 20.8 Municipalities network 20.7 20.5 Failure rate (%) State network 8.8 8.4 Municipalities network 11 8.8 Source: Mensagem a Assembl6ia Legislativa - 1998 Table 73. - Share of Public and Private Servic es on Total Education Services (,lo) 1985 1990 1995 Public Private Public Private Public Private Northeast 84.56 15.44 82.65 17.35 75.88 24.12 Maranhao 83.68 '6.32 88.81 11.19 84.29 15.71 Piaui 92.90 7.10 94.51 5.49 76.39 2:3.61 Ceara 83.98 16.02 81.74 18.26 73.69 26.31 R. G. do Norte 86.74 13.26 90.41 9.59 80.60 19.40 Paraiba 90.17 9.83 87.16 12.84 83.41 16.59 Pernambuco 76.24 23.76 73.58 26.42 68.64 31.36 Alagoas 90.00 10.00 84.52 15.48 76.66 23.34 Sergipe 91.72 8.28 86.99 13.01 71.43 28.57 Bahia 82.54 17.46 76.11 23.89 72.99 27 -01 Source: Banco do Nordeste Health and Sanitation Table 74. - Ceara - Basic Sanitation 1990 1995 User % User Population Population % Piped water 2,597,798 39.84 2,971,475 44.13 Esgoto 39,254 6.2 55,196 7.8 Coleta de Lixo (1) Coletado 50,496 36.28 53,538 35.8 Outros 88,679 63.72 96,025 64.2 Source: Iplance, Anuario Estatistico do Ceara, 1993 e 1995196, FIBGE-PNAD, 1990 e 1995 (1) By permanent private home Table 75. - Share of permanent private homes with water facilities as % of total 1980 1991 % Increase Maranhao 17.87 35.25 97.26 Piaui 26.71 48.96 83.30 Ceara 17.65 42.69 141.87 R. G. do Norte 37.85 62.73 65.73 Paraiba 36.27 58.57 61.48 Pernambuco 41.90 65.72 56.85 Alagoas 33.25 52.55 58.05 Sergipe 42.31 65.57 54.98 Bahia 34.68 52.22 50.58 Northeast 31.59 52.74 66.95 Brazil 54.91 70.71 28.77 Source: IBGE - Censos Demograficos, 1980, 1991; SUDENElDPO/IPUContas Regionais Table 76. - Brazil, Southeast, Norteast by State - Life expectation at Birth (years) 1950-96 1950 1960 1970 1980 1991 1996 Brazil 45.9 52.4 52.7 60.1 66.3 72.4 Southeast 48.8 57.0 56.9 63.6 68.8 76.3 Northeast 38.7 43.5 44.4 51.6 59.1 64.2 Maranhao 44.5 48.7 49.1 55.4 62.7 68.1 Piaui 45.5 47.8 49.4 57.9 65.1 70.7 Ceara 40.9 38.9 43.1 47.0 56.8 61.7 R.G. do Norte 33.9 34.1 38.6 45.4 54.6 59.3 Parafba 34.8 35.2 38.9 44.3 53.7 58.3 Pernambuco 35.0 36.8 41.1 47.8 56.6 61.4 Alagoas 36.8 37.4 40.5 46.9 55.7 60.5 Sergipe 37.3 41.2 45.1 55.3 63.0 68.4 Bahia 40.7 44.7 48.8 58.0 64.8 70.3 Source: IBGE(1950-80), PNUD-IPEA (1991-6) Table 77. - Share of Public and Private Services on Total Heath Services (%/6) 1985 1990 1995 Public Private Public Private Public Private Northeast 57.44 42.56 58.33 41.67 62.32 37.68 Maranhao 65.85 34.15 58.07 41.93 74.99 25.01 Piaui 89.56 10.44 7354.00 26.46 75.61 24.39 Ceara 62.79 37.21 64.66 35.34 67.00 33.00 R. G. do Norte 73.66 26.34 73.91 26.09 71.67 28.33 Paraiba 58.39 41.61 55.77 44.23 52.95 47.05 Pernambuco 53.85 46.15 48.61 51.39 59.38 40.62 Alagoas 34.86 65.14 61.90 38.10 67.44 32.56 Sergipe 81.81 '18.19 72.00 28.00 55.56 44.44 Bahia 46.96 53.04 52.12 47.88 54.70 45.30 Source: Banco do Nordesie Table 78. - Northeast, Distrito Federal and Brazil - Human Development Index IDH IDH Education IDH Income 1970 1980 1991 1970 1980 1991 1970 1980 1991 Maranhao 0.289 0.404 0.471 0.286 0.364 0.457 0.180 0.340 0.327 Piaui 0.273 0.412 0.494 0.286 0.373 0.458 0.125 0.315 0.355 Ceara 0.266 0.418 0.495 0.321 0.417 0.492 0.176 0.471 0.464 Parafba 0.237 0.365 0.457 0.329 0.380 0.468 0.150 0.393 0.426 Pernambuco 0.302 0.491 0.547 0.372 0,450 0.528 0.266 0.643 0.586 Alagoas 0.248 0.382 0.467 0.288 0.349 0.444 0.197 0.431 0.446 Sergipe 0.296 0.490 0.559 0.338 0.401 0.515 0.215 0.564 0.530 Bahia 0.330 0.522 0.551 0.351 0.426 0.504 0.244 0.589 0.498 Distrito Federal 0.652 0.790 0.825 0.650 0.724 0.754 0.819 0.965 0.970 Brazil 0.475 0.704 0.757 0.500 0.577 0.641 0.463 0.949 0.943 Source: SUDENEIDPO/Contas Regionais Fiscal Indicators Table 79. - Ceard - Budget Revenue Compositon (lo) 1991 1992 1993 1994 1995 1996 1997 Current Revenue 94.3 94.7 87.5 92.4 91.7 94.3 Tax Revenue 45.8 46.2 36.9 50.0 51.0 52.6 Current Transfers 32.7 33.4 30.9 30.2 34.6 34.3 Others 15.8 15.1 19.7 12.2 6.1 7.4 Capital Revenue 5.7 5.3 12.5 7.6 8.3 5.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 Source: SEFAZ - CE, Balan;o Geral do Estado Table 80. - Ceara - Expenditure Composition (%o) 1991 1992 1993 1994 1995 1996 A. Current Expenditure 70.6 70.9 70.4 74.2 79.1 83.3 Wages 25.1 25.7 24.2 27.0 31.2 29.6 B. Capital Expenditure 29.4 29.1 29.6 25.8 20.9 16.7 Investment 14.8 11.4 14.7 9.5 9.3 5.0 Internal Debt Amort. 1.3 2.1 1.5 4.2 2.2 4.2 External Debt Amort. 2.7 0.2 Total (A+B) 100.0 100.0 100.0 100.0 100.0 100.0 Source: SEFAZ-CE, Balanro Geral do Estado Table 81. - CearA - Budget performance R$ (000) 1995 1991 1992 1993 1994 1995 1996 1997 1. Current Revenue less: Current Expenses 518,412.87 388,997.49 361,112.49 330,635.57 205,579.73 193,560.67 195,480.00 2. Capital Revenue less: Credit Operations 2,518.98 13,999.66 161,809.36 34,598.86 50,780.75 20,737.76 2,310.00 3. Self-financing Margin (1+2) 520,931.85 402,997.19 552,921.87 365,234.42 256,361.52 214,298.42 197,790.00 4. Total Investments 471,862.84 428,924.58 541,534.58 354,067.29 324,848.53 273,143.40 204280.00 5. Amortization 21,442.55 33,824.10 28,429.98 68,427.23 99,908.77 96,338.36 9000 6. Third parties resources (27,626.45) 59,769.48 47,042.70 57,260.09 168,394.73 155,183.34 7. Financing Requirement (49,069.00) 25,945.39 18,612.70 (11,167.13) 68,485.96 58,844.98 3474800 8. Credit Operations 99,685.90 70,420.06 82,590.05 92,219.91 113,453.50 103,714.14 20,13.0 9. Budget Deficit/ Surplus 127,292.35 10,650.57 35,547.35 34,959.82 (54,941.23) (51,469.20) (1) Source: SEFAZ-CE, Balango Geral do Estado Table 82. - Ceara - Federal Taxes Collection, 1991-1997 R$ (000) 1996 (Jan- 1997 (Jan- 1991 1992 1993 1994 1995 1996 Aug) Aug) Import Tax- II 9,369 19,325 22,258 41,614 56,677 60,993 40,157 32,381 Income Tax - IR 292,614 291,956 367,668 336,822 357,439 386,898 282,900 285,256 Industrial Production Tax - IPI 124,315 122,898 111,470 105,577 149,123 151,476 106,774 95,573 IPI - Tobacco 66,071 66,748 57,548 57,120 73,727 78,538 55,487 50,028 IPI - other than tobacco 58,244 56,150 53,921 48,457 75,395 72,938 51,288 45,545 Financial Transactions Tax - IOF 49,303 54,693 73,622 63,972 27,224 16,984 13,195 1,013 Other Taxes 2,949 48 9,175 101,528 2,907 2,189 1,502 1,714 Total 478,550 488,920 584,193 649,513 593,370 618,540 444,528 415,937 Source: SEFAZ-CE Table 83. - Cear*: Effective ICMS Tax Rates, Effective ICMS Tax rate ICMS Revenue VA in Current Prices (%) Sector 1996 1997 1996 1997 1996 1997 Agriculture 2,153 2,021 1,211,709 1,080,986 0.18 0.19 Crops 865 842 660,853 0.13 Animal Production 1,288 1,180 550,856 0.23 Industry 471,483 487,391 4,438,336 5,175,799 10.62 9.42 Mining 2,070 951 104,993 115,654 1.97 0.82 Public Utilities (Water & Elect) 91 99,944 349,370 395,260 26.15 25.29 Construction 4,840 7,002 750,900 974,172 0.64 0.72 Manufacturing Industry 373,228 379,493 3,233,074 3,687,932 11.54 10.29 Non-Metalic Minerals 14,127 16,176 264,722 316,164 5.34 5.12 Metallurgy 11,615 13,457 100,791 104,116 11.52 12.92 Machinery 3,519 1,631 46,029 34,462 7.65 4.73 Elect. Machinery & Equipment 5,880 8,209 22,945 25,972 25.63 31.61 Transportation Equipment 1,192 1,278 186,919 223,593 0.64 0.57 Wood Products 1,190 1,250 43,863 49,625 2.71 2.52 Furniture 3,836 3,947 41,474 47,864 9.25 8.25 Paper Products 2,162 3,332 9,578 10,828 22.58 30.77 Rubber Products 3,943 3,694 19,930 22,434 19.79 16.47 Leather 834 762 304,096 460,682 0.27 0.17 Chemicals 66,415 57,688 63,705 54,282 104.25 106.27 Pharmaceutical Products 5,963 7,163 33,657 43,911 17.72 16.31 Perfumery, Soaps, etc. 563 540 27,150 35,422 2.07 1.52 Plastic Products 9,781 9,261 65,549 70,473 14.92 13.14 Textiles 66,314 31,653 672,085 727,522 9.87 8.47 Apparel & Footwear 52,734 61,095 344,528 404,482 15.31 15.10 Food Products 54,766 60,525 802,594 867,950 6.82 6.97 Beverages 65,472 65,021 102,993 101,185 63.57 64.26 Tobacco 111 104 2,231 2,916 4.97 3.56 Editorial, Graphics & Printing 1,099 1,076 69,759 74,778 1.58 1.44 Miscellaneous Manufactures 1,711 1,630 8,425 9,272 20.30 17.59 Services 1,033,903 635,821 11,571,509 12,639,634 8.93 5.03 Commerce 426,715 408,763 3,755,544 4,093,394 11.36 9.99 Transportation 23,261 23,625 294,783 324,995 7.89 7.27 Communication 95,381 106,303 245,148 281,373 38.91 37.78 Hotel & Food Services 6,557 6,219 303,318 399,689 2.16 1.56 Public Administration 55,270 89,923 1,892,843 2,077,674 2.92 4.33 Banks and Financial Institutions 4 4 864,488 Total 1,507,539 1,125,233 17,221,554 18,896,419 8.75 5.95 Note: * Chemicals includes petroleum products on the revenue side but no on the output side (where they are included under Mining) Source: author's calculations from SEFAZ and IPLANCE information