33664 AFRICA PRIVATE SECTOR GROUP INVESTMENT CLIMATE ASSESSMENT ENHANCING THE COMPETITIVENESS OF KENYA'S MANUFACTURING SECTOR: THE ROLE OF THE INVESTMENT CLIMATE KENYA NOVEMBER 2004 WORLD BANK KIPPRA CSAE, OXFORD Christopher Blattman Peter Kimuyu Arne Bigsten Linda Cotton Rose Ngugi Måns Söderbom Vyjayanti Desai Ibrahim Elbadawi James Habyarimana Jean Michel Marchat Vijaya Ramachandran Manju Kedia Shah Kehnide Ajayi Acknowledgements This Investment Climate Assessment (ICA) is based on an analysis of investment climate survey data conducted by the Kenya Institute for Public Policy Research and Analysis (KIPPRA) in Nairobi, Kenya and the Regional Program on Enterprise Development in the Africa Private Sector Group at the World Bank. For helpful insights and analysis, we would also like to thank Vanessa Dick (EU), Ibrahima Diong (PPIAF), David Ferrand (DFID), Isaac Kamande (Kenya Ministry of Trade and Industry), Daniel Kanyi (APDF), Moses Kibirige (APDF), Julius Kipng'etich (Kenya IPC), Dorothy McCormick (University of Nairobi Institute for Development Studies), Catherine Masinde (DFID), David Mwangangi (KPSA), Ndiritu Muriithi (APDF), Kevin Njiraini (IFC), Fortunatus Okwiri (UNDP), Ocjeng Oloo (Market Intelli- gence), Gladwell Otieno (TI Kenya), and Terry Ryan (ACEG). Michael Fuchs, and Andrew Stone served as peer reviewers for this work, and provided a number of sug- gestions and comments. Helpful comments were also received from Praveen Kumar, Makhtar Diop, Christiane Kraus, Manuel de la Rocha, Geoffrey Bergen, Axel Peuker, participants at the review meeting, and several members of the Kenya country team. i List of Acronyms AGOA Africa Growth and Opportunity Act KIPPRA Kenyan Policy Research Institute AIDS Acquired Immunity Deficiency Syndrome KMES Kenyan Manufacturing Enterprise Survey BDS Business Development Services KPA Kenya Port Authority CBK Central Bank of Kenya KPF Kenya Police Force CBS Central Bureau of Statistics KPLC Kenya Power and Lighting Company CCK Communications Commission of Kenya KR Kenya Railways CEM Country Economic Memorandum KRA Kenya Revenue Authority CFR Country Framework Report Ksh Kenyan Shillings COMESA Common Market for East and Southern Africa LDP Liberal Democratic Party CWA Collective Wage Agreement MoF Ministry of Finance DFI Development Finance Institution MoL Ministry of Labor DFID UK Department for International Development MoTI Ministry of Trade and Industry EIU Economist Intelligence Unit MSME Micro, Small and Medium Enterprises EPC Export Promotion Council MUB Manufacturing Under Bond EPZ Export Processing Zone MVA Manufacturing Value Added EU European Union NAK National Alliance (Party) of Kenya FDI Foreign Direct Investment NARC National Alliance Rainbow Coalition FIAS Foreign Investment Advisory Services NSE Nairobi Stock Exchange FLSTAC Financial and Legal Sector Technical OECD Organization for Economic Cooperation and Assistance Credit Development FSAP Financial Sector Assessment Program OLS Ordinary Least Squares (regression) GDP Gross Domestic Product PRGF Poverty Reduction and Growth Facility GJLOS Governance, Justice, Law and Order Sector PPIAF Public Private Infrastructure Advisory Facility GNI Gross National Income PSD Private Sector Development GoK Government of Kenya PSP Private Sector Participation HIV Human Immuno-Deficiency Syndrome RPED Regional Program on Enterprise Development ICA Investment Climate Assessment SBP Single Business Permit ICT Information and Communication Technology SME Small and Medium Enterprises IMF International Monetary Fund SSA Sub-Saharan Africa ILS Integrated Labor Survey TFP Total Factor Productivity IPC Investment Promotion Centre TI Transparency International IP-ERS Investment Programme for the Economic TVET Technical and Vocational Education and Recovery Strategy Training ITL Industrial Training Levy ULC Unit Cost of Labor KA Kenya Airways UNAIDS Joint United Nations Programme on HIV/AIDS KACC Kenya Anti-Corruption Commission UNCTAD United Nations Conference on Trade and KANU Kenya African National Union Development KCB Kenya Commercial Bank US United States (of America) KenGen Kenya Electricity Generating Company ii Executive Summary 1. The objectives of the ICA are to assess the current performance of formal manufacturing firms, to identify the key constraints on their growth and competitiveness, and to prioritize and assess policy priorities to promote private sector development. 2. While attention is often drawn to the large and growing informal sector, the formal manu- facturing sector remains of crucial interest because it is one of the largest and most produc- tive sectors in the economy. The formal manufacturing sector represents roughly 13 per cent of GDP in spite of employing less than 1.5 per cent of the workforce. Policies that promote im- provement and expansion of the formal sector can therefore have a disproportionately large im- pact on national wealth. By size and rate of growth the informal manufacturing sector is larger-- as a whole it employs roughly 40 per cent of the workforce, and more than three quarters of all manufacturing workers are employed there. These firms tend to be very small and unproductive, however, which is why the formal sector accounts for such a large share of GDP. 3. The analysis of the formal manufacturing sector focuses on the analysis of data collected in a 2002/03 survey of 282 formal manufacturing firms and workers. The survey covered seven sub-sectors in five urban areas: Nairobi, Mombasa, Eldoret, Kisumu and Nakuru. Up to ten em- ployees from each firm were also surveyed. Roughly half of the firms have less than 100 employ- ees, two-thirds are located in Nairobi, a fifth have a more than 10 per cent foreign ownership, half export more than 5 per cent of sales, and three-quarters are owned by ethnic Asians. Assessing the competitiveness of Kenyan firms 4. In general, Kenyan firms have a weak competitive edge over Uganda and Tanzania, but ap- pear to be at a significant competitive disadvantage to strategic competitors like China and India. Kenyan firms also pay more in bribes, provide more of their own infrastructure, and suffer under more regulation than Asian ones. Kenyan firms have only a slight productivity advantage, if any, over Tanzanian and Ugandan ones, and are at an increasingly severe disadvantage to Chi- nese and Indian firms. Labor is more productive than capital, and indeed appears better in Kenya than in the rest of East Africa. Yet in terms of overall firm productivity, Kenyan firms have little if any advantage over Tanzanian and Ugandan ones, largely because of its relative capital inten- sity. With little productivity advantage, Kenya's large trade surplus with East Africa is likely driven by size and perhaps historical and geographical advantages. Meanwhile, Chinese and In- dian firms achieve similar or better labor productivity to Kenyan firms, but do so with much lower levels of capital. Kenyan productivity has been stagnating, moreover, while firms in India and China advance. 5. Kenyan plants and equipment are outdated, overvalued and inefficiently used. Investment levels are low and declining. Kenyan investment levels are very low after decades of decline. Most firms are investing nothing, and few firms that do invest spend enough to even replace worn-out equipment. Surprisingly, given their low rates of investment, firms' use of capital is relatively high and capital productivity low. Kenya's capital stock is unusually old, capacity utili- zation is poor. 6. Productivity growth in Kenya has been zero or negative over the last twelve years. Productiv- ity declined by 0.5 per cent per year between 1991and 1998. Regression analysis of recent firm data suggests that, between 1999/2000 and 2002/03, almost no productivity improvement is visi- ble in the average firm. There has been virtually no change in labor productivity. Capital seems iii moderately more productive, but the increase is not statistically distinguishable from zero. Total factor productivity appears to have increased by 7% between 1999 and 2002, but again this esti- mate is not statistically different from zero. 7. Increased trade openness has facilitated the rapid growth of a few internationally competi- tive firms and a rise in total exports. The average firm, however, is less internationally com- petitive and is now less likely to export. With economic recovery and access to new markets through AGOA, COMESA and EAC, total exports have grown in the last few years. Firm data show, however, that since 1999 the average firm has become less likely to export. This suggests that the average firm is unable to compete internationally, and that the rise in exports is being driven by a few firms. Only firms in the textile sector have on average shown export growth, probably because of AGOA. 8. Firms demonstrate an alarming indifference to and ignorance of the HIV/AIDS problem. While the infection rate in the workforce is estimated at 15% nationally, more than half of all firm managers in the sample believed that none of their workforce was at risk. The other half, how- ever, had programs to inform about or address the problem--a better performance than in Tanza- nia or Uganda. Most workers expressed a willingness to be tested, and even pay for that test. Assessing the competitiveness of the Kenyan workforce 9. Worker-level data suggests that the Kenyan workforce is relatively well-educated, with high returns to education. The workforce in the sampled formal manufacturing firms is experienced, middle-aged and possesses a high level of education. Almost all workers have some schooling. There is a wide dispersion in earnings, driven largely by differences in education, experience, and industry. The average wage in the sample is equivalent to $261 per month, with unskilled produc- tion earning about $99 dollars per month. 10. The level and quality of production and technical training in Kenya is low. This may be in part because the current training incentive system does not encourage firms to invest in en- hancing production skills. Firms appear to invest more heavily in managerial and professional training than in developing production skills. Training deficiencies can be traced, at least in part, to structural problems in the technical and vocational training system. The current training levy system is financially troubled and appears to be inadequate to firms' needs, as it does not support in-house training in production skills. There is sufficient international evidence to indicate that incentives to firms to increase in-house training are vastly superior to public provision of training. 11. The cost of labor in Kenya is comparable to that in other East African countries, but ap- pears strikingly uncompetitive with that in Asia. Wages of unskilled production workers, at spot exchange rates, are higher in Kenya than all neighbours and strategic competitors. For in- stance, unskilled production wages in US dollars are twice that in India. Higher Kenyan wages are justified if labor and firms are highly productive. As seen above, however, capital productiv- ity is lower than that seen in strategic competitors. Looking at estimates of the unit cost of labor (which accounts for wage premiums due to productivity) higher Kenyan wages appear justified when compared to the less labor-productive Tanzania or Uganda. Compared to Asia, however, the cost of labor still appears high. 12. Real wages have doubled or tripled since 1994 while firm productivity has remained stag- nant. There is clearly a disconnect between productivity and wages that cannot be explained by the education or experience of the workforce. Minimum wages have been rising rapidly as well, but more slowly than the private sector average. Several possible reasons are suggested for this wage-productivity disconnect, including the possibility that regulation is driving low-wage jobs iv into the informal sector, or non-market driven increases in public sector wages. Conclusive evi- dence on the matter will have to await the release of several ongoing labor market studies. Assessing the competitiveness of the Kenyan financial sector 13. Relative to other poor countries, Kenya has a well-developed financial sector and a falling cost of capital. A high level of credit channelled to the Kenyan private sector relative to other low-income countries. Moreover, in the last two years, stability has return to the macroeconomy, lending rates have dropped, and banks have returned to profitability. 14. While on the surface firms appear to be dissatisfied with the cost and availability of finance, finance does not currently appear to be a general and severe constraint to business. While high interest rate spreads were undoubtedly a barrier before 2002, rates have fallen dramatically in the past eighteen months, lowering the cost of capital for most firms. Moreover, looking more closely at the data, one can see that access to finance is only an acute problem for a subset of firms, usually smaller domestic ones. Most firms do not feel credit constrained, and report that the reason they have not sought a loan is that they do not need one. 15. While finance may not be a severe constraint, investment capital still may not be sufficiently cheap and available to enable the private sector to meet the government's ambitious in- vestment target. Interest spreads are still high relative to rich countries and emerging economies, and bank productivity is extremely low. Realistically, for the Government to reach their target in- vestment rate of 23 per cent of GDP, interest rate spreads will have to decrease further, and capi- tal will have to be made more available to small firms. 16. Throughout the world, access to credit by smaller firms is limited by high transactions costs. In Kenya, low productivity banks find it costly to evaluate and monitor small-value loans. The lack of public credit institutions (such as a rating agency) makes the evaluation of firm credibility very costly for banks, and dissuades them from lending to small enterprises. Moreover, deficien- cies in the legal system hinder the enforcement of contracts, especially debt, and result in rela- tively high collateral requirements that small firms find slightly more difficult to meet. As a re- sult, small firms (who are less likely to possess high-value collateral) face dramatically higher costs of lending than larger ones. Smaller firms generally report lower use of credit instruments, are less likely to apply for a loan because of cost and rejection fear, and are more likely to feel credit constrained. 17. Transactions costs appear to be high, and the supply of credit appears to be limited, by the legal and institutional structure of the financial sector. High interest rate spreads are drive by low bank productivity, the presence of many small banks, the difficulty of collecting debt con- tracts, and the high level of non-performing loans. These problems in turn have been traced largely to an inadequate legal and institutional structure, barriers to sector consolidation, and po- litically-motivated interventions. Chief barriers to firm competitiveness: Corruption, crime and infrastructure 18. Corruption is one of most significant barriers facing firms, especially foreign firms. More than half reported regularly having to make unofficial payments worth more than 6 per cent of revenues. Two thirds felt they were expected to pay bribes for government contracts. Corruption was rated as a severe or major obstacle by three quarters of the sample firms, and re- spondents reported that "unofficial payments" to "get things done" are required 57 per cent of the time. Some of the worst offenders included the taxation authority, the health inspectorate, mu- nicipal authorities and utility companies. These payments were typically very costly. When firms reported a figure, bribe amounts averaged 6.1 per cent of annual sales revenue (two to three times v the level in Uganda or China). Of the firms that felt it was necessary to pay a bribe to secure a government contract, the value was typically 10% of the value of the service. 1.1.1 Crime was the third most common complaint among firms, and a third of firms experienced a crime in 2002. The direct loss to crime is large (4 per cent of annual sales revenue) but the indirect cost of security (i.e. security measures) is also burdensome (2.7 per cent of sales). A third reported an act of theft or arson in the previous year, with an average of 5 incidents per firm. Most firms also spent money on private security. Less than a fifth of the crimes were solved, and more than half of firms judged police services to be poor or very poor. Crime and insecurity also negatively affect the image of Kenya in the international investment community. 19. Deteriorating transport infrastructure, especially in roads, rail and ports, cause firms to in- cur significant costs in trucking, vehicle repair, product delays and returns, and bribery. Firms report high levels of dissatisfaction with transport infrastructure, especially roads and rail. These problems are perceived to be much more acute in Kenya than elsewhere in East Africa. A quarter of firms pay to build or repair local roads. Delays in delivery result in product refusals and returns of 2.5 per cent of sales. Port productivity is reckoned to be a third or half of the interna- tional norm, and perhaps six times as costly. 20. Domestic and international investment is hindered by power difficulties. Firms lost nearly 10 per cent of sales to power outages, and two-thirds lost capital equipment to surges. Firms experienced an average of 33 outages in a year, and most firms own their own generators to cope with power losses. Yet generators did not prevent damage to capital equipment and lost produc- tion time, equivalent to almost 10 per cent of sales. Electricity hook-ups and usage are also very costly relative to East Africa. 21. Kenya's fixed-line telephone and Internet services are relatively costly and of poor quality due to the weak performance of Telkom Kenya. Mobile communications have dramatically improved access, but remain expensive. Per minute charges are typically two to ten times that faced by rich nations. Quality is poor, and access is limited by long waiting times for connections. Mobile phone service is more widely and cheaply available, and mobile subscribers dwarf the number of fixed line subscribers. Yet mobile tariffs are still high. Policy Implications 22. Kenya has several policy reforms underway. The policy discussion arising from this analysis is intended to preserve the momentum of ongoing reforms, while also making additional sugges- tions to raise productivity. Five major areas are addressed--quality of labor, access to finance, improvements in infrastructure, solutions to corruption and crime and improvements in the pub- lic-private dialogue. Specific recommendations include the following: Labor Review the performance of public sector training institutions with the objective of restructuring training systems as needed, and performing a Skills Needs Inventory as part of the restructuring of curricula and training capacities. Restructure or replace the National Industrial Training Council to make it more autonomous and accountable to the private sector, and to upgrade the skills and qualifications of Council staff. Broaden the scope of the ITL scheme, allowing specialized production skills training to qualify, especially in the high growth sectors (such as garments). Expand the range of skills and training institutions allowed to qualify. Enable firms and the Council to use international trainers until the shortage of qualified Kenyan trainers can be overcome. Encourage enterprises to offer training vi to employees through additional incentive mechanisms, such as cost-sharing programs or tax breaks. Investigate a public-private partnership model for delivery of training, The 2004 Growth and Competitiveness Report suggests that Athi River Vocational Training Centre (AVRTC), which is currently functioning at a very low level of capacity utilization, be converted, on a pilot basis, into a dedicated training facility for the garments industry, with the Government providing insti- tutional and financial support, and the private sector providing training content, knowledge and direction. Expand the scope of and funding for the ILS. Focus ILS or WB study on question of wage growth, or commission a specific study. Have the CBS conduct an annual survey of workers and wage. Postpone further broad-based public sector wage increases (beyond that of the inflation level). Finance Evaluate alternatives for building capacity in commercial banks to serve smaller enterprises. Modernize key commercial registries to provide access to current, accurate, and reliable infor- mation. Establish the legal basis for credit information-sharing among all financial service providers. Remove barriers to creation, registration, and enforcement of security, and integrate the land registry systems, including the removal of hidden liens and excessive registration costs. Reform and modernize insolvency procedures contained in the Companies and Bankruptcy Acts. Strengthen capacity in the Commercial Court to achieve efficient case administration, and pro- mote training among judges. Expand the specialized Commercial Court to other regions, includ- ing Mombasa. Corruption and Crime Increase the staff and financial resources of the Kenya Anti-Corruption Commission. Develop and reinforce institutions to increase scrutiny of firm inspectors and regulators. Focus on agencies such as the taxation authority, municipal authorities, and utilities. Enforce public officer codes of conduct more strictly and publicly, and with officials at the firm- level. Establish an anti-corruption authority or ombudsperson for the reporting and investigation of petty (firm transaction-level) corruption. Establish systems for monitoring the impact of corruption reforms. Options include surveys of en- terprises, households and other users of public services. As discussed below and in the FIAS study, streamlining business regulation and procedures, by increasing the clarity, consistency and ease of regulation, will reduce opportunities for corrup- tion in inspections and regulatory compliance. Simplify and streamline the court procedures for commercial cases. Improve court recording and records management. Increase the resources and appointing more Judges and Magistrates specialized in commercial disputes settlement. vii Recruit new staff and upgrade the skills of existing staff. Facilitate the registration of property liens and improve access to credit information to enhance debt recovery. Introduce a small claims procedure to ease the pressure on court. Strengthen alternative mechanisms of dispute resolution to ease the pressure on courts. Target particularly problematic agencies and organizations (such as the taxation authority, mu- nicipal authorities, and utilities) for reorganization and increased scrutiny. In order to reduce regulatory corruption, several general principles can be followed, including: (i) minimize direct contact between public officials and firms by streamlining of regulations, the elimination or merging of inspections, automating and computerizing procedures, and increasing the use of third-party data and services; (ii) rotate regulatory responsibilities, so that the same inspector or auditor is not perma- nently assigned to a firm; and (iii) spread the regulatory process across more than one individual, department, or organiza- tion (such as a reorganization of a regulatory agency along functional lines) so that au- diting, payments, customer service, and so forth are performed by more than one individ- ual. Implement broader strategies for addressing corruption in civil service organizations can also help, such as allowing independent internal and external audits, protecting whistleblowers, and giving firms a mechanism for complaining about harassment. Keep up the momentum on current reforms of the Kenya Police Force. Examine viable alterna- tives for a transparent and meritocratic system for promotions and raises. Infrastructure Pass the privatization bill. Fully implement the $225 million, donor-financed power sector project, including the develop- ment of an adequate policy, institutional and regulatory environment; expansion of power gen- eration capacity; and better access to reliable electricity, as described above. Accelerate preparations for the concessioning of major roads. Increase the pace of road construction and repair, which has been criticized as slow. Charges for heavy vehicles could possibly be increased and vehicle license collections improved. Increase funding for maintenance of urban roads, especially in industrial parks and key urban access routes. Complete the privatization of the Kenya Railways by means of a long-term concession. Convert the Kenya Ports Authority into a landlord port authority. Private provision and competi- tion should be introduced into all services. Clearance processes and customs procedures should be radically simplified to reduce the scope for discretion and rent seeking and to reduce costs to port users. Public-Private Dialogue viii Use existing fora for a public-private dialogue, while allowing KEPSA time to establish its use- fulness to its member organizations. The National Investment Council can also serve as a key player in the dialogue on investment. Develop objective measures of private sector performance and collect annual data on progress towards their improvement. Create an independent "steering committee" for PSD policy made up of public and private actors to (1) make recommendations on the assignment of specific ministerial roles and responsibilities, (2) advise on PSD objectives and priorities, (3) make recommendations on PSD policy, and (4) publicly monitor and evaluate progress towards goals and create a donor-GoK-private sector coordination group to advise the steering committee. ix Table of Contents Acknowledgements.........................................................................................................................................i List of Acronyms ...........................................................................................................................................ii Executive Summary......................................................................................................................................iii Table of Contents.......................................................................................................................................... x List of Tables and Figures ..........................................................................................................................xii 1 Introduction and Motivation........................................................................................................1 1.1 The impetus for change: Kenya's struggling formal sector.........................................................1 1.2 Description of the 2004 ICA .......................................................................................................4 1.3 General economic overview........................................................................................................6 1.4 A short history of Kenyan industry ...........................................................................................14 2 The Competitiveness of Kenyan Firms in National and International Perspective ..................16 2.1 Overview ...................................................................................................................................16 2.2 The quality, use, and accumulation of capital in Kenya............................................................17 2.3 Firm productivity in international perspective ..........................................................................20 2.4 Kenyan manufacturing exports..................................................................................................24 2.5 Appendix: Estimating overall firm productivity........................................................................26 3 Kenyan Competitiveness in the Factors of Production: Labor and Financial Capital.............31 3.1 Overview ...................................................................................................................................31 3.2 Education and wellbeing of the manufacturing workforce........................................................32 3.3 Wages and the competitiveness of labor ...................................................................................37 3.4 The availability and cost of finance in the Kenyan manufacturing sector.................................43 3.5 The cost of and access to finance in manufacturing firms.........................................................47 4 Chief Constraints to Competitiveness: Corruption, Crime and Infrastructure.........................54 4.1 Overview ...................................................................................................................................54 4.2 Corruption..................................................................................................................................54 4.3 Crime and Security....................................................................................................................58 4.4 Infrastructure .............................................................................................................................59 4.5 Other Key Barriers to Investment..............................................................................................68 5 Policy Reforms ..........................................................................................................................70 5.2 Improving the Quality of Labor.................................................................................................71 5.3 Improving Access to Finance ....................................................................................................72 5.4 Addressing Corruption and Crime.............................................................................................73 x 5.5 Accelerating Improvements in Infrastructure............................................................................77 5.6 Improving the Public-Private Dialogue.....................................................................................81 Policy Matrix ..............................................................................................................................................84 Bibliography ...............................................................................................................................................88 xi List of Tables and Figures List of Figures Figure 1.1: Annual GDP per capita growth rates ( per cent), 1975-2002 ......................................................................7 Figure 1.2: MVA per capita in levels (left, in 1998 $US) and annualized growth rate 1985-98 (right)........................8 Figure 1.3: Adult life expectancy (left) and infant mortality (right) in East Africa.......................................................8 Figure 1.4: Breakdown of employment by sector in 2003...........................................................................................11 Figure 1.5: Distribution of employment by industry and sector..................................................................................12 Figure 2.1: Capital intensity--Median capital per worker by firm size (000's $US)..................................................18 Figure 2.2: Investment levels in Kenya .......................................................................................................................19 Figure 2.3: Capital Productivity--Ratio of MVA to capital for the median firm, by firm size...................................20 Figure 2.4: Labor Productivity--MVA per worker (in 000s US$) for the median firm, by firm size.........................21 Figure 2.5: Share of workers that are permanent.........................................................................................................22 Figure 2.6: Export behaviour of sample firms, 2002/03..............................................................................................24 Figure 3.1: Highest Educational Achievement of Employees .....................................................................................32 Figure 3.2: Highest Educational Achievement of Employees in Manufacturing.........................................................33 Figure 3.3: Staff trained as a percentage of all permanent workers, by job category..................................................34 Figure 3.4: HIV-AIDS, perception of the managers/owners .......................................................................................36 Figure 3.5: Firms with HIV/AIDS prevention programs by type, 2003......................................................................36 Figure 3.6: Estimate of Monthly Earnings of Unskilled Production Workers (US$) ..................................................37 Figure 3.7: Monthly Cash Earnings (in US $ by position) in early 2003. ...................................................................38 Figure 3.8: Index of average real wages, 1986-2003...................................................................................................39 Figure 3.9: Ratio of total wages to MVA in the median firm, by firm size.................................................................40 Figure 3.10: Estimates of total wages to MVA in a series of developing economies..................................................40 Figure 3.11: Earnings levels and growth by sector......................................................................................................41 Figure 3.12: Minimum wage trends, 1993-2003 .........................................................................................................42 Figure 3.13: Share of firms rating finance as a "major" or "severe" constraint, by country .......................................45 Figure 3.14: Share of firms rating finance as a "major" or "severe" constraint, by firm characteristic.......................47 Figure 3.15: Sources of finance used across countries ................................................................................................48 Figure 3.16: Sources of finance used in Kenya ...........................................................................................................49 Figure 3.17: Use of different financial instruments.....................................................................................................49 Figure 3.18: The use and cost of credit across East Africa..........................................................................................50 Figure 3.19: Share of firms self-reporting that they are credit constrained .................................................................51 Figure 3.20: Why didn't firms apply for loans? An East African comparison ............................................................51 Figure 3.21: Why didn't firms apply for loans? A look at Kenya by firm size ...........................................................52 Figure 3.22: Percentage of loans backed by collateral and ratio of loan to collateral..................................................53 Figure 4.1: Barriers to business in Kenya--Firms rating the constraint as a "major" or severe" impediment to business..............................................................................................................................................................55 Figure 4.2: Corruption Perceptions Index--score and ranking [in brackets] ..............................................................56 Figure 4.3: Bribe requests by public agency or service, as a % of firms that used the service....................................58 Figure 4.4: Benchmarking Kenyan transport satisfaction............................................................................................60 Figure 4.5: Firms perceiving service to be "poor", "very poor" or "not available"......................................................61 Figure 4.6: Firms perceiving electricity service to be "poor", "very poor" or "not available") ...................................63 Figure 4.7: Benchmarking Kenya's energy sector.......................................................................................................64 Figure 4.8: per cent of firms perceiving service to be "poor", "very poor" or "not available" ....................................65 Figure 4.9: Benchmarking water service internationally.............................................................................................66 Figure 4.10: Firms perceiving telecom services to be "poor", "very poor" or "not available" ....................................66 Figure 4.11: Telecommunications as a business constraint in international perspective.............................................68 Figure 4.12: Firms rating service as "poor", "very poor", or "not available", by export status...................................68 xii List of Tables Table 1.1: Kenya at-a-glance.........................................................................................................................................2 Table 1.2: Structure of the surveyed sample..................................................................................................................5 Table 2.1: Relative capital intensity--Ratio of capital per worker in Kenya to other countries..................................21 Table 2.2: Determinants of Firm Level Productivity, Regression Results...................................................................27 Table 2.3: TFP is higher in some sectors in Tanzania than in Kenya and Uganda......................................................28 Table 2.4: Average TFP is higher in large firms, exporters, and firms with training programs ..................................29 Table 4.1: Bribe levels (for firms that paid bribes), in Ksh .........................................................................................56 Table 4.2: Incidence and cost of security in Kenya.....................................................................................................59 Table 4.3: The Cost of Telkom Kenya Services in 2002.............................................................................................67 xiii 1 Introduction and Motivation 1.1 The impetus for change: Kenya's struggling formal sector 1.1.1 To reach and maintain the 4.6 per cent GDP growth objective set out by the Government of Kenya (GoK), private enterprise (both formal and informal) is going to have to grow by at least 7.5 per cent annually--a sustained increase unprecedented in Kenyan history. In recent years pri- vate enterprise growth has been less than 2 per cent, and often negative. · Manufacturing employment rose by 7.3 per cent in 2002 and 6.3 per cent in 2003, so strong growth is possible. Yet these growth rates followed a period of recession, and may be diffi- cult to maintain. · Private enterprise has not sustained a high rate of growth for more than a handful of years for decades, if ever. Growth rates of 4 to 6 per cent were achieved briefly in the mid-1980s, and rates exceeding 20 per cent were recorded for 1977 and 1978. Otherwise the economy has grown slowly or declined. · Note that at current rates of population growth, the government's goal will only raise GDP per capita at 2.5% per year. To reach per capita growth of 5 per cent per year, on the other hand, private enterprise would have to grow by more than 12 per cent annually. 1.1.2 The Kenyan private sector has several important competitive advantages that will help it reach its growth goals. · In contrast to several of its close neighbours, Kenya is politically stable, recently executed a peaceful and democratic change of government, and is free of violent conflicts. · Several oft-mentioned geographic features--landlocked neighbours, coastal access, and a long-established port--make Kenya a natural eastern gateway to Africa. Cultural, linguistic, and historical ties to the UK and South Asia further enhance trade opportunities, especially when combined with a history of market-orientation, a business culture, and manufacturing. · Compared to the rest of Africa, Kenya possesses a relatively skilled and educated workforce, and labor productivity is high in comparison to both Tanzania and Uganda. · Firms' biggest complaint--petty corruption--has seen great improvement in the last year. TI Kenya reports less bribery activity, leading to a 68 per cent decrease in the average bribe. · Interest rates have decreased dramatically in the last year and banks are aggressively seeking lending clients, implying improvements in both the cost of and access to finance. · Finally there are several successful national industries. Kenyan tea and horticulture products continue to improve their position in world markets, while the nation's garment sector has experienced enormous growth due to US market access through the African Growth and Op- portunity Act (AGOA). 1.1.3 Yet current levels of investment, productivity, and exports are all insufficient to fund the required private growth. Raising all three is possible but will pose major challenges, particularly because all each has been in decline for some years. · The government estimates that investment rates, which have been declining for two decades, will need to rise to 23 per cent of GDP--rates not seen since the heady days of growth in the 1960s. Currently investment is roughly 15 per cent of GDP, and is barely large enough to re- place existing capital, let alone generate new capital. Most firms in 2002/03 invested nothing 1 in new plants or equipment. As a consequence, Kenya's capital stock is much older and less efficiently used than in East Africa, India, and China. · Productivity is not only low relative to strategic competitors like China and India, but it is also falling behind. Kenya's formal manufacturing firms have not seen gains in productivity in more than a decade. Since the early 1990s, productivity has declined about as often as it has risen. Meanwhile China and India have been making huge gains in firm productivity. · Exports must also be turned around. With the exception of the textiles sector, firms' propen- sity to export actually fell between 1999 and 2002. AGOA will help, as it has already in tex- tiles, but in other sectors Kenya will have to continue to compete against China and India. 1.1.3.1.1 Kenya at-a-glance Kenya Tanzania Uganda China 1995 2002 1995 2002 1995 2002 1995 2000 Macro environment GNI per capita (US$, PPP) 1,000 1,010 440 500 1,000 1,320 2,650 3,950 Population, mid-year (millions) 27 30 30 34 19 23 1,205 1,262 GDP growth (1991-95 and 1996-2000, avg %) 1.6 1.8 1.8 4.1 7.0 6.1 12.1 8.2 Openness (Imports+Exports/GDP) 71.4 62.1 46.0 48.6 32.6 39.8 45.7 49.1 FDI inflows (net, % GDP) 0.4 1.1 5.1 3.8 2.1 2.5 5.1 3.6 Governance Informal payments (% of revenue) - 3.8 - 1.5 - 2.4 - 1.4 Confidence in the judiciary (% disagree) - 51 - 53 - 70 - 7 Control of corruption (Scale of -5 to 5) - -1.0 - -1.0 - - - -0.3 Rule of law (Scale of -5 to 5) - -1.0 - -0.5 - - - -0.2 Political stability (Scale of -5 to 5) - -0.9 - -0.3 - - - 0.4 % of senior management time with govt officials - 14.0 - 16.0 - 0.4 - 7.0 Infrastructure Share of firms with own generator (%) - 70 - 55 - 35 - 27 Days to clear imports (longest in last year) - 20 - 33 - 11 - 12 Telephone lines in largest city (per 1000 people) 78 78 23 20 - 37 - 294 Personal computers (per 1000 people) 1 5 - 1 - 3 - 16 Paved roads (% of total) 14 12 4.2 - - 67 - 67 Finance Cost of capital (lending interest rate, %) 28.8 15.0 - - - 16.7 - 5.9 Share of credit from financial institutions (%) - 29 - 8 - 12 - 25 Credit to private sector (Stock, % of GDP) 34 30 13 29 - 7 - 125 Source: Investment Climate surveys, and WDI database. 1.1.4 The drive to increase productivity is even more urgent for Kenya because of its high and growing wage levels in all sectors. · Unskilled production worker wages in Kenya are the highest in our sample, and are twice the level in India. Once one accounts for differences in productivity across countries, the cost of Kenyan labor still seems high relative to India and China, although similar to East Africa. 2 · At the same time that firm productivity has been stagnating, manufacturing wages have risen steeply, further threatening the competitive position of Kenyan firms. Wages have grown throughout the economy, and average earnings in both the private and public sectors have more than doubled in the past decade. It is this wage growth that seems to account for the seemingly high relative cost of labor in Kenya. 1.1.5 Kenya will also need to address health issues in the workforce. What is most alarming is that, while one of the greatest threats to productive capacity is HIV/AIDS, this risk is unrecognized by many firms. More than half of the firms surveyed believed that none of their employees have HIV. HIV prevalence in the working-age population is estimated at 15 per cent. 1.1.6 So far the expansion of the informal sector has saved the Kenyan economy, providing jobs for the expanding working-age population and a source of economic growth. Yet the expansion of the in- formal sector has also limited economic expansion in many ways. · Informal firms are often constrained in their growth as their uncertain status limits their ac- cess to capital. It may also limit their access to public infrastructure and utilities. As a result these firms are typically small and relatively unproductive. · Moreover, informal firms do not contribute to the tax base and the growing need for public revenues. Such low levels of tax compliance likely discourage other individuals and firms from paying taxes as well. 1.1.7 In the face of these trends and the increasingly uncertain political climate, business confidence and investment is declining. That investor perceptions have turned negative is evident in interna- tional surveys such as the World Economic Forum's Africa Competitiveness Index, which places Kenya near the bottom in terms of economic governance and country risk ratings. The Institu- tional Investor Index ratings have fallen nearly 50 per cent since the end of the 1980s. 1.1.8 Declining business confidence, low investment, stagnating productivity, declining exports, and the growth of the informal sector at the expense of the formal one--all of these growing competi- tive disadvantages are direct consequences of the across-the-board deterioration in the investment climate. Key constraints on business include the following: · Political Instability. Political in-fighting, the instability and unpredictability of macroeco- nomic and private sector policies, and a history of stalled and half-hearted reform processes increase business uncertainty and risks. · Corruption. Rampant petty and grand corruption has hindered business for over a decade and, in spite of the improvements in the last year, persists at damaging levels. Recent high- profile corruption scandals have corroded the new government's reputation. · Poor infrastructure. Many firms must sacrifice their profits to purchase generators, dig their own wells, and repair their own roads as the provision of public goods like roads, water, and electricity has been extremely poor and unpredictable. Not only may self-provision of such services be inefficient in an economy-wide sense, but on an individual level they erode prof- its, discourage investment, and further reduce international competitiveness. For instance, the average Kenyan manufacturing firm lost more than nine per cent of output because of power failure, and experienced 33 outages per year, in addition to high voltage fluctuations. · Crime. Compared to Tanzania and Uganda, three times as many firms in Kenya report that crime and theft is a major impediment to business. One third of all Kenyan firms were vic- tims of crime. · Unsuitable financial instruments. While the cost of finance has come down dramatically in the last year, Kenyan banks do not appear to have the tools or capacity to evaluate and moni- tor loans to small and medium enterprises (SMEs) with profitable investment opportunities. 3 · Administrative constraints. Business entry and registration procedures are long and cum- bersome. Insolvency procedures are lengthy and costly. Poor governance has created wide- spread mistrust of the courts, making enforcement of contracts and security, and resolution of disputes, very difficult. · Ill-suited training. Kenya's formal training institutions have little orientation toward the practical needs of the enterprise sector, and firms cannot use the funds they pay into the train- ing levy to obtain productivity-enhancing training for their manufacturing workers. 1.1.9 Improving the investment climate--through improvements in policy stability, governance, secu- rity, infrastructure, finance, skills, and legal and administrative systems--will need to be a central focus of government policy in order to capitalize on positive economic trends and take advantage of the new optimism and momentum created in the wake of the last elections. 1.2 Description of the 2004 ICA Objectives and scope 1.2.1 The objectives of this study include the following: · To assess the current performance of formal manufacturing firms in light of past performance as well as the performance of regional and strategic competitors; · To identify the principal obstacles to increases in the growth and competitiveness of the Ken- yan manufacturing sector relative to strategic competitors; and, · To prioritize policy demands for private sector development and assess the ability of current policy initiatives to address the problems at hand. 1.2.2 While this study will consider diverse types of evidence from a variety of donor and government investigations, the principal focus will be upon the analysis and interpretation of data collected in surveys of formal manufacturing firms. 1.2.3 While this study will seek to provide policy prescriptions based on the available evidence, the nature of the analytical work--namely the analysis of manufacturing firm data--will be more useful at identify policy directions and priorities than specific tasks and action plans. Methodology and Data 1.2.4 The firm and worker surveys form the core of our analysis. The 2002/03 firm survey is the result of a partnership between a leading Kenyan Policy Research Institute (KIPPRA) and the Regional Program on Enterprise Development (RPED), which is based in the Africa Private Sector Group of the World Bank. 1.2.5 The sample was drawn from a recent census conducted by the Central Bureau of Statistics (CBS) of nearly 2,000 formal manufacturing firms employing more than 250,000 full-time employees. In order to ensure representation of all types of firms, the sample was stratified across location, sub-sectors, and size in 148 clusters: · Four locations were defined: Nairobi, Eldoret/Kisumu, Mombasa, and Nakuru. · Nine manufacturing sub-sectors were: Agro-industry, Chemicals/Paints, Construction Materi- als, Furniture, Metals, Paper/Publishing/Printing, Plastics, Textile/Leather, and Wood. Four size classes were used: Small (11-49 employees), Medium (50-99 employees), Large (100- 499 employees), and Very Large (500 and more employees). 4 1.2.6 368 firms were selected randomly from the clusters, representing roughly 20 per cent of all for- mal firms. Several firms, often non-African and foreign ones, refused to be interviewed, perhaps as a result of survey fatigue. Whenever possible, these firms were replaced with "new" firms hav- ing the same characteristics as the ones that refused. Due to the high rate of refusal, however, the replacement strategy was only partly successful and, in the end, 282 firms completed a survey. 1.2.7 Table 1.2 describes the sample. 282 firms employing more than 61,000 people were covered. · Roughly two-thirds of firms (employing about 27,000 workers) were stationed in Nairobi, and the largest industry was agro-industry, with a quarter of firms in this industry. · Half of the firms sampled had more than 5 per cent of sales in exports ("exporters" for this report), and about a fifth had more than 10 per cent foreign ownership ("foreign-owned"). 1.2.8 Not listed is the ethnicity of owners. Roughly three-quarters of the sample firms were "Asian" owned, and roughly a tenth were "African" owned. While the majority of firm owners are Ken- yan nationals, the manufacturing industry is largely owned by those of South Asian descent. 1.2.9 Firms were asked to complete a lengthy questionnaire with the assistance of an enumerator. Up to ten employees from each firm were also randomly sampled to complete a worker questionnaire, providing a database of more than 1,969 workers. 1.2.9.1.1 Structure of the surveyed sample Firm Size (%) Firm Location (%) Small (10-49 employees) 38.3 Nairobi 62.8 Medium (50-99 employees) 17.4 Mombasa 15.3 Large (100-499 employees) 31.1 Nakuru 11.4 Very Large (500+ employees) 13.3 Eldoret 6.4 Kisumu 4.3 Market Orientation (%) Firm Activity (%) Exporter (>=5% sales) 51.9 Agroindustry 24.5 Non-Exporter 48.1 Bakery 5.0 Chemicals and Paints 8.9 Firm Ownership (%) Construction Materials 6.0 Furniture 2.8 Publicly listed company 3.9 Garments 7.1 Publicly held, limited company 6.1 Leather 1.8 Privately held, limited company 77.6 Machinery 2.5 Partnership 5.3 Metal 14.9 Sole proprietorship 2.1 Paper, Printing, Publishing 6.4 Cooperative 2.1 Plastic 8.2 Other 2.9 Textile 7.8 Wood 4.3 Foreign (>=10% foreign ownership) 18.2 Domestic 82.8 Note: Source is 2002/03 Investment Climate survey. Additional Data 1.2.10 Data is frequently drawn from other country Investment Climate Assessments, and will be sourced appropriately. All ICAs share a core survey module and are designed to provide compa- 5 rable benchmarks. The Tanzania and Uganda ICAs are of particular interest. It is worth noting that the firm composition in these samples is somewhat different. · Whereas the Kenyan sample is 56 per cent small firms and 44 per cent large, Uganda is 88 per cent large firms and Tanzania is only 26 per cent large. Therefore where possible this re- port will typically try to look at differences at equivalent firm sizes when comparing across countries. · Kenyan firms are also more likely to export. In all countries, Agro-Industry is the dominant sub-sector. In Kenya the metals industry is the next largest industry, while in Uganda and Tanzania, where the metal industry is small, furniture is more significant. 1.2.11 In addition, in 1999/2000 a team from the Centre for the Study of African Economies at Oxford University collected firm data in Kenya in a similar survey exercise--the Kenyan Manufacturing Enterprise Survey (KMES). While the 2002/03 and 1999/2000 samples overlap, they do not con- stitute a panel. Even so, by comparing the two periods, and in some instances by pooling the two series, the use of the additional data improve our understanding of the sector. Structure of the Document 1.2.12 The remainder of this chapter describes the 2002/03 data collection, and provides background on the Kenyan economy and private sector, including economic structure, major trends, and a brief history of manufacturing in Kenya. The remainder of the document is organized as follows: · Chapter 2 examines the competitiveness of Kenyan firms in an international perspective, ex- panding on some of the sources of competitive disadvantage noted above. In particular, the analysis primarily at what the firm-level data say about the productivity of labor and capital, the competitiveness of wages, and the determinants of exporting. Kenya is considered relative to other East African nations as well as strategic competitors like China and India. · Chapter 3 examines the competitiveness of Kenya's key factors of production--labor and capital. Worker health and education and the relative cost of labor are discussed, as are the determinants of wages in the Kenyan manufacturing sector. The cost and availability of fi- nance is analyzed, identifying in what ways credit is constrained by factors other than the general investment climate. · Chapter 4 assesses the barriers to private sector growth in more detail, focusing on the top three concerns. Again the analysis focuses on the firm's perspective, drawing on opinion data from firm owners and managers, backed up with estimates of the magnitude of the barrier or issue using firm-level data. Kenya is benchmarked to its neighbours and competitors. · Chapter 5 examines how the investment climate has changed since the data collection in 2002/03, in order to set the scene for discussing current and relevant policy implications, and discusses the implications of the previous analysis for strategic policy priorities and, drawing on these lessons and those from related private sector studies, the chapter concludes by sum- marizing key policy implications. 1.3 General economic overview 1.3.1 The Kenyan private sector has had a tough decade. As a result of a number of factors, not least of which were severe economic mismanagement and growing corruption, almost every economic and social indicator showed steep decline from the mid-1990s until the end of 2002. There were several bright spots, however, including the cut flower and tourism sectors. Coffee and tea re- mained strong export crops, and the informal sector thrived. Kenya also maintained a strong fi- nancial sector throughout. In 2003 the economic and social decline appeared to slow, and growth 6 forecasts for 2004 are optimistic. Private sector employment is growing, interest rates are low, and aid is beginning to flow once again. These and other aspects of the Kenyan economy are ex- plored below. Economic structure 1.3.2 Kenya's economy is the largest in East Africa with a Gross National Income (GNI) of $12.2 bil- lion in 2002--more than a third larger than Tanzania's, and twice the size of Uganda's. 1.3.3 Agriculture continues to dominate the Kenyan economy, accounting (with forestry and fishing) for about 24 per cent of GDP. Agricultural products also make up the nation's principal exports. Agriculture's share of output has been declining, however, for four decades. 1.3.4 The formal manufacturing sector only accounts for 13 per cent of GDP and, with the recent ex- ception of the garment industry, has largely stagnated in terms of output, productivity and em- ployment. By contrast the small-scale informal manufacturing sector appears to have expanded rapidly and is estimated to make perhaps a fifth of GDP. 1.3.5 The informal sector in Kenya is large and growing, and currently employs about 40 per cent of the labor force. The sector includes all semi-organized, small-scale, and unregulated activities. They typically do not pay taxes, do not heed minimum wage or other regulations, and have poor property rights. The lack of formality and property rights limits their access to credit and con- strains growth opportunities. 1.3.6 Tourism is also a pillar of the Kenyan economy, accounting for 20 per cent of GDP and a signifi- cant portion of the country's foreign exchange earnings. The sector has been severely weakened in the face of repeated security problems and concerns. A decade of decline in economic growth and investment 1.3.7 Economic growth was generally robust in Kenya through the 1960s and 1970s, with GDP per capita increasing at an average of 2.9 per cent per annum, slowing to 0.6 per cent in the 1980s. Between 1990 and 2003, however, average GDP per capita growth actually declined by 0.72 per cent per annum. Figure 1.1 plots GDP per capita growth in East Africa from 1975 to 2002. 1.3.7.1 Annual GDP per capita growth rates ( per cent), 1975-2002 10.0 8.0 6.0 4.0 2.0 0.0 -2.0 -4.0 -6.0 -8.0 -10.0 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Kenya Tanzania Uganda Source: World Bank, Statistical Information and Management Analysis (SIMA) 1.3.8 Gross domestic investment has been falling for more than three decades, from 22 per cent of GDP in the 1970s and 1980s, to 17 per cent in the 1990s, to an estimated 15 per cent in 2002. Much of 7 the decline occurred in public sector investment--from about 10 per cent of GDP in the early part of the 1990s to about 4 per cent in 2002. 1.3.8.1 MVA per capita in levels (left, in 1998 $US) and annualized growth rate 1985-98 (right) Malaysia 936 Tanzania -5% Mauritius 739 Nigeria -2% Thailand 584 Kenya 1% South Africa 557 India 3% China 287 South Africa 3% India 65 Uganda 7% Nigeria 62 Malaysia 7% Kenya 37 China 8% Uganda 24 Thailand 10% Tanzania 16 Mauritius 11% Source: UNIDO, Industrial Development Report 2002/2003 1.3.9 Kenya is far less industrialized than many developing countries, and recent industrial growth has been low. In Figure 1.2 it can be seen that Manufacturing Value Added (MVA) per capita in Kenya is only US$37 in 1998. Out of 87 countries studied, Kenya ranked 77th. While Kenya per- formed better than its neighbours (Uganda ranked 81st and Tanzania ranked 85th) the Sub-Saharan Africa average was $40 per capita. Moreover, growth over 1985-98 was 1 per cent per annum, compared to Uganda's 7 per cent. If only the 1990s were examined, growth would be negative. 1.3.9.1 Adult life expectancy (left) and infant mortality (right) in East Africa 60 110 )sr 58 56 100 eay(yc 54 hstrib0 90 52 antcepxeefLi 50 80 48 001,rep 46 70 44 hsateD 60 42 40 50 8 4 7 3 6 9 2 1975 197 1981 198 198 1990 199 199 199 200 1980 1983 1986 1989 1992 1995 1998 2001 Kenya Tanzania Uganda Kenya Tanzania Uganda Note: Source is World Bank, Statistical Information and Management Analysis (SIMA). Life expectancy data are available for 1975, 1977, 1980, 1982, 1985, 1987, 1990, 1992, 1995, 1997, 1999, 2000, and 2002. Infant mortality data are available for 1980, 1990, 1995, 2000 and 2002. Other years are interpolated geometrically. 1.3.10 Foreign direct investment (FDI) has been relatively modest. According to UNCTAD, Kenya's foreign direct investment of about $50 million a year is much lower than those of its neighbours, such as Uganda and Tanzania, each of which has attracted more than $200 million annually. Low 8 and declining FDI is even more remarkable in that it took place at a time when the trade regime and economy were being liberalized. 1.3.11 In 1997, 52 per cent of Kenyans were living in poverty--a figure that has likely grown worse with the decline in per capita incomes. Important social indicators have also deteriorated. Be- tween 1990 and 2002/03 infant mortality increased from 63 to 78 per 1,000 live births, and adult life expectancy fell from 57 to 45 years (Fig 1.3). Current growth prospects 1.3.12 In 2004 Kenya may see its first rise in per capita GDP growth since 1996. · According to the Central Bank of Kenya (CBK), GDP growth in 2004 is expected to be 2.3 per cent, up from 1.8 per cent in 2003. Population growth was at 2 per cent in 2003, meaning GDP per capita fell slightly in that year. If population grows at less than 2.3 per cent in 2004, however, the country will see a slight rise in GDP per capita. · It is worth noting that the CBK's growth forecast for 2004 was recently downgraded from 3.1 per cent to 2.3 per cent due to drought and strained relations with donors. 1.3.13 Through the strategy outlined in the IP-ERS, the Government envisages annual GDP growth of 4.6 per cent, investment rates above 23 per cent of GDP, and inflation of less than 5 per cent. These forecasts have so far not been affected by the downturn in rains and donor relations. · Reasons given for not downgrading 2005 growth projections include strong growth in key sectors in the first six months of 2004. Tourism growth in this period was estimated at 11.5 per cent. Agriculture, textiles, telecommunications and financial services also experienced significant growth. · Near term growth should be boosted by a falling cost of capital. Domestic interest rates have tumbled, dramatically decreasing the cost of finance and spurring commercial banks to ag- gressively seek out private investments. Private sector credit grew by 11.5 per cent in May 2004 after a long period of stagnation in the demand for credit. 1.3.14 Fiscal balance and economic growth depend crucially on the continued disbursement of donor funds. As discussed below, donors have been very critical about official corruption and the Gov- ernment's capacity to manage aid disbursements, and aid flows could be delayed or suspended. Already the IMF has postponed an assessment meeting until October 2004. 1.3.15 In addition to depending on rains, agricultural performance, and the disbursement of donor funds, growth forecasts also depend crucially on investment in infrastructure and structural reforms, in particular better governance and political stability. Recent trends in fiscal and monetary policy 1.3.16 Kenya's macro environment is marked by a natural vulnerability and many near misses in eco- nomic policy, rather than reckless mismanagement. Fiscal policy is often off-track, but discipline is occasionally restored, even during periods of economic slump. Inflation has historically been high and volatile, but in recent years underlying inflation has been kept low and stable. The ex- change rate has been similarly variable, and although it has been fairly stable against the US dol- lar in the last few years, has recently been in decline. The current account has more often than not been in deficit, but the magnitude has seldom been alarming. Thus, with determined economic management, the country has the potential to deliver a more stable environment. 1.3.17 The main influence on economic conditions is fiscal policy. Here several factors have been par- ticularly important. Pre-election-spending has been high and at variance with the budgets. The 9 public wage bill is relatively large, estimated at 8.7 per cent of GDP in 2003/04 (not including parastatals), and is a significant fiscal burden. Revenues have been declining as a share of GDP (from 29 per cent in 1995/96 to 21 per cent in 2003). Slow economic growth has depressed the tax base, and tax administration has been poor. Finally, aid has been relatively small by regional standards, and frequent suspensions of donor support contribute to fiscal volatility. 1.3.18 There is reason to be optimistic about the fiscal outlook. The government is aiming to reduce the wage bill to 7.6 per cent of GDP by 2005/06 through voluntary retrenchment. Tax collections in 2003/04 were reported to be 4 per cent above target, suggesting that the government may have ended its revenue decline. Moreover, the war on corruption could raise donor assistance and make disbursements more predictable. The deficit in 2003/04 is projected at 3.5 per cent of GDP. The government's ability to achieve its fiscal targets is increasingly being called into question, how- ever. The GoK recently announced a substantial pay increase for its 130,000 civil servants, call- ing into question the commitment to reducing the wage bill. Several donor agencies have also threatened to freeze all budgetary support unless allegations of grand corruption in government are investigated and culprits prosecuted. 1.3.19 Kenya's external debt is low by international standards. By mid-2003, domestic public debt was at 25 per cent of GDP, with interest payments amounting to 14 per cent of total public expendi- tures. The net present value of Kenya's external debt to exports thus remains below the HIPC threshold. It is estimated that in 2002 the net present value of debt to exports ratio was 116 per cent, and the debt service to export ratio was 12 per cent. Kenya's external debt service is about 20 per cent of foreign exchange receipts (as of 2001), because a large proportion of its debt is on concessional terms. 1.3.20 After a decade of high inflation, monetary stability has returned and policy is expected to be used to keep inflation within a low target range. In the last two years the underlying inflation has been below 3 per cent. Measures of inflation fell during the year to June 2004 in spite of the rises in oil prices, transport costs (from enforcement of the new transport policy), and basic food prices. 1.3.21 Between 1992 and early 2002, the real effective exchange rate appreciated by more than 25 per cent, with adverse implications on Kenya's export competitiveness. During 2002 the real effec- tive exchange rate reversed its direction and modest depreciation was observed. Depreciation halted through 2003, but resumed in the first six months of 2004. The currency depreciation puts Kenyan exporters at an advantage, but importers of capital inputs, intermediate goods (including oil) and consumer products will suffer. 1.3.22 Kenya's overall balance of payments has been in surplus and international reserves have grown in recent years. In the external sector, Kenya has traditionally run trade deficits, which vary in mag- nitude from 1 per cent to 4 per cent of GDP. Trade deficits have usually been offset to a large ex- tent by a surplus in the invisibles account, keeping the current account deficits relatively narrow. Starting in 1997, however, the surplus on the invisibles account was sharply eroded as foreign ex- change from tourism plummeted and the foreign aid from donors was suspended on several occa- sions. Surplus has been maintained, however, mainly as a result of short-term capital inflows. Population and labor force 1.3.23 The population of Kenya in 2003 was roughly 32 million, with a working-age population (age 15 to 64) of approximately 18 million. While population has been growing at 2 to 2.5 per cent per annum, the working-age population is estimated to be growing at a rate of at least 3.5 per cent. Kenya's 1998/99 Integrated Labor Survey (ILS) estimated that nearly 23 per cent of the working age population were inactive, which applied to 2003 imply a labor force of 13.9 million. 10 1.3.24 Growth in formal sector employment has been insufficient to meet the demand for jobs created by a growing population. Significant growth in the informal sector has filled the gap. · Employment in the private sector expanded by 2.7 per cent in 2003, while employment in the public sector did not change. 2003 was in fact a strong year for formal employment growth; from 1998 to 2002 private sector employment grew at an average annual rate of 1.9 per cent, while public sector employment shrank by 1.1 per cent per year. · Employment in the informal sector is estimated to have grown by 9 per cent in 2003 (after growing at an annual average rate of 11.2 per cent from 1998 to 2002). 1.3.25 The formal private sector employed just over 1 million people in 2003, or roughly 7.7 per cent of the labor force. A breakdown of the labor force by sector can be seen in Figure 1.4. Roughly 4 million working age people are said to be inactive, and 6.5 million are either engaged in small- scale agriculture or unemployed. Unemployment levels are very difficult to estimate, in part be- cause underemployment is a more common affliction. Government estimates of unemployment range about 15 per cent, or roughly 2 million people, while an estimated 5.5 million are in the category of the underemployed or the working poor. 1.3.25.1 Breakdown of employment by sector in 2003 Total employment, 2003 Private sector employment, 2003 Mining Transport & 4,700 Communication Construction Self-employed Utilities 0.4% 49,300 53,100 65,700 Public sector 1,800 4.6% 5.0% 0.5% 659,100 0.2% 4.7% Privatesector Social &Personal 1,068,600 Services 7.7% 265,600 Financial & 24.9% Business Services Agriculture& 69,100 unemployed 6.5% 6,550,046 Wholesale,Retail, 47.2% Food&Hotel Informal 156,700 sector 14.7% 5,545,200 Agriculture 39.9% 259,600 Manufacturing 24.3% 208,700 19.5% Note: Calculations based on the 2004 Economic Survey, 2003 Statistical Abstract, and 1998/99 ILS. 1.3.26 Manufacturing is the third largest formal private industry by employment, and one of the fastest growing industries in 2003. · As seen in Figure 1.4, the formal manufacturing sector is estimated to have employed just over 200,000 people in 2003. After stagnating in 2000 and 2001, manufacturing employment is estimated to have grown by 7.3 per cent in 2002 and 6.3 per cent in 2003, especially in tex- tiles. · Within the formal private sector, the largest industry is social and personal services, with roughly a quarter of the formal private workforce (see Figure 1.5). This sector was also one of the fastest growing, with an annual average rate of growth of 2.6 per cent in 2000-03. 1.3.27 While manufacturing is a substantial employer in the formal sector, the informal sector claims 83 per cent of employment in manufacturing overall (see Figure 1.5). In fact, the informal sector dominates nearly every major industry in employment levels. 11 1.3.27.1 Distribution of employment by industry and sector Distribution of industryby sector Sectoral share of major industries 5 % Wholesale, 14 % 3 % Retail, Foo d & 41% 21% 38% Other 6% 3 1% Ho tel 22% 5% Transpo rt & 4% M anufacturing 83% 14% 2% Communication 5% M anufacturing 2 0% Construction 95% 5% Wholesale,Retail, Fo od & Hotel 59% Construction 71% 15% Transport & 67% 23% 10% Co mmunication Social& P ersonal 5% Services Social& Perso nal 66% 20% 15% 2 5% 3 % Services 9 % Informal Formal P ublic Public Formal Informal Note: Calculations based on the 2004 Economic Survey, 2003 Statistical Abstract, and 1999 Labor Force Survey from CBS. Education and health 1.3.28 Kenya has a highly educated workforce by African standards. · As a result of a post-independence expansion in education, Kenya has a significant pool of educated personnel, and the labor force is well-educated relative to the rest of East Africa. Adult literacy is estimated at 84 per cent (79 per cent for females) in 2001. · In 2001, 70 per cent of eligible children attended primary school and the primary school completion rate was estimated at 52 per cent (51 per cent for females). Moreover, 24 per cent of the relevant age group was enrolled in secondary school. In 2003 the GoK eliminated pri- mary school fees for the country, boosting enrolment. 1.3.29 Yet school enrolments and the quality of training have been declining. · The imposition of fees in 1985 led to a fall in primary school enrolment, and more than half of the children that do go to primary school do not finish. Gross secondary enrolment grew through independence to 1991, but since then enrolment has dropped substantially, likely due to the rising costs of education and a fall in employment opportunities.1 · Tertiary level enrolments in Kenya have stagnated and are at the low end for Sub-Saharan Af- rica, especially in technical and vocational subjects. · The quality of industrial training is inadequate to firms' needs, a subject discussed in more detail in Chapter 4. 1.3.30 UNAIDS has estimated the HIV infection rate for Kenya at 15 per cent in 2001. These figures are expected to increase due to the high rates of transmission in the young and sexually active popu- lation. In addition to overstretching the health system, the EIU reports that every day the disease kills 700 people under age 40, and short-term economic costs (including caring for the sick and lost labor) amount to US$6.5m a month. 1.3.31 The education, health, wages and productivity of the Kenyan workforce are analyzed further in Chapter 3, using the ICA survey data and information from the CBS. 1World Bank CEM (2003) 12 The Kenyan financial sector 1.3.32 Kenyan has a relatively diversified and developed financial sector with the region's largest stock exchange, 43 commercial banks, and a large insurance industry. There has been a dramatic and positive turnaround in the Kenyan financial sector since the 1990s when the economy was suffer- ing, foreign aid was cut, corruption intensified, and interest rates climbed to more than 90 per cent. With an improving economy and government reform and stabilization, rates are roughly 16 per cent, bank profits are up and the sector is growing. 1.3.33 The health of the financial sector and the impact on the cost of and access to credit and finance of manufacturing firms are discussed at length in Chapter 3. Trade in the Kenyan economy 1.3.34 Kenya's new strategy for economic recovery relies on substantial export growth. Currently the tea industry is the largest export earner, and together with coffee, sugar and horticulture make up more than half of export earnings. Horticulture, in particular the cut flower industry, has seen rapid growth since the mid-1980s. 1.3.35 There has also been a significant increase of textile exports in recent years. Export markets have also become more diversified, as East African markets have become larger than European mar- kets and the US market has expanded substantially since the year 1999/2000. Kenya's imports have been dominated by machinery, equipment and fuels, which together account for about 90 per cent of total imports. 1.3.36 As part of the planned formation customs union with Tanzania and Uganda in 2005, the GoK plans to reduce or eliminate tariffs between member states. In economic terms, the most impor- tant regional integration efforts are the Common Market of Eastern and Southern Africa (CO- MESA) where Kenya is also a member of COMESA, and most of its manufacturing exports go to member countries. COMESA members have also agreed to move to a customs union by 2005, which includes the establishment of a common external tariff. Crime and Security 1.3.37 Crime. Crime escalated in Kenya from the mid-1980s, and by the 1990s violent crime and inse- curity were among the hallmarks of Kenya (and Nairobi in particular). Banditry became common in the rural areas, and housebreaking and violent car robbery became commonplace in Nairobi. Consequently, the UN has given Nairobi a security rating below that of Jerusalem and Bogotá.2 While the rise in crime is undoubtedly related to the rise in urban poverty and unemployment, one study argues that the crime wave can also be traced to flaws in the policing and political systems.3 · In general the police force is widely recognized as being underpaid and under-equipped, and a lack of discipline resulted in police violence becoming a commonplace in the 1990s. It is widely acknowledged that, historically, a sizable fraction of the police force has participated directly or has been complicit in criminal activity. As a consequence, by 2000 the police were widely feared and hated. · The political will of the Moi regime to halt crime was also questionable. The study notes that State-sponsored violence was consistent with the suppression of political pluralism. In the mid-1990s Moi would attribute the rising crime and violence to political activists in league with Western powers seeking to undermine his authority. 2EIU, 2004. 3Gimode, 2001. 13 1.3.38 Several terror incidents illustrate Kenya's terrorist security risk, including the 1998 US embassy bombing, the 2002/03 suicide bomb attack in Mombasa, and the simultaneous (but unsuccessful) missile attack on an Israeli airliner. A perceived terrorist threat against British Airways flights re- sulted in the cancellation of many international flights in June 2002/03 (and was accompanied by a travel warning from several Western countries). Such incidents have been extremely damaging to Kenya's large tourism industry. Donor support 1.3.39 The Government has already begun to normalize relations with donors. For instance, in 2003 the World Bank resumed credits and grants to the country and the International Monetary Fund (IMF) concluded arrangements for a poverty reduction and growth facility (PRGF). In return for donor support the GoK has committed to restructure the public sector, reduce the civil service wage bill, attack corruption, increase development pending, privatize state institutions, and re- form the financial sector. An August 2004 IMF assessment mission has recently been postponed amid growing concerns growing concerns over official corruption and the lack of institutional ca- pacity to manage donor funds. The postponement means that further aid disbursements will be delayed until at least October, and possibly later if a positive assessment is not made at that time. 1.3.40 The postponement of the assessment mission, which was due this week, to next month means that IMF disbursements to Kenya will resume from late October if the team makes a positive recom- mendation to the IMF board. 1.3.41 Donor pressure is most public and acute in the realm of anti-corruption. The US, the EU and oth- ers regularly and vocally criticize the pace and extent of investigations into high-level corruption. Cuts and delays in aid have been promised if the government does not take more serious action against current and former public officials implicated in corruption scandals. 1.4 A short history of Kenyan industry 1.4.1 Through the 1950s and 1960s Kenya, with its massive advances in industry, economic growth and standards of living, was one of the developing world's greatest success stories. With eco- nomic shocks and mismanagement, this success flagged in the 1970s, dwindled in the 1980's, and--after a brief rally in the early 1990's following important reforms--has since stagnated. 1.4.2 Lacking confidence in the ability of the private sector alone to generate industrial growth, the government initially took an active role in growing the manufacturing sector through investments in parastatal firms, trade restrictions, and currency overvaluation. While state-led development and import substitution led initially to growth and diversification, by 1980 its limitations had be- come obvious. Inward-looking policies undermined the competitiveness of Kenyan products in export markets and foreign investment slowed. 1.4.3 In the 1980s Kenya turned away from import substitution toward structural reform. These reforms helped stabilize and grow the economy. By the middle of the 1990s, Kenya had a regional finan- cial centre in Nairobi, with the second largest stock market in the continent, a large manufactur- ing sector, a dynamic tourism market and the largest exports in Africa of such agricultural prod- ucts as tea and horticulture. In spite of the macroeconomic stabilization and growth of the second half of the 1980s, the impact on formal private industry was limited. Stagnation of investment implied that a number of structural factors mattered beyond simple macroeconomic stability. 1.4.4 Notable in this period is the growth of small informal firms. By the 1990s there were more people in informal than formal employment. The informal sector continues to employ more than 85 per cent of the manufacturing workforce and, in contrast to formal sector firms, tend to be largely Af- 14 rican-owned. Yet firm surveys in the 1990s, these African-owned firms still tended to be smaller, younger, owner-managed, and less productive. They had less access to credit, were more diversi- fied, operated in more competitive markets, and were less able to self-provide for infrastructure or to participate in export markets. By contrast, the larger firms, owned mainly by Asian Kenyans, enjoyed higher market power and were more specialized. They also showed greater export market orientation, had better access to credit, and were more productive. 1.4.5 Corruption, economic mismanagement, and the slow process of democratization continued to hinder the economy and growth in the early 1990s was poor. · Aid restrictions, expansionary policy and political violence in the lead-up to the multi-party elections in 1992 destabilized the economy. Signs of recovery appeared in 1994 and 1995, but firms remained very concerned about corruption and political stability. · The benefits accruing from the structural adjustment measures were gradually eroded by a highly irresponsible economic policy stance, backtracking on declared policies, a restrictive economic control regime, and severe governance problems. · Corruption reached new heights in the last years of the Moi regime. Compliance with aid conditions was often only superficial. It is not surprising, therefore, that reforms could not be sustained for long. · Public infrastructure deteriorated as construction and maintenance funds were cut, misdi- rected, or misused. Infrastructure issues are discussed at greater length in Chapter 4. 1.4.6 As a consequence of the deterioration in governance, economic management, aid, political stabil- ity and infrastructure, firm performance suffered. · Firms, especially small ones, were plagued by high levels of risk in their market and produc- tion, and hence appeared reluctant to specialize and faced a high cost of capital. Combined with exorbitant base interest rates, few firms could take loans. · Investment levels had dropped to about 10 per cent of GDP by the late 1990s. FDI levels dropped precipitously and capital outflows intensified. · Manufacturing firm productivity through the 1990s was largely stagnant, declining as often as it improved, a topic investigated in Chapter 2. · Rising unit labor costs has also reduced the competitiveness of manufacturing firms. Wages doubled between 1994 and 2003, a topic explored further in Chapter 4. · There was very little foreign ownership of manufacturing firms in Kenya (often an important factor in technological upgrading and efficiency improvement). 1.4.7 Analysis of macroeconomic and firm data in the 1990s also implies that economic and trade re- form policies failed to bring the expected benefits. · Trade liberalization negatively affected most manufacturing firms, revealing their inability to compete. Many firms closed down, partly because of unfair competition from imports due to massive duty evasion. · Trade liberalization also did not stimulate private sector investment. Part of the reason may be that manufacturers were able to employ underutilized capacity in production. Investment was also constrained, however, by the high cost of imported inputs, rising interest rates and, particularly for the smaller firms, lack of access to credit. · Trade disputes were also common, and mechanisms for settlement were inefficient. · Although the implementation of reforms was not smooth, it improved the availability of im- ported raw materials and foreign exchange, increased opportunities for importing industrial equipment, and opened opportunities for exporting. 15 2 The Competitiveness of Kenyan Firms in National and International Perspective 2.1 Overview 2.1.1 Sustained increases in economic growth and well-being of the sort experienced by Europe, the US and East Asia have been based on increases in investment and improvements in productivity. · In addition to funding expansion, investment keeps capital equipment updated and assists in the import of skills and knowledge from abroad. · Increases in employment, in investment, and in natural resources will all raise economic out- put, but only account for a small fraction of the expansion in the world's most successful economies. Rather, it is improvements in technological know-how and efficiency--i.e., pro- ductivity--that increase wealth. 2.1.2 This chapter examines the investment and productivity of Kenyan manufacturing firms, looking at patterns within the country and benchmarking Kenya to strategic competitors. It looks at the ef- fectiveness and efficiency of key inputs--capital and labor--as well as the productivity of overall operations. 2.1.3 It is first seen that Kenyan capital productivity is low while its use of capital is relatively high. The capital stock is unusually old, capacity utilization is poor, and investment levels in 2002/03 were very low after decades of decline. These findings suggest that Kenyan plants and equipment are outdated, overvalued and inefficiently used. 2.1.4 At first glance Kenyan labor productivity, on the other hand, seems relatively competitive. This strength is deceptive, however, since labor productivity is not a reliable measure when there are large differences in capital usage and casual labor across countries. · The measure of labor productivity--manufacturing value-added per permanent employee--is high in Kenya relative to East Africa, is of a comparable level to that of India, and is lower than in China. · Kenyan firms, however, have much more capital per worker than almost all other countries examined--5 times more capital per worker, for example, than in India. For a given amount of capital, Kenya workers are thus relatively unproductive in comparison to China and India, and have less of an edge over East Africa. That is, the average Indian worker produces the same amount of output as Kenyan workers using a fifth of the plant and machinery. We ex- amine the reasons for this difference in productivity in this as well as subsequent chapters of this ICA. 2.1.5 Performing a "total factor productivity analysis", where the marginal contribution of labor and capital is estimated, it is seen that the average firm in Kenya has only a slight productivity advan- tage, if any, over Tanzania and Uganda. · Labor is more productive than capital, and indeed appears better in Kenya than in the rest of East Africa. Yet in terms of overall firm productivity, Kenyan firms have little if any advan- tage over Tanzanian and Ugandan ones, largely because of its capital intensity. · Within East Africa, larger firms and exporters are on average the most productive. Agro- Industry, Chemicals, and Metals firms are the most productive, with Textiles among the least. 16 2.1.6 The productivity gap between Asia and East Africa is also growing. An analysis of the Kenyan experience over time, moreover, implies that Kenyan productivity has been stagnating or declin- ing. Meanwhile, there is ample evidence that firms in India and China advance. 2.1.7 Low levels of average productivity probably account for the poor export performance of the aver- age Kenyan firm. While AGOA and other trade agreements appear to have given a boost to the textile sector, the average firm showed little or no productivity growth and little change in the propensity to export. · Excluding textile firms the propensity to export at the firm level actually fell between 1999/2000 and 2002/2003, while at the same time exports at the country level grew substan- tially. Firms in the textile sector were the only ones that registered improvements in both pro- ductivity and exporting. · This evidence suggests that only a small number of firms are productive enough to compete internationally, in a handful of sectors that are demand-driven. Kenya's rising export levels are driven by these firms, not the general population. 2.1.8 Within East Africa, however, Kenya still maintains an exporting edge over the rest of East Africa, which is suggestive of a mild productivity edge. · Kenya manufacturers export heavily to Uganda and Tanzania, as well as to North America and Europe. Tanzanian and Ugandan firms, on the other hand, are much less likely to export to Kenya or abroad. · While Kenya's edge may be driven by a slight productivity advantage, it may simply be his- torical or geographical, or it may be related to other factors impossible to capture in produc- tivity analysis. 2.2 The quality, use, and accumulation of capital in Kenya 2.2.1 This section begins by looking at the capital stock. Firm owners and managers were asked to es- timate the age and value of their capital stock, specifically the replacement value of plants and equipment. Age and intensity of capital 2.2.2 One of the most striking findings is that Kenya's capital stock is largely outdated. Only 20 per cent of manufacturing capital is less than five years old, compared to more than 30 per cent in Tanzania and more than 40 per cent in Uganda. Vintage capital may explain the poor productivity performance, and implies that Kenyan firms are exceptionally slow to adopt new technologies. 2.2.3 Kenyan firms are also running far short of capacity. According to the survey data, Kenyan manu- facturing firms are running at just two-thirds of capacity. This capacity utilization is marginally better than other East African firms, but substantially worse than strategic competitors like India and China. · Low utilization is probably partly a result of poor management, unreliable power, and volatile demand, but may also be a tool for uncompetitive practices--spare capacity can be used to discourage new market entrants, keeping individual firm profits high at the expense of com- petition, productivity and economic growth. 2.2.4 In Figure 2.1 it can be seen that Kenya is also extremely capital intensive in comparison to its neighbors and to India and China, in every firm category. 17 · In most of the countries, capital intensity increases in firm size. Not so in Kenya, where large- sized firms appear far more capital-rich than very large firms. 2.2.4.1 Capital intensity--Median capital per worker by firm size (000's $US) 19.3 16.8 11.411.5 7.4 7.4 7.5 7.8 8.5 7.7 6.7 5.46.1 4.2 1.0 0.81.42.5 1.5 1.9 2.0 3.0 2.4 Kenya Tanzania Uganda India China Micro (<10 emp) Small (10-49 emp) Medium (50-99 emp) Large & Very Large (>100 emp) All Note: Data on Tanzania, Uganda, India and China are from their respective ICAs. Capital is the manager's estimate of the re- placement value of plant and equipment. Workers are the number of permanent full-time employees. Casual labor is excluded. 2.2.5 Capital-intensive manufacturing can be optimal and efficient, especially in high value-added in- dustries. Kenya's capital intensity, however, is more likely a sign of aged and overvalued capital used inefficiently. · High capital intensity is consistent with having highly skilled labor (assuming educated workers are more efficient and can handle more sophisticated equipment). Kenyan workers are indeed more skilled relative to their East African counterparts, that may explain some of the difference, and indeed it can be seen below that labor in Kenya is relatively productive. Even so, the gap between Kenya and Uganda, India and China is so large that this explana- tion is not fully satisfactory. Moreover, few Kenyan firms produce sophisticated goods re- quiring highly skilled labor and complex equipment, making this explanation even more unlikely. · Capital intensity is also consistent with relatively costly labor--firms will substitute capital for labor as it becomes more costly. The cost of capital, however, has also been relatively high, and in the next subsection it can be seen that investment rates have been low, so this explanation also seems unsatisfactory. · An explanation more consistent with the facts is that Kenyan firms employ low quality capi- tal equipment and do even this inefficiently. Low investment rates, low capacity utilization and an aged capital stock suggest that many firms are running on old machinery and are hesi- tant to update. Reports of the value of capital equipment and buildings are also likely over- stated, and should be depreciated in value. Capital investment 2.2.6 Investment is extremely low. Figure 2.2 shows the frequency distribution of investment rates in the 2002/03 data. Of the 202 firms for which complete information is available, only 15 per cent of firms have investment rates exceeding 10 per cent--the rate one might reasonably assume is required simply to replace worn-out equipment. More than two thirds of the firms reported in- vestment rates of less than 5 per cent. A third of all firms reported zero investment. 2.2.7 Investment rates have been similarly low since the early 1990s. RPED data from the early 1990s through to 1999/2000 indicates that approximately half of the firms undertook no investment whatsoever in a given year. Further, those who do invest tend to have low investment rates, and 18 approximately 75 per cent of the firms had investment rates less than 0.16 in the early 1990s (and less than 0.1 in 1999/2000.4 2.2.8 Low levels of firm investment are consistent with the low and declining rates of capital invest- ment observed in the Kenyan economy. Figure 2.2 displays the gross capital formation in Kenya as a per cent of GDP over 42 years. From peaks of nearly 30 per cent of GDP in the late 1970s, investment has declined to less than 14 per cent by 2002--a level not seen since Mau Mau. 2.2.8.1 Investment levels in Kenya Investment as a %of capital in Gross capital investment in Kenya, 1960-2002 sample firms 30 >50% 28 40-50% 26 30-40% 24 IP-ERS target rate 22 20-30% 20 10-20% PDGfo % 18 5-10% 16 0-5% 14 0 12 10 0 0.1 0.2 0.3 0.4 0.5 Proportion of firms 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 Note: Firm-level capital investment rates are defined as gross investment in plant and equipment divided by the replacement value of plant and equipment. Economy-wide gross capital investment rates 2.2.9 There are several plausible explanations why investment may be so low, all of which indicate that the investment climate has been unfavourable. · The Kenyan economy was in the midst of a recession, after stagnating or declining for a dec- ade. With few profitable investment projects, the demand for investment may have been low. Yet investment activity was consistently poor through a variety of economic conditions in the last decade, including trade liberalization in the early 1990s, suggesting that other forces may be at work. · Recent theory also emphasizes that investment often is irreversible, and that as a result firms may be reluctant to invest if uncertainty is high. In Chapter 4 it will be noted that political and business uncertainty was especially high in 2002/03, and firms did not generally perceive the investment climate as conducive to expansion. · The demand for investment would also weaken if a poor investment climate diminished the expected profitability of investment projects. Chapter 4 quantifies the high costs firms in- curred from corruption, crime, unreliable electricity, transport, and the need to provide one's one infrastructure, all of which would diminish the expected return on manufacturing. · Another explanation would be that firms are unable to raise the necessary funds to finance in- vestment, for example because of a poorly functioning financial market. Chapter 3 examines the cost of and access to finance, and conclude that the cost of finance was indeed prohibitive 4Söderbom (2001). 19 in the mid-1990s, and still very high in 2002/03. The availability of finance has also been limited by high transactions costs, especially for smaller firms. 2.2.10 It is worth noting that, while economic growth and uncertainty have undoubtedly improved since 2002/03, it is not clear that the improvement has been dramatic. Economic growth continues to be negligible, and the political climate is still uncertain. Further improvements may be necessary be- fore firms begin to invest on a large scale. 2.3 Firm productivity in international perspective Capital productivity 2.3.1 As seen in Figure 2.3, Kenyan firms appear to have much lower capital productivity compared to those in India and China. · Given the capital intensity of Kenyan firms, this is not a surprising result. The gap between Kenya and these Asian countries is quite large, however, suggesting a less efficient use of capital overall. 2.3.2 Capital productivity seems similar in Tanzania and Kenya, especially among large firms where capital intensity in the two countries is almost identical. This suggests that capital is just as ineffi- ciently used in both countries. 2.3.2.1 Capital Productivity--Ratio of MVA to capital for the median firm, by firm size 1.5 1.3 1.1 1.2 1.1 0.8 0.9 0.8 0.6 0.7 0.7 0.7 0.6 0.5 0.5 0.5 0.3 0.3 0.4 0.4 0.4 0.4 0.3 0.1 Kenya Tanzania Uganda India China Micro (<10 emp) Small (10-49 emp) Medium (50-99 emp) Large & Very Large (>100 emp) All Note: Data on Tanzania, Uganda, India and China are from their respective ICAs. Capital is the manager's estimate of the re- placement value of plant and equipment. Labor Productivity 2.3.3 Labor productivity is simply the ratio of MVA to the number of permanent employees. As Figure 2.4 shows, the median Kenyan worker produces $3,457 of MVA per year, two-thirds more than the median Tanzanian worker, and three times more than the average Ugandan. 2.3.4 What is notable is that China and India--nations whose firms are more labor-intensive--have similar labor productivity to Kenya in nearly all firm classes. Anecdotal evidence would tend to suggest the opposite conclusion--that China and India have a substantial productivity edge over Kenya. 20 2.3.4.1 Labor Productivity--MVA per worker (in 000s US$) for the median firm, by firm size 5.3 4.64.8 4.1 4.1 4.2 4.4 3.5 3.3 3.5 3.3 3.1 3.2 3.4 2.9 2.4 2.1 1.9 1.5 1.4 1.0 1.1 0.9 0.6 Kenya Tanzania Uganda India China Micro (<10 emp) Small (10-49 emp) Medium (50-99 emp) Large & Very Large (>100 emp) All Note: Data on Tanzania, Uganda, India and China are from their respective ICAs. Workers are the number of full time perma- nent employees. Casual labor is excluded.. 2.3.5 The measure of labor productivity can be unreliable, however, when there are differences in the usage of capital. Looking at this simple measure of total factor productivity, Kenyan firms do in fact appear to be less productive than ones in India and China. · Labor productivity is not a reliable measure when there are large differences in capital usage across countries. MVA per worker is only a partial measure of productivity, and disregards the tools and equipment and investment in each worker. · Table 2.1compares the ratio of capital intensities and labor productivities between Kenya and its competitors. Kenyan firms are many times more capital intensive than firms in other coun- tries: 1.5 times Tanzania and China, 7.9 times Uganda, and 4.8 times India. Yet in spite of this heavier investment in equipment for workers, Kenya's labor productivity is the same as that in India, and less than that in China. · If Kenya's capital-intensive strategy were as productive as India's and China's labor- intensive, one would expect Kenya's labor productivity to be superior. The next subsection bolsters these claims in a formal analysis of total factor productivity within East Africa. 2.3.5.1.1 Relative capital intensity--Ratio of capital per worker in Kenya to other countries Kenya:Tanzania Kenya:Uganda Kenya:India Kenya:China K/L MVA/L K/L MVA/L K/L MVA/L K/L MVA/L Small (10-49 emp) 1.0 1.6 5.3 2.7 3.7 0.8 1.4 0.5 Medium (50-99 emp) 2.2 1.3 6.9 3.0 5.7 1.3 2.8 0.9 Large & Very Large (>100 emp) 0.6 1.2 1.7 1.2 2.7 0.8 1.3 1.0 All firms 1.5 1.7 7.9 3.2 4.8 1.0 1.5 0.8 Source: Investment Climate surveys 2.3.6 The measure of labor productivity can also be unreliable, moreover, when there are differences in the use of casual labor across countries. · Because of difficulties in collecting data on the number of hours worked by part-time and casual employees, labor productivity statistics are calculated using only the number of per- manent employees. · In Figure 2.5, however, it can be seen that while Kenya uses casual labor in proportions simi- lar to that in Tanzania, Uganda and India, many fewer casual workers are employed in China. This suggests that the Chinese labor productivity measure is understated, and that the ratio of labor productivity between Kenya and China is much lower than 0.8. 21 2.3.6.1 Share of workers that are permanent 86% 68% 64% 60% 56% Kenya Tanzania Uganda China India Source: Investment Climate assessments Total factor productivity 2.3.7 The previous measures of factor productivity provide some insight into firm performance, but they can provide a misleading indication of overall productivity when considered in isolation. · For instance, it has been shown that it is difficult to compare the productivity of capital across countries when different countries make different choices about the mixture of labor and capital inputs. One needs to look at the contribution of capital holding labor constant. 2.3.8 Multivariate regression analysis, however, will allow us to look at capital, labor and the other elements of productivity simultaneously rather than in isolation. Unfortunately, because of com- parability issues in the data, it is only possible to perform this analysis on East African firms, and not compare Kenya to China and India. · In particular, regression analysis will give us estimates of firms' technical know-how and ef- ficiency, what is known as total factor productivity (TFP). TFP is essentially what is left over once the inputs--that is, the intermediate goods, capital, and labor--that went into producing output are accounted for. It is the element of value added that can't be directly explained, and when looking at a large number of firms it can be taken as a measure of their efficiency. · Full details of the analysis are provided in Annex III. 2.3.9 Pooling our survey data for East Africa, it can be seen that on the margin labor is roughly twice as productive as capital. · The marginal contribution of capital to output is very low. A one per cent increase in the capital stock is associated with just a 0.12 per cent increase in manufacturing output. The low productivity of capital may be an indication of the low efficiency of capital in East Africa, but is more likely to be a reflection of the high capital intensity of East African firms. That is, there are diminishing returns to additional capital. · A one per cent increase in employment is associated with a 0.25 per cent increase in output. Hence labor's marginal contribution to output is about twice that of capital, which again is probably reflective of the relatively high intensity of capital use. 2.3.10 Kenyan firms also have TFP remarkably similar to their East African counterparts, with perhaps a weak advantage. 22 · Based on the TFP analysis, an average firm, given the same factor inputs, produces 12.75 per cent more in Kenya than one in Tanzania. Likewise, given the same inputs, output for the av- erage firm in Uganda would be 1 per cent lower than in Kenya. These productive edges per- sist at the sector level as well. · Yet because these country differences are both small and estimated with error, one cannot re- ject the proposition that all three countries have similar levels of productivity. 2.3.11 Productivity performance is also linked to firm characteristics. · In Kenya, the large agro-industry sector, as well as the smaller chemicals/paints and construc- tion materials sectors, are the most productive. Chemicals and paints firms appear extremely productive--in Kenya they are three times more productive than agro-industry, and nine times more productive than textile firms. Textile firms are typically among the least produc- tive overall. Similar patterns hold in Uganda and Tanzania. · On average, very large firms (those with more than 250 employees) tend to have a much higher TFP than smaller firms do. Given the same inputs, the average very large firm can produce more than twice as much output than small and medium firms, and approximately 50 per cent more than large firms. · Firms that export also have much higher TFP than non-exporters. With the same inputs, ob- serve that the exporting firms typically produce twice as much output than non-exporters. · There is no apparent correlation between firm age and productivity. · There is substantial geographic heterogeneity, and firms in Nairobi are substantially more productive than elsewhere in the country. For instance, in 2002/03, compared to the average firm in Nairobi, one in Mombasa was only 60 per cent as productive. Productivity Growth 2.3.12 Productivity growth in Kenya has historically been zero or negative, especially in recent years. Productivity declined by 0.5 per cent per year 1991-1998. · One study found that productivity growth from 1964-1994 was -0.12 per cent per annum.5 · An IMF report6 found that TFP in the manufacturing sector grew at an annual rate of 0.8 per cent during 1973-98. However, performance was uneven during different periods. TFP re- mained constant during 1973-80, 2.5 per cent a year during 1981-90, and -0.5 per cent in 1991-98. This result is corroborated from evidence from RPED surveys 1993-1996, which see negative productivity growth in manufacturing firms. · Accordingly, growth in the size of the manufacturing sector appears to have been driven by increases in inputs rather than improvements in efficiency and productivity. Higher demand from East Africa, Europe and America (through AGOA) may explain the increase in scale. 2.3.13 Regression analysis of recent firm data suggests that, between 1999/2000 and 2002/03, almost no productivity improvement is visible in the average firm.7 · There has been virtually no change in labor productivity. A one per cent increase in employ- ment results in a 0.7 per cent increase in MVA in both 1999/2000 and 2002/03. · Capital seems moderately more productive in 2002/03, although the improvement is not sta- tistically significant. A one per cent increase in capital resulted in a 0.3 per cent increase in MVA in 1999/2000, and a .4 per cent increase in MVA in 2002/03. 5Gerdin (1997, Ch 6) 6IMF (1999) 7Details of the regression analysis are reported in Annex III. 23 · Total factor productivity shows a small but statistically insignificant improvement between 1999/2000 and 2002/03. Given the same inputs, firms in 2002/03 appeared to be able to product 7 per cent more MVA. This estimate, however, is not statistically significantly differ- ent from zero. · Moreover, investment rates are low in both periods, and appear insufficient to replace worn- out capital. Permanent employment is almost unchanged. Since the CBS reported that total manufacturing employment increased by 7 per cent from 2000 to 2002, this growth probably came from an increase in the number of firms rather than an increase in the size of the aver- age firm. 2.4 Kenyan manufacturing exports 2.4.1 Kenya appears to be more export oriented than its neighbours and strategic competitors. In Figure 2.6, it can be seen that 57 per cent of the Kenyan sample exported at least some fraction of their output, more than twice the proportion of the Tanzanian and Ugandan sample. 2.4.1.1 Export behaviour of sample firms, 2002/03. % firms exporting Average exports as a % of sales Kenya 57% China 19% China 38% Kenya 17% Tanzania 26% Pakistan 17% Pakistan 20% Tanzania 12% Uganda 19% Uganda 10% Note: Data from China, Tanzania, Pakistan and Uganda drawn from the respective ICAs. 2.4.2 Kenya's export success appears to be principally a product of its industrial shipments to the rest of Africa. · Uganda and Tanzania absorb more than half of exports of all manufacturing output from Kenya. A fifth of exports go elsewhere in Africa. About a tenth of exports go to Europe and North America. 2.4.3 Kenya's industrial exports to the rest of Africa are not matched by its East African neighbours, suggesting industrial superiority in spite of the weak productivity advantages. Sources of this su- periority are only speculative, but the list includes higher levels of education, access to the coast, recent promotion of EPZ policies, a colonial history of light manufacturing, a post-colonial em- brace of capitalism, and more limited efforts to expropriate industry from the ethnically Asian businesspersons. · Even after controlling for firm size, sector of operations, and age of the firm, Tanzanian firms are eighteen per cent less likely to export and export less than Kenyan firms. · The difference is primarily due to differences in their exporting behaviour within Africa. Whereas 43 per cent of Kenyan firms exported to other countries in Africa, only 13 and 11 per cent of Tanzanian and Ugandan firms did the same. 24 2.4.4 Export activity in the manufacturing sector as a whole has boomed in the past two years, in part due to increased access to export markets in the EAC, COMESA, and AGOA. · In value terms, manufactured exports increased by 15.0% during the 2002/03 fiscal year, ver- sus an increase of 11.9% during the financial year 2001/02.8 2.4.5 Government export platforms such as Manufacturing Under Bond (MUB) and Export Processing Zones (EPZs), which once seemed ineffective, have performed impressively in recent years. · In the late 1990s, exports had stagnated in spite of the government's implementation of measures to attract foreign firms for export industry. Exports from EPZs accounted for just 3.5 per cent of total manufacturing exports and barely one per cent of manufacturing em- ployment in 1997. Just 22 companies operated under the programme in 1997, and 21 in 2001. · From 2001 to 2003, at least partly due to the incentives provided by the Africa Growth and Opportunity Act (AGOA), the number of companies operating under the EPZ program rose from 21 to 70, and direct employment in the EPZs in the year almost tripled from 13,444 to 35,935. Local investor participation in the EPZs has also grown significantly, with a tenth of the companies wholly owned by Kenyans, and three-quarters operating under venture ar- rangements with foreign investors. · Looking at the firm data, however, exporting in Kenya appears relatively stagnant. With the exception of the textile sector, exporting actually declined between 1999/2000 and 2002/03. This implies that much of the export growth has probably occurred in a small number of firms, while the average firm in Kenya has seen a decline in export activity. · Using the recent firm data, along with firm data collected by Oxford University in 1999/2000, one can analyze the decision to export in Kenya, including growth over time. Textiles firms appear more likely to import in 2002/03 than in 1999/2000, while in other sectors the propen- sity to export has decreased over the same period. · It seems reasonable to assume that this positive effect observed for the textile firms is related to AGOA and other policy measures designed to spur exports from firms in this sector. 2.4.6 While exports in individual firm often stagnated or declined, the destination of exports shifted from Africa to Europe and North America. The trend appears to be driven in large part by textile firms. · The likelihood that firms in our sample exported outside Africa increased between 1999/2000 and 2002/03. A firm with the "average" characteristics was seven percentage points more likely to export to non-African countries in 2002/03 than a firm with the same characteristics in 1999/2000. Further probing of the data suggests that a large part of this in- crease is played by more firms in the textiles and garments sector becoming export-oriented during the 1999/2000 to 2002/03 period. 2.4.7 Analysis of the survey data also indicates that exporting firms are more likely to be larger, older, Nairobi-based or foreign-owned (see Annex IV for details of the analysis). · Larger firms are more likely to export. In 2002/03 an increase of employment by one per cent is associated with an increase in the estimated likelihood of exporting by 0.17 percentage points--hence the probability of exporting for a firm with 10 employees is predicted to 24 per cent while for a firm with 100 employees it is 63 per cent. The size effect is clearly important. One commonly proposed explanation for the positive association between firm size and ex- porting is that firms face significant fixed costs to entering the exports market, due to bureau- cratic procedures, the establishment of new marketing channels, and economies of scale. 8CBK, 2003 Annual Report and June 2004 Monthly Economic Review 25 · The age of a firm matters too. In 2002/03, the results imply that the probability of exporting for a new firm (whose age is one year) is 43 per cent while that for a firm that has been in op- eration for ten years is 68 per cent. This provides evidence that breaking into exports markets takes time, perhaps because firms need to learn about marketing and distribution channels. · Firms located in Nairobi have a higher export propensity than firms located elsewhere. The likelihood of exporting is highest in Nairobi, followed by Nakuru, Mombasa, Eldoret and lastly Kisumu. Firms in Mombasa were 26 percentage points less likely to export, providing evidence that Mombasa has yet to take advantage of its coastal location. · In Kenya manufacturing exporting is reasonably well diversified across industries, at least compared to many other African countries. In 2002/03 the likelihood of exporting is highest among firms in the textiles, furniture and paper sectors, all other factors held constant. Quan- titatively the sector effects are quite large. For example, the difference in the probability of exporting between the textiles sector and the wood sector is 38 percentage points. · Foreign-owned firms are more likely to export. The estimated probability of exporting among firms with foreign ownership is 34 percentage points higher than among domestic firms. It seems possible that access to foreign markets and technology play a role in driving this result. 2.5 Appendix: Estimating overall firm productivity Firm productivity in East African perspective 2.5.1 Table 2.2 illustrates the contribution of labor, capital and intermediate inputs, as well as man- ager's education, to manufacturing output in three East African countries: Kenya, Tanzania and Uganda. A full description of the estimation method, the data, and the results is provided in An- nex III. · The table presents the results from estimating what is known as a log-linear production func- tion. Using ordinary least squares (OLS) regression techniques, the natural logarithm of manufacturing sales is decomposed into the individual impact of intermediate inputs used in production, total employment, and the use of capital. Done in this fashion, the results have an easy interpretation: the percentage change in manufacturing output that arises from a one unit increase in the input. All results are of course estimated with some degree of inaccuracy, and standard errors are provided. · The table also examines the impact of the manager having a university degree, as well as dif- ferences in total factor productivity between the three countries that cannot be explained by differences in factor use. In the case of indicator variables such as these, the interpretation of the result is less obvious: it is the change in the log of manufacturing output that comes from having this characteristic. It will be seen that there is an easier interpretation, however. · Note that China, India and other countries are excluded from this analysis due to concerns about pooling data from China and India with data from Africa. Differences in technologies, accounting practices and sectors of operation are make comparisons between Asian and Afri- can countries difficult. 26 2.5.1.1.1 Determinants of Firm Level Productivity, Regression Results Intermediate Inputs (natural log) 0.6 (0.03)*** Capital (natural log) 0.12 (0.02)*** Employment (natural log) 0.25 (0.05)*** Manager Degree 0.16 (0.12) Tanzania Indicator 2.58 (0.27)*** Uganda Indicator 2.69 (0.24)*** Kenya Indicator 2.7 (0.30)*** Number of firms in sample 438 Proportion of variation explained (adjusted R squared statistic): 0.99 Notes: Standard errors in parentheses. * significant at 20 per cent; ** significant at 10 per cent; *** significant at 5 per cent. Dependent variable: Logarithm of sales. Capital is the re- placement value multiplied by the rate of capacity of utilization. 2.5.2 Table 2.2 conveys several important characteristics of East African manufacturing: · As discussed, a one per cent increase in the capital stock is associated with a 0.12 per cent in- crease in manufacturing output, and a one per cent increase in employment is associated with a 0.25 per cent increase in output. · A one per cent increase in intermediate inputs (primarily raw materials and energy) is associ- ated with an increase in manufacturing output of 0.6 per cent. Such a high contribution is not unusual when the material cost of production is high (i.e., the cost of cotton cloth to a textile firm, or the cost of fruit to a canning company). · Kenyan firms have TFP remarkably similar to their East African counterparts, with perhaps a weak advantage. Based on the TFP analysis, an average firm, given the same factor inputs, produces 12.75 per cent more in Kenya than one in Tanzania. Likewise, given the same in- puts, output for the average firm in Uganda would be 1 per cent lower than in Kenya. Note that because the country differences are estimated with error one cannot reject the proposition that all three countries have similar levels of productivity. · The positive sign of the Manager Degree result indicates that enterprises with university- educated managers appear mildly more productive, although the large standard error implies that one cannot say with a high degree of confidence that firms with university-educated managers are consistently more productive. 2.5.3 While the above results are relatively unchanged when variations in sector productivity and sector mix are accounted for, the aggregation across sectors still hides sector variation within and be- tween countries. Table 2.3 looks at TFP differences across six sectors in the three countries. · The sector composition of the pooled East African sample is as follows: agro industry (33 per cent), chemicals and paints (6.7 per cent), construction materials (9.9 per cent), metals (12 per 27 cent), furniture and wood (16 per cent), paper, printing and publishing (7.1 per cent), plastics (3 per cent) and textile garments (12 per cent). 2.5.3.1.1 TFP is higher in some sectors in Tanzania than in Kenya and Uganda Tanzania Uganda Kenya Average TFP Agro industry 3.2 3.3 3.6 (0.48)*** (0.43)*** (0.53)*** Chemicals and Paints 5.3 4.7 4.7 (1.5)*** (1.4)*** (1.5)*** Construction Materials 3.6 3.7 3.6 (1.3)*** (1.0)*** (1.3)** Metals 2.1 2.7 2.5 (1.2)** (1.0)*** (1.2)*** Furniture Wood 2.1 2 2.4 (0.5)*** (0.5)*** (0.6)*** Paper, Printing and Publishing 2.6 3.6 3.1 (2.2) (2.2)* (2.6) Textile Garments and Leather 2.3 2.3 2.5 (0.52)*** (0.51)*** (0.53)*** Notes: Standard errors in parentheses. * significant at 20 per cent; ** significant at 10 per cent; *** significant at 5 per cent. Dependent variable: Logarithm of sales. Capital is the replacement value mul- tiplied by the rate of capacity of utilization. 2.5.4 Key findings from table 2.3 include the following: · In Kenya, the large agro-industry sector, as well as the smaller chemicals/paints and construc- tion materials sectors, are the most productive. With equivalent labor, capital and intermedi- ate inputs, agro-industry appears to be able to produce 11 per cent more output than both metals and textiles firms, for example. The some pattern holds in Uganda and Tanzania. · Chemicals and paints firms appear extremely productive--in Kenya they are three times more productive than agro-industry, and nine times more productive than textile firms. · With the exception of the Chemicals and Construction Materials industries, individual Ken- yan sectors seem to have a productivity edge on Tanzania. Given identical inputs, the esti- mated output for the average Kenyan Agro-industry or Metals firm is 50 per cent greater than in a Tanzanian one. The Kenyan edge is 22 per cent for Textiles firms, 35 per cent in furni- ture, and 65 per cent for Paper and Printing. Ugandan and Kenyan forms are more similar, and neither country has a decisive advantage. · It is important to note that while the point estimate differences can be quite large, the number of firms in each category is small enough that it is hard to make the above statements with a high degree of precision. The margins of error are quite wide and one cannot say with high levels of confidence that there is a wide TFP gap between Kenya and Tanzania, for instance. In short, while it appears that Kenya has a small productivity edge in several sectors, the con- clusion that should be drawn is that this edge is sufficiently small and estimated with suffi- cient error that it the most sensible conclusion is that Kenyan firms are remarkably similar to their East African counterparts, and possess at best a mild edge. 2.5.5 Another method of investigation is to break TFP down by firm type and look for insightful pat- terns. In order to understand which firms tend to perform better than others, Table 2.4 reports av- erage differences in TFP by size and other firm characteristics. The key insights are as follows: 28 · On average, very large firms (those with more than 250 employees) tend to have a much higher TFP than smaller firms do. Given the same inputs, the average very large firm can produce more than twice as much output than small and medium firms, and approximately 50 per cent more than large firms. · Firms that export also have much higher TFP than non-exporters. With the same inputs, ob- serve that the exporting firms typically produce twice as much output than non-exporters. · Firms with training programs have slightly higher TFP. With the same inputs, firms with training programs on average produce 35 per cent more output than those without. 2.5.5.1.1 Average TFP is higher in large firms, exporters, and firms with training programs Average TFP Firm Size Small 2.8 Medium 2.8 Large 3.2 Very Large 3.6 Education of the Manager University Degree 3.1 Non-University Degree 2.5 Export Capacity: Exporters 3.4 Non-Exporters 2.7 Training Effort Training 3.0 Non-Training 2.7 Firm productivity in Kenya over time 2.5.6 The above analysis pooled all the East African data to analyze productivity. Looking at Kenya alone, one can glean some additional country-specific insights. This is especially true because, unlike Tanzania and Uganda, similar firm data is available in Kenya from 1999/2000. A full de- scription of the analysis is available in Annex III. 2.5.7 Between 1999/2000 and 2002/03 almost no growth or improvement is visible in the average firm. Only capital efficiency has improved. · The use of pooled cross-sections of firms rather than a panel of the same firms over time mean that any change over the three years may simply be an artefact of sampling. · There has been virtually no change in labor productivity. Capital productivity appears to have improved by 24 per cent, an extremely large gain. It is difficult to imagine that this change is an artefact of the sample, but an explanation for the increase is not easy to provide. The re- tirement or breakdown of older capital and the failure to replace it with new capital is one likely explanation, since investment levels have been so low and since there has been virtu- ally no change, however, in labor productivity. · Investment rates are low in both periods, likely insufficient to replace worn-out capital. · Permanent employment is almost unchanged, falling by about 3 per cent (but not statistically distinguishable from zero). The median change is -0.4 per cent. Similar results are obtained when looking at the smaller sample of firms for which there are data on casual employment as well. 2.5.8 Other key insights from the 1999/2000- 2002/03 data are as follows: 29 · As in the East Africa-wide analysis, labor appears to be significantly more productive than capital, again perhaps because of the capital intensity of Kenyan firms. · There is no apparent correlation between firm age and productivity. · There is substantial geographic heterogeneity. Firms in Nairobi are substantially more pro- ductive than elsewhere in the country. In 2002/03, compared to the average firm in Nairobi, one in Mombasa was only 60 per cent as productive. The figure for Nakuru is 80 per cent, 29 per cent for one in Kisumu, and 25 per cent for one in Eldoret. With the exception of Nakuru, these differences are statistically significant. · The geographic pattern was broadly similar in 1999/2000, except it seems that Eldoret and Mombasa fell further behind between 1999/2000 and 2002/03. · By industry, the patterns are broadly similar to that seen in the previous section. In 1999/2000, the productivity of the Agro-industry sector was significantly higher than in any of the other three sectors covered (wood, metals and textiles). The least productive sector then was textiles and garments. By 2002/03 there was only one sector more productive than the food sector, namely the chemical sector. The difference, however, is not significant. The least productive sectors in 2002/03 are leather, wood and textiles. There are some signs that the textiles sector has recovered somewhat relative to the Agro Industry sector over the pe- riod considered. It seems reasonable to assume that this is at least partly due to better export opportunities. 30 3 Kenyan Competitiveness in the Factors of Production: Labor and Financial Capital 3.1 Overview Competitiveness of the Kenyan workforce 3.1.1 As part of the survey, a sample of up to 10 workers in each firm was interviewed, providing a sample of 1,922 employees in manufacturing. The data suggest that the Kenyan workforce is ex- perienced, middle-aged and possesses a high level of education. There is a wide dispersion in earnings, driven largely by differences in education, experience, and industry. The average wage in the sample is equivalent to $261 per month, with unskilled production earning about $99 dol- lars per month. 3.1.2 Though the general education level is high, the level and quality of production skills and technical training in Kenya is low. These training deficiencies can be traced, at least in part, to structural problems in the technical and vocational training system. 3.1.3 One alarming finding is that firms demonstrated an alarming indifference to and ignorance of the HIV/AIDS problem. While the infection rate in the workforce is estimated at 15% nationally, more than half of all firm owners and managers in the sample believed that none of their work- force was at risk. The other half, however, had programs to inform about or address the prob- lem--a better performance than in Tanzania or Uganda. 3.1.4 A second alarming finding is that the cost of labor in Kenya appears striking uncompetitive-- wages of unskilled production workers are higher in Kenya than all neighbours and strategic competitors. Higher Kenyan wages are justified if labor and firms are highly productive, but look- ing at estimates of the unit cost of labor higher Kenyan wages appear justified only when com- pared to Tanzania or Uganda. Compared to Asia, however, the cost of labor still appears high. As a consequence, wages consistent with the regional labor market can't be reconciled with the global product market. 3.1.5 A third alarming finding is that real wages appear to have been rising rapidly for a decade while firm productivity has remained stagnant. Several possible explanations for this wage-productivity disconnect are suggested, including the possibility that regulation is driving low-wage jobs into the informal sector, or non-market driven increases in public sector wages. Conclusive evidence on the matter will have to await the release of several ongoing labor market studies. Competitiveness of Kenyan finance 3.1.6 The findings from the firm survey support those of a joint World Bank-IMF financial sector study9: although the principal elements of a well-developed financial system are in place in Kenya, the sector is both vulnerable to risks, and has been unable to reach its full potential in supporting the allocation of scarce economic resources and promoting strong economic growth. 3.1.7 Three-quarters of firms in Kenya cited the cost of finance as a "major" or "severe" constraint to their business--the second most common complaint, and far more common than elsewhere in 9World Bank/DFID Financial Sector Assessment Program (FSAP) 2004. 31 East Africa. In spite of these numbers, this chapter will argue that finance is more of a constraint to small firms rather than firms in general. First, firms currently face much lower interest rate spreads than they did in 2002, when high interest rates did indeed restrict access to finance among a much larger cross-section of firms. Second, looking more closely at the ICA survey data, one sees that access to finance is principally a problem for small and medium domestic ones. Yet most firms do not feel credit constrained, and report that the reason they have not sought a loan is that they do not need one. 3.1.8 To say finance is not a severe constraint to business is not to say that investment capital is widely and cheaply available. For the Government to reach their targets of an investment rate of 23 per cent and GDP growth of 4.6 per cent, important financial sector reforms will be required. More- over, while most firms did not perceive themselves as credit-constrained, in a depressed economy (like that in 2002) demand for loans may be very low. 3.2 Education and wellbeing of the manufacturing workforce Education and experience 3.2.1 Overall, the Kenyan workforce in manufacturing appears to be well educated. · Looking at Figure 3.1, only 1.3 per cent of the interviewed workers have no education. Data indicate that about 19 per cent of the workers finished primary school and about 35 per cent, secondary school. About 10.7 per cent have some sort of university. The dominance of sec- ondary education in the workforce is similar to what was found in many African surveys. · Gender differences exist, but they are not as wide as in other countries. Interestingly, many more female workers had vocational/technical training (38.3 per cent) than their male coun- terparts, (about 23.2 per cent). 3.2.1.1 Highest Educational Achievement of Employees Other University Program 0.3% 0.0% Female University Post Graduate Degree 1.4% Male 1.6% University First Degree 7.4% 9.0% Vocational or Technical Training 38.3% 23.2% Secondary School 34.7% 35.7% Mid-School 4.4% 8.3% Primary 13.2% 20.8% None 0.3% 1.6% Source: World Bank, RPED Kenya, 2002/03 3.2.2 Figure 3.2 shows that the Kenyan workforce compares quite favourably in terms of education level with other African countries for which recent survey data are available. 32 · The education level of workers varies widely, however, according to the sector and the size of the firm. The largest proportion of workers with a university degree is found in sectors with significant technological requirements, including: chemicals and paints (17.2 per cent), agro- industry (13.9 per cent), and plastics (11 per cent). · Not surprisingly, the university-trained prefer to work for large and very large firms. 3.2.2.1 Highest Educational Achievement of Employees in Manufacturing 4% 13% 10% 12% 15% 20% 12% 26% 30% 25% 50% 26% 32% 43% 45% 43% 23% 20% 19% 12% 9% 6% 4% 1% 1% Eritrea 2002 Tanzania Uganda Nigeria 2001 Kenya 2003 2003 2002/03 None Primary Middle or secondary Technical/Vocational Some or full university Source: RPED/ICA Surveys. 3.2.3 In terms of experience, workers are on average middle-aged and tenure is quite long. · The mean tenure of the sample's workers was about 8.8 years. Firms in the construction and furniture sectors tend to keep their employees longer than companies in other sectors. The mean tenure is respectively 9.8 and 10.3 years. · Contrary to the results of other African firm surveys, younger workers tend to concentrate in large firms while older ones are found in small firms. Training and Skills 3.2.4 Nearly half of all firms offered some form of formal worker training. In pure value terms, skilled production workers received by far the most formal training. Production workers were the next most frequently trained, and professionals were the lowest number trained, with an average of four per firm in 2002. 3.2.5 In order to get a more accurate representation of workers trained, it is useful to calculate the num- ber of workers trained as a percentage of permanent workers. Looking at Figure 3.3, professionals were most likely to receive training and non-production workers were least likely to be trained. · The plastic industry trained the highest proportion of workers, except for the unskilled pro- duction workers. In this case, the chemical industry provided the highest proportion. In con- trast, firms in the textile industry tended to train a relatively low number of workers across most levels, with the exception of unskilled production workers, where the proportion of trained workers was above Kenya's average. 33 · Foreign owned firms tended to train the highest proportion of managers, professionals, skilled production workers and non-production workers. Finally, small firms generally trained the highest proportion of unskilled production workers, the average proportion of 36.7 per cent was almost ten points higher than the Kenya average. 3.2.5.1 Staff trained as a percentage of all permanent workers, by job category Training levels, all firms Training levels by industry 59% 61%60% Non- 54% 54% 27% production 48% 50% 46% 42% 41% 42%43%44% 37% Unskilled 28% 32% 31% 30% 25% 19% Skilled 35% 17% 10% 7% 4% 3% 0% Professional 49% Agro Metal Chemical Plastic Textile Manager 39% Manager Professional Skilled Unskilled Non-production Training levelsby firm characteristics 76% 54% 56% 57% 49% 45% 48% 40% 43% 33%37% 37% 36%38% 36% 29% 32% 31% 32% 32%34% 27% 28%28% 23% 22% 25% 17% 20% 14% Small Large NonExporter Exporter Domestic Foreign Manager Pr ofessional Skilled Unskilled Non-production Source: Investment Climate survey 3.2.6 Though literacy levels of Kenya's workforce are relatively high compared to its Sub-Saharan Af- rican neighbours, recent reports by the World Bank suggest that the level and quality of skills de- velopment and technical training in the economy is less than adequate. · The 2003 Country Economic Memorandum (CEM) for Kenya notes that the main concern in the further development of the textile industry will be skill development. · A 2004 report on Growth and Competitiveness in Kenya argues that current training curricula are obsolete, and that major deficiencies are observed in public training facilities and instruc- tional capacities. These problems lead to a mismatch between the supply and quality of skills in the market and the actual demands of the growth sectors of the economy. · Moreover, the report argues that the existing system focuses on formal enterprises, and does not provide adequate support for the apprenticeship system as well as the skills needs of the MSME and informal sectors. 3.2.7 The reports trace these training deficiencies to structural problems in the Technical and Voca- tional Education and Training (TVET) system in Kenya. In particular, the reports suggest that the TVET system is inadequate to firms' needs, is financially troubled, and requires a broader-based approach and shared vision. 34 · The core of the current TVET system is the Industrial Training Levy (ITL). Under the ITL, firms pay into a common fund and are reimbursed a proportion of the costs of approved train- ing undertaken in specified facilities by employers. · The ITL appears to be largely ineffective and in a state of financial crisis. Public funding is inadequate. These problems are compounded by role confusion amongst various ministries and lack of a clear institutional framework to govern the management of the system. · Moreover, the specialized skills required by many factories to compete in export markets are not covered under the ITL. The ITL only covers offsite training in a narrow range of activi- ties, few of which have to do with production skills and productivity improvement. This may account for the heavy investment in professional training versus production skills in the ICA survey data. · The levels of reimbursement are also much lower than the actual cost, so the program pro- vides little incentive to employers to release their staff for training. The government does not offer finance or incentives to private enterprises to invest in in-house training, and private firms invest relatively little in this form of training. · The textile sector provides a good example. The CEM notes that, since the time of the ICA survey, firms are putting more funds into production training, in particular sewing machine operation. The established rules and procedures for the ITL, however, make it difficult to be reimbursed from the fund for expenses related to onsite training. Export-oriented private firms, such as the EPZ garment exporters, have lost confidence in the scheme and conduct their own enterprise-based training (at additional cost to themselves). Health and wellbeing 3.2.8 Firm awareness and response to HIV/AIDS is not encouraging, as seen in Figure 3.4. · About 22 per cent of the interviewed firms were unable to provide any estimate of prevalence for their workforce or considered the question as irrelevant. For the remaining firms able to provide an estimate, 45 per cent of them declared a zero prevalence rate, a disturbing figure considering the official figures of prevalence which are largely publicized. · Such a result can be explained either by the ignorance or by a reluctance to disclose such in- formation. Nonetheless, the same firms believed that a significant proportion of their work- force died from HIV/AIDS-related causes in the last 5 years, on average 22.6 per cent. 3.2.9 On the other hand, some firms are taking action. 45 per cent report having undertaken actions aimed at raising awareness about the disease and how to prevent it. · It is interesting to compare this number to the result obtained in Uganda, one of the few coun- tries to have successfully reduced the growth of the disease. In Uganda, 37.2 per cent of the firms report having undertaken actions against HIV/AIDS. Hence, in this respect, Kenyan firms are doing better. In Kenya, as in Uganda, the proportion of firms taking a proactive stance rises with the size of the firm, 16.7 per cent of the very small firms undertake such ac- tions, while 78.1 per cent of the very large firms do the same. · These results suggest that firms are to some extent aware of AIDS but do not seem yet to consider it with the seriousness required. However, taking some action does not imply that the depth of the disease and its potential impact is properly assessed by firms. 3.2.10 Among employees, however, the perception of the HIV/AIDS issue is much more acute. · 83.6 per cent of employees report HIV/AIDS to be a "big" or "very big" concern to them. · 73 per cent of workers would be ready to pay to get tested at the firm, provided these tests were anonymous and voluntary. This proportion is almost the same as in Uganda where 72 35 per cent of the employees would be ready to be tested at the firm. Overall, employees would be ready to pay about 613 Ksh (about US$8) to be tested. 3.2.10.1 HIV-AIDS, perception of the managers/owners Firms' own estimates of HIV Percentage of Firms undertaking prevalence in their workforce activities to prevent HIV/AIDS More than 20 % of Very Large (>100 w orkers) 78% w orkforce 3.6% 11 to 20 % of w orkforce 4.3% Large (50-99 w orkers) 61% 6 to 10 % of w orkforce 12.1% Medium (10-49 w orkers) 37% 1 to 5 % of w orkforce 35.0% Small (<10 w orkers) 24% None of w orkforce 45.0% All firms 45% Source: World Bank, RPED Kenya, 2002/03 3.2.11 Although firm awareness and action in Kenya seems disappointingly low, in fact firms appear to be doing much better than in Kenya's neighbours. Figure 3.5 illustrates that 44 per cent of Ken- yan firms offer at least one HIV/AIDS program, compared to 31 per cent in Tanzania and 32 per cent in Uganda. Kenya firms are much more likely to provide prevention messages, counselling, and free condoms. Financial support and anonymous testing services are low all around. 3.2.11.1 Firms with HIV/AIDS prevention programs by type, 2003 44% Any programs 31% 32% HIV prevention 38% messages 27% 24% 29% Counseling for HIV/ADIS 16% 14% 23% Free condom distribution 13% 9% Financial support for 4% 3% dependents 2% 3% Kenya Anonymous HIV testing 4% 2% Tanzania 7% Uganda Other 3% 4% Note: Sources are Investment Climate Surveys. Enterprises with programs can have multiple programs 36 3.2.12 The health status of workers interviewed seemed only moderately disruptive to their work, and was comparable to African standards. About 20 per cent of the workers report having had an ill- ness of varying severity within the last 30 days before their interview, translating into an average loss of about 2.1 workdays over a 30-day period (or a loss of about 10.5 per cent of workdays). It seems likely, however, that the very sick or terminally ill (including AIDS victims) would not be working, and in any case would be highly unlikely to have been interviewed. Thus the illness finding really only apply to the non-terminally ill fraction of the workforce. 3.2.13 When ill, a majority of workers (almost 50 per cent) would obtain treatment from private health care providers and would thus bear a significant cost. Firms' health care facilities and public fa- cilities do not appear to be a first choice. Only 17.6 and 16.5 per cent of the employees, respec- tively, seek treatment in such places. This is probably a reflection of the reduced availability of such facilities and possibly of an uncertainty regarding the quality of treatment. 3.3 Wages and the competitiveness of labor Earnings in the manufacturing sample 3.3.1 Using unskilled production wages of permanent workers as a benchmark, it can be seen that Ken- yan wages are much higher than in neighbours and strategic competitors, as seen in Figure 3.6. Average earnings of unskilled production workers in Kenya are about US$99.20 per month. This puts Kenya at the top end of the cost of labor. Of course, this figure does not take into account differentials in labor productivity across countries (which are examined below). 3.3.1.1 Estimate of Monthly Earnings of Unskilled Production Workers (US$) $99.20 $84.23 $85.00 $73.10 $57.48 $45.01 $48.40 $50.00 $51.70 Eritrea Zambia India Tanzania Uganda Thailand Nigeria China Kenya 2002 1996 1999 2003 2003 1995 2001 2000 2003 Note: Based on sample average monthly earnings from country RPED/ICA surveys. 3.3.2 Looking at all worker categories, it can be seen that there is substantial dispersion in earnings. Total average monthly cash earnings were US$261 in early 2003. Figure 3.7 shows the break- down of average monthly cash earnings by job function, expressed in current dollar terms. The table suggests gender discrepancies in the labor market. For sample firms, male worker earnings are about 30 per cent higher than female employees, although regression results (which control for other individual and firm characteristics) suggest that the difference is much smaller, on the order of 5 per cent. 37 3.3.2.1 Monthly Cash Earnings (in US $ by position) in early 2003. All 210 273 Female Non Production Worker 188 Male 180 Unskilled Production 104 Worker 98 Skilled Production 150 Worker 196 Professional 417 675 Management 659 789 0 200 400 600 800 1000 S $U Note: Computed on the basis of the wages provided by workers in February/March 2003 and converted into US $ using the Feb- ruary/March 2003 official exchange rate of 1Ks=0.0133 US Dollar. 3.3.3 Regression analysis of the earnings differentials (discussed in Annex V) reveal the following pat- terns and determinants, controlling for all relevant factors: · Each extra year of education is associated with roughly a 14 per cent gain in monthly wages. · General work experience matters rather than experience specific to the firm. A worker with an extra 10 years of experience earns about 2.5 per cent more on average. · Males earn about 5 per cent more than females, holding education and experience constant. This is a small gap relative to other countries, and in fact statistically one cannot reject the hypothesis that there is zero difference between the sexes. · Earnings were at least a third lower in Eldoret and Nakuru than in Nairobi. There seems to be no significant gap in earnings between Nairobi and Mombasa. · Earnings are highest in the chemical and lowest in the textiles sector. 2002/03 earnings were on average about 39 per cent higher in the chemical sector than in the food sector, and 81 per cent higher than in the textiles sector. · Wages are greater in large firms. The wage of a worker in a firm with 200 employees is about 30 per cent higher, on average, than that of worker employed by a firm with 10 employees. Wage trends in Kenya 3.3.4 High wages in Kenya are a relatively recent phenomenon. After falling by roughly half through the late 1980s and early 1990s, real wages in the private and public sector recovered their losses by 1999, and continued to rise rapidly through the recession years to 2003. · Figure 3.8 displays an index of average real wages in the public sector, the private sector, and also the two largest private subsectors--private manufacturing and private social and per- sonal services. Real manufacturing wages hit a nadir in 1994 and climbed steadily thereafter. · From 1987 to 1994, a period of intense structural adjustment in the Kenyan economy, real wages in both the private and public sectors halved. Furthermore, the real wage premium of- fered by the public sector--nearly 20 per cent in 1986--disappeared by 1994. 38 · Between 1994 and 2003 real wages in the private sector increased by 250 per cent, and those in the public sector rose by 228 per cent. By 2003 private real wages were 56 per cent greater than their 1986 level, while public real wages were 21 per cent greater than in 1986. 3.3.5 These wage trends appear in the manufacturing survey data as well. Between 1999/2000 and 2002/03 real wages rose 9% in our sample of firms, even after controlling for increases in the age and experience of workers. In one study of firm survey data from 1978 to 2000, manufacturing wages declined through the 1980s and early 1990s, but began to rise by 1995. · Moreover, in the same study of long term wage trends, some groups gained while others lost. University educated workers gained significantly more than the secondary- and primary- educated workers after 1994, and in fact workers with only primary schooling observed a de- cline in their real earnings. 3.3.5.1 Index of average real wages, 1986-2003 180 160 100) 140 All private sector 994=1(x 120 Private manufacturing only ndei 100 geaw Private Community, Social & 80 Personal Services ealR All public Sector 60 40 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Note: Data are average wage payments (total sector wage payments divided by the number of sector employees) from the CBS Economic Survey, various years. Nominal wages have been deflated using the Nairobi CPI. All data have been indexed relative to average real wages in the manufacturing sector in 1994. 3.3.6 It is worthwhile noting that, even though manufacturing wages have risen substantially in the last decade, they have been eclipsed by wage growth in the public and other private sector industries. · Manufacturing wages declined more quickly than the private and public sector averages be- fore 1994, and rose more slowly from 1994 to 2003. By 2003 the wage premium in manufac- turing had reversed. · Despite doubling between 1994 and 2003, by 2003 manufacturing wages were only 10 per cent greater than the recorded level in 1986, a less substantial gain than in other sectors. · Wage gains in other large sectors, such as social and personal services, exceeded those of manufacturing between 1994 and 2003, and by 2003 offered a substantial wage premium. Measuring the competitiveness of wages 3.3.7 Kenya's high wage level does not appear to be matched by sufficient labor productivity to com- pete with firms in Asia, although the labor seems competitive in comparison to the rest of East Africa. More alarmingly, the wage increases in the last decade do not appear to have been driven by productivity improvements, suggesting that Kenya's formal manufacturing sector is becoming less competitive. 39 3.3.8 To measure the competitiveness of labor one has only imperfect measures such as the ratio of wages to value-added. In a world with a handful of easily measurable and comparable outputs, it would be possible to calculate a cost of labor per unit of output--the unit cost of labor (ULC). By converting this figure into a common currency, it would be possible to make international com- parisons of the cost and productivity of labor. In a world with multiple products and hard-to- measure output, however, one can only approximate this unit labor cost. One proxy is the ratio of wages to MVA. 3.3.9 Data from the firm surveys in Figure 3.9 indicate that Kenya's ratio of wages10 to Manufacturing Value Added (MVA) is comparable to Uganda and Tanzania, with wage bills of nearly 40 per cent of value added, but moderately higher than that of China (32 per cent of MVA) and well above that that of India (27 per cent of MVA). 3.3.9.1 Ratio of total wages to MVA in the median firm, by firm size .56 .45 .41 .42 .38 .39 .41 .41 .39 .34 .36 .38 .33 .35 .34 .29.30 .32 .25 .25 .27 .29 .24 Kenya Tanzania Uganda India China Small (<10 emp) Medium (10-49 emp) Large (50-99 emp) Very Large (>100 emp) Overall Note: The wage bill is calculated as the ration of wages to MVA. Figures displayed are the median values by firm size 3.3.10 East Africa in general has higher estimated ULC relative to Asia at roughly equivalent stages of development. When present data from Africa are compared with Asian data from the 1960s and 1970s (Figure 3.10) it is clear that earnings in Africa are about two-thirds higher than was the case historically in Asia, and African productivity is about one-fourth lower. 3.3.10.1 Estimates of total wages to MVA in a series of developing economies 0.39 0.39 0.35 0.36 0.32 0.24 0.26 0.27 0.27 0.21 0.16 Taiw an Indonesia Thailand South Malaysia India 1999 China 2000 Singapore Kenya Tanzania Uganda 1961 1981 1970 Korea 1963 1970 1963 2002/03 2003 2003 Source: Lindauer and Velenchik (1994); and RPED Surveys (1990s). 3.3.11 Even though the ratio of wages to MVA is not a true unit cost of labor, the results are still sugges- tive that East African labor is very costly relative to its level of productivity. 10Wages include permanent, casual and part-time workers. 40 · Given that Kenyan firms are much more capital-intensive than in Asia, one would expect a higher MVA per worker and, all other things equal, a lower ratio of wages to MVA. That the ratio in Kenya (and indeed all of capital-intensive East Africa) is well-above that in China in India suggests low marginal productivity of labor. · African firms also tend to employ more casual and part-time workers than firms in Asia, and to the extent that the estimate of total wages misses some wage payments to non-full-time workers, the ratio of wages to MVA in Africa will be understated.11 The Kenyan estimates may also be understated because the survey did not cover micro enterprises, which typically have lower labor productivity than larger firms (and would lower average MVA). Thus one might consider the above results a lower bound estimate. A productivity-wage disconnect 3.3.12 The evidence above suggests a disconnect between wages and labor productivity in manufactur- ing--the former have been rising steadily for a decade while the latter appears stagnant. 3.3.12.1 Earnings levels and growth by sector 2003 monthly real wage earnings (Ksh) Avg annual growth of real wage 1994-2003 Financial & 54,103 Financial & 10.9% Business Business 8.2% Services 42,096 Services Wholesale, 28,951 Wholesale, 11.2% Retail, Food & Retail, Food & Hotel 32,852 Hotel 9.9% Social & 19,758 Social & 9.6% Personal Personal 12.7% Services 24,717 Services 15,139 8.0% M anufacturing M anufacturing 19,671 7.5% 18,591 11.5% Construction Construction 19,303 9.4% Private Public Private Public Note: Data are nominal average wage payments (total sector wage payments divided by the number of sector employees) from the CBS Economic Survey, various years. Wages are deflated using a Nairobi CPI. 3.3.13 A natural explanation for the disconnect is rising productivity (and wages) in sectors with which manufacturing must compete for labor.12 The productivity-wage disconnect appears to be econ- omy-wide, however. · There has been impressive earnings growth in other private and public industries. Wages in the largest industries were generally greater than those in manufacturing and all grew at a faster rate between 1994 and 2003 (see Figure 3.11). · Meanwhile, it is not clear that productivity in these other sectors has improved. Real GDP per worker declined by an average rate of -0.8 per cent between 1992 and 2001. The years 1997 11This understatement could be offset or amplified, of course, by other sources of bias. For instance, under-reporting of sales would decrease our measure of MVA and lead to an overstatement of the ratio of wages to MVA. 12Even if there have been no productivity gains in the manufacturing industry, productivity and wage increases in other sectors could raise manufacturing wages through competition for skilled and unskilled workers. Manufacturing firms would be forced to raise their wages to keep their workforce if other sectors began to offer more attractive earnings. 41 to 2002 were some of the worst growth years on record and yet wage growth persisted throughout. Individual industry performance was relatively similar. · If true, economy-wide increases in wages and stagnation in productivity imply that productiv- ity-induced wage competition from other industries cannot explain the growth observed in manufacturing wages. 3.3.14 A second natural explanation for the wage increase is that union-driven or government-mandated increases in the minimum wage have driven the cost of labor too high. Yet, as pointed out by a recent IMF report, this story does not seem to fit the facts either. · Little growth in the government-mandated average real minimum wages can be seen 1993- 2003, either urban or agricultural, suggesting that the government's minimum wage policy has not sparked the rise in real wages (see Figure 3.12). · The near-doubling of minimum wages in collective wage agreements (CWAs) seen in Figure 3.12, however, have led some observers to conclude that the collective bargaining process is behind the rise in industrial wages. Labor unions have become more active and powerful since the end of major structural adjustment, during which time unions were somewhat con- strained by government and wages fell steeply. 3.3.14.1 Minimum wage trends, 1993-2003 Trends in real minimum wages Ratio of minimum wage to average wage 250 1.40 200 1.20 h 1.00 montr 150 pe hsKs000 0.80 100 0.60 50 0.40 - 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Ratio of urban minimum wage to average private sector wage Avg urban minimum w age Avg agricultural minimum w age Ratio of CWA wages to average private sector wage All CWAs All manufacturing CWAs Ratio of manufacturing CWA wages to average manufacturing wage Note: Source is the Economic Survey from the CBS, various years. All minimum wages exclude housing allowances. · The collective bargaining explanation is unsatisfactory for at least two reasons, however. One, as a recent IMF report points out, while CWA minimum wages have been rising, they have failed to keep up with the sector averages. Figure 3.12 also charts the ratio of minimum wages to average wages in the private sector, which by any measure have roughly halved in the past decade.Two, it is not clear that the coverage of collective wage agreements is suffi- ciently broad to explain economy-wide wage growth. With roughly 1.7 million workers in the formal sector, only 50,000 to 75,000 workers are typically covered in the CWAs registered each year. 3.3.15 The same IMF report points out another possible reason for growing formal sector wages: to the extent that government and union regulation (including minimum wages and other labor regula- tion) encourage the growth of informal firms, the low-skilled and low-wage earners will be crowded out of the formal sector into the informal ones. That is, as minimum wages and other forms of regulation increase, informal firms (perhaps offering lower pay) will grow faster than 42 formal firms. Thus, as the bottom wage bracket disappears from the formal statistics, the average wage in formal industry will rise. · The IMF notes the steep growth in informal employment in the last two decades and draws a correlation between increases in the minimum wage and increases in informal sector em- ployment. Naturally, correlation does not imply causation. · The IMF's hypothesis is weakly supported by the ICA survey results. Analysis of the formal firm data reveals substantial wage increases, but when firm size is added to the regression analysis the unexplained growth in wages disappears. Larger firms tend to pay their employ- ees more, and the 2002/03 sample contained more large firms than the 1999/2000 one. There are at least two stories consistent with this result: one is the IMF's hypothesis that smaller firms are more likely to appear in or move to the informal sector; the second story is that the increase in large firms is due to sampling error. 3.3.16 The rise in wages continues to presents a puzzle, and a full analysis and explanation of recent wage trends await the completion of two ongoing studies. Several other stories appear plausible, however, but will require further investigation to confirm. These possible explanations include the following: · Increasing public sector wages. As seen in Figure 3.12 above, in most industries public sec- tor earnings grew faster than those in the private sector. Public sector wages rose 9.2 per cent per year in real terms between 1994 and 2003, similar to the increase in private sector wages of 9.7%. If increases in public sector wages arose from non-market considerations, then they may have driven growth in private-sector wages (to the extent that those firms had to raise wages to compete for workers). · Wage pressure from donors, tourists, and foreign firms. Private wage growth has been high in the growing financial services, social and personal services, and trade and tourism sectors. To the extent that these industries serve foreigners with higher pay scales or deeper pockets--foreign banks, donors, and tourists--wage pressure elsewhere in the economy may increase. · Labor market rigidities. If firm output is falling due to demand contractions, but the work- force is not reduced, then productivity will fall. A study by Mandu and Sen employs the Ken- yan firm data from the mid-1990s notes a fall in labor productivity in the textiles and gar- ments, electrical machinery and transport equipment sectors. In these industries, output fell sharply due to falling domestic demand, but employment did not decline in the same propor- tion. If we want to discuss this story, however, we might want to analyze the full sample of firm data. · Measurement problems. Measurement of both productivity and real wage growth is prob- lematic and the stagnation in productivity or the rise in real wages observed may be biased. 3.4 The availability and cost of finance in the Kenyan manufactur- ing sector 3.4.1 When financial markets are underdeveloped, established businesses and new entrepreneurs must forego profitable investment opportunities due to a lack of affordable, accessible capital. For this reason financial sector development is an important determinant of growth, and countries with well-developed financial systems (banks, stock markets and bond markets) tend to grow faster than countries with less well-developed systems. 3.4.2 Partly as a consequence of the high cost of capital and other financial sector problems, investment in Kenya has been falling for more than three decades. In Chapter 2 Kenyan capital was seen to 43 be outdated, only a minority of firms invested in new capital equipment, and most of this invest- ment would only be sufficient to replace worn-out capital. 3.4.3 To illustrate the limitations and risks to which the current financial system is subject, this section explores three forces driving the cost and availability of finance: the supply of credit, demand for credit, and transactions costs. 3.4.4 On the supply side are such macroeconomic factors as overall financial depth, economic stability, fiscal discipline, the capacity to manage shocks, and the efficacy of the legal system. This chapter demonstrates that while improvements have been made, deeper structural challenges remain. · Relative to other low-income countries, Kenya has a very well developed financial sector and relatively high levels of credit channelled to the private sector. Moreover, in the last two years, stability has return to the macroeconomy, lending rates have dropped, and banks have returned to profitability. · Yet interest spreads are still high relative to rich countries and emerging economies, and bank productivity is extremely low. These problems have been traced largely to non-performing loans, an inadequate legal and institutional structure, high levels of bank employment, barri- ers to sector consolidation, and politically-motivated interventions. 3.4.5 On the demand side are the quality of firms' investment opportunities and the quality and profes- sionalism of firm management (in understanding when and how to obtain credit). · With economic growth returning, decreases in petty corruption, and growing export opportu- nities (through the EAC, COMESA, and AGOA) investment opportunities have improved. · Anecdotally, financial sector development specialists have expressed less confidence in the ability of many firm managers, especially those in smaller firms, to prepare and execute ac- ceptable business plans, and such skill-building and business development services are hence a key focus of many domestic and donor projects. 3.4.6 Transactions costs are the costs of evaluating, monitoring and collecting on credit contracts. They are affected by the quality and availability of information on firms (credit ratings, disclosure re- quirements, incentives and penalties for misrepresentation) and by the effectiveness of the legal and institutional framework for credit collection and repossession. When collection is difficult or uncertain, high levels of collateral are required. Transactions costs appear to be the principal problem for small and medium firms. · Chapter 4 outlines deficiencies in the legal system that hinder the enforcement of contracts, especially debt, and hence raises the cost of capital. It also results in relatively high collateral requirements, which small firms find slightly more difficult to meet. · Furthermore, a lack of public credit institutions such as a rating agency make the evaluation of firm credibility very costly for banks and dissuade them from lending. This will also hurt small firms more than large ones, and can account for some of the gap in availability, as well as the interest premium paid by small firms versus large ones. Trends and challenges in the Kenyan financial sector 3.4.7 At the time of the ICA survey in 2002/03, almost three-quarters of firms in Kenya cited the cost of finance as a "major" or "severe" constraint to their business--the second most common com- plaint. Far fewer firms complained of the cost of finance in Uganda, Tanzania and Asia (see Fig- ure 3.13). Nearly half of Kenyan firms, meanwhile, reported that access to finance was a signifi- cant constraint, a high number, but comparatively fewer than in Tanzania and Uganda. 44 3.4.7.1 Share of firms rating finance as a "major" or "severe" constraint, by country Share rating cost of finance a major Share rating access to finance a major constraint constraint 73% 58% 60% 48% 44% 45% 43% 38% 23% 22% Kenya Tanzania Uganda Pakistan China Kenya Tanzania Uganda Pakistan China Source: Investment Climate surveys 3.4.8 This section argues that the cost of finance was indeed a serious barrier to firms in 2002/03, but that declining interest rates since that time have probably lessened the cost of finance as a con- straint. For small firms, however, access to finance is probably still too limited. 3.4.9 In assessing finance as a barrier to investment and growth in the Kenyan manufacturing sector, this section and the following one combine findings from the Investment Climate survey and a 2004 study by the World Bank and the IMF, the Financial Sector Assessment Program, or FSAP. 3.4.10 The Kenyan banking sector is well developed and comprises 43 commercial banks. The sector is moderately concentrated, with the top three banks controlling nearly 40 per cent of all assets. This concentration ratio is lower than the OECD average (48 per cent) and much lower than the SSA average of 77 per cent. 3.4.11 The most notable recent trend is the falling cost of capital. Interest rate spreads, once extremely high, have fallen rapidly in recent years. The health of the banking sector has also improved. · A plunging economy and poor governance drove interest rates as high as 90 per cent in the mid-1990s. By 2002/03, real lending rates had fallen to roughly 16 per cent, and today real lending rates have come down to between 5 and 20 per cent for most firms.13 · Meanwhile, bank profits are up, banks are aggressively searching for new business, and they must also now pay heed to tighter central bank regulation. 3.4.12 Another key trend is increasing privatization of state financial institutions. While the GoK cur- rently plays a prominent part in the financial sector through its part ownership of several large fi- nancial institutions, there seems to be widespread support for reform and divestiture of the banks and development finance institutions (DFIs). · As seen in Annex VI, state-owned financial institutions are generally less productive and have more non-performing loans. The Consolidated Bank and the Industrial Development Bank are among the worst-rated financial institutions in the country. · The government had a 35 per cent stake in KCB, the third largest bank by assets, and a 25 per cent stake in National Bank, the sixth largest bank. Already it has reduced its shareholding in KCB from 35 per cent to 25 per cent. There is also a plan to recapitalize and restructure Na- tional Bank and prepare it for eventual privatization. Finally, the GoK also plans to privatize Consolidated Bank and Industrial Development Bank. 13CBK (2004). 45 3.4.13 The Nairobi Stock Exchange (NSE) recently improved it performance, and is one of the most de- veloped markets in the region. From 1994 to 2002 its performance was disappointing and market capitalization fell sharply as a percentage of GDP. In 2003, however, the NSE 20-share index more than doubled while market capitalization tripled. Although it is one of the best developed stock exchanges on the continent, the market is also relatively illiquid and relatively concentrated. Transaction costs are also relatively high 3.4.14 As a result of its relatively high level of financial sector development, in 2001 Kenya had higher levels of credit channelled to the private sector and higher deposits in financial institutions than other SSA and poor countries. Annex VI discusses the state of the banking sector at the time of the ICA survey in detail. Key issues and challenges facing the financial sector 3.4.15 At the time of surveying, by regional standards Kenya's financial system was reasonably well developed but highly unproductive, with high interest spreads. There have been improvements in lending rates and bank profitability since this time, but bank efficiency is still much lower, and spreads much higher, than what will be required to motivate high rates of investment. · At the time of the ICA, Kenya's interest rate spread--the difference between lending and de- posit rates--was comparable to the rest SSA but much greater than in developed countries. · Kenya's high spreads in 2002 appear to have been driven by a host of factors, including: (i) high bank operating costs, especially staff costs; (ii) a high level of non-performing loans; (iii) a large number of small, inefficient banks hindered from consolidation by the regulatory framework; (iv) high statutory reserve requirements; (v) high bank liquidity due to poor tele- communications and transport infrastructure; and (vi) a deficient legal and institutional struc- ture that hampers the enforcement of debt contracts. 3.4.16 As noted in the 2004 FSAP, key weaknesses in the financial sector infrastructure identified relate to the legal and institutional framework for finance, including property rights, insolvency, and creditor rights. · A lack of accurate and reliable information about the borrowers' ability to pay reduces com- petition, increases credit risk, and lending rates, and makes it difficult to reduce the depend- ence of banks' lending decisions on collateral. · Inefficiencies and corruption in the system of land registration, as well as delays in the court system, undermine property and creditor rights. In such cases, lenders reluctant to lend, re- quire high levels of collateral, or increase risk premiums. 3.4.17 The fragility of institutions is compounded by weaknesses in financial supervision. Major regula- tors have suffered from a lack of independence from government influence and have often been handicapped in enforcing prudential regulations. Overall, the FSAP team found that direct gov- ernment participation in the financial system was a source of distortions and an indirect source of vulnerabilities. It therefore recommended that the Government's role in financial development be focused on providing a robust legal and judicial framework, and strong supervision and regulation of financial institutions and markets, thereby promoting soundness and competition among all providers of financial services. 3.4.18 Non-performing loans amounted to at least 28 per cent of the total loan portfolio in July 2003, and continue to present a problem, especially in the state-influenced banks. The FSAP found that the Kenyan DFIs not only operated with very high overhead, but also accumulated large non- performing assets equivalent to as much as 95 per cent of their loan portfolios. 46 3.4.19 In spite of the low bank concentration ratio, competition in the banking sector is still quite weak. Anecdotal evidence from the report suggests that most customers in Kenya below the top tier of corporate and wealthy borrowers face a non-competitive banking market and are often effectively tied to one bank, with very high switching costs. Competition is also hampered by deficiencies in the legal infrastructure and by the presence of many weak banks that are unable to put competi- tive pressure on the few strong ones. 3.4.20 A recent World Bank project document also suggests that there are important structural problems in bank and non-bank oversight: banking supervision is under-funded and has not been decisive; the payments system is inefficient; insurance sector supervision could be more effective; en- forcement of capital market rules and supervision of market participants are still weak; and, fi- nally, the pension system has very limited coverage and does not provide adequate benefits. 3.4.21 Finally, financial sector specialists emphasize that there is a "financing gap" between the com- mercial banks and the microfinance institutions. Small and medium-sized firms are typically too large for a microfinance loan but are challenged in obtaining loans from commercial banks. There is a sense that monitoring, evaluation and other transaction costs are too high to make medium- sized loans worthwhile. 3.4.22 In view of the above constraints, the GoK has proposed a short-term financial sector reform pro- gram and is planning to develop a long-term sector development strategy, and has asked the World Bank for a Technical Assistance Credit to assist in the implementation of these programs. Government and donor activities are outlined in Chapter 5. 3.5 The cost of and access to finance in manufacturing firms 3.5.1 While the cost and availability of finance were identified as important constraints by Kenyan firms, Figure 3.14 shows that dissatisfaction with both appears to be more acute in smaller firms. Small firms were almost twice as likely to complain of access to finance as large ones. Non- exporters were also more likely to complain of a lack of access to finance. This subsection argues that while the cost of finance has improved dramatically for all firms, as so is not likely to be a severe barrier, access to finance by small firms still appears to be limited by a lack of appropriate instruments and high transactions costs. 3.5.1.1 Share of firms rating finance as a "major" or "severe" constraint, by firm characteristic Share rating cost of finance a major Share rating access to finance a Share rating cost or access to constraint major constraint finance a major constraint, in Kenya 80% 56% 53% 67% 46% 76% 73% 41% 58% 60% 56% 59% 33% 34% 52% 39% Kenya Tanzania Uganda Kenya Tanzania Uganda Cost Access Small Large Small Large Non-Exporter Exporter Source: Investment Climate surveys 47 Sources and use of finance 3.5.2 Looking across countries in Figure 3.15, the most significant source of capital for many busi- nesses around the world is retained earnings. Bank loans are typically second, and equity financ- ing seems somewhat uncommon. By these global standards, and certainly by East African ones, firms in Kenya--which fund roughly half of their working capital and new investment out of re- tained earnings--appear to be relatively healthy consumers of bank and trade credit. Of course, 1999 to 2002 were recession years in the Kenyan economy, and thus many companies may have had few profits to reinvest. 3.5.2.1 Sources of finance used across countries Source of financing for working capital Source of financing for new investment 100% 100% 90% 90% 80% 80% Other Other 70% 70% Informal sources Informal sources 60% 60% Equity Equity 50% 50% Trade credit Trade credit 40% 40% Banks Banks 30% 30% Retained earnings Retained earnings 20% 20% 10% 10% 0% 0% Kenya Tanzania Uganda China India Kenya Tanzania Uganda Source: Investment Climate surveys. New investment finance sources not available for China and India. 3.5.3 Looking within Kenya in Figure 3.16, heavy reliance on retained earnings is common to all firms. Interestingly, large firms look similar to small ones, but foreign firms and exporters have rely more on retained earnings. This may be an indicator of their relative profitability. · Obviously firms tend to rely on bank loans for investment, and bank overdrafts and trade credit for working capital, and this is the pattern one observes. Almost all loans and over- drafts are with domestic banks, however, and few firms do business with foreign banks. · Only firms with some foreign ownership show any real use of foreign-owned banks, and even this is small banks. Surprisingly, large firms and exporters are not more likely than small and domestic form to use loans from local or foreign sources. 48 3.5.3.1 Sources of finance used in Kenya 100% 90% 80% Retained earnings 70% Local CB overdraft 60% Foreign CB loan 50% Local CB loan 40% Trade credit 30% 20% Other 10% 0% la egr Sm citse La ngier la egr m Fo on-N retrop retrop Sm citse La ngier m Fo on-N retrop retrop Do Ex Ex Do Ex Ex Funding w orking capital Funding new Investments Source: Investment Climate survey. 3.5.4 Although most firms report funding most of their working capital and new investment out of re- tained earnings, many also have access to bank loans and overdrafts. In Figure 3.17, three quar- ters of Kenyan forms have an overdraft facility, more than three times the level in Uganda, Tan- zania, and China. Comparatively fewer firms have a bank loan--just 39 per cent in Kenya--but this level is similar to that in China and twice the level in Tanzania and Uganda. 91 per cent of firms in Kenya use trade credit, the survey indicating that three quarters of inputs are purchased in this way. 3.5.4.1 Use of different financial instruments Use of financial instruments by country Use of financial instruments by firm type in Kenya 91% 96% 100% 93% 74% 88% 89% 87% 91% 80% 78% 62% 60% 69% 71% 73% 46% 39% 44% 41% 43% 32% 35% 36% 35% 20% 23%20% 22% Kenya Tanzania Uganda China Small Large Domestic Foreign Non- Exporter Exporter Share that purchase input on credit Share that purchase input on credit Share w ith overdraft or line of credit Share w ith overdraft or line of credit Share w ith a loan from a bank or financial institution Share w ith a loan from a bank or financial institution Source: Investment Climate surveys 3.5.5 It can also be seen in Figure 3.17 that, within Kenya, larger firms, firms that export, and firms with some foreign ownership are slightly more likely to use credit. What is more important to note, however, is that smaller, domestic, and non-exporting firm are still highly likely to use credit, and in fact the gap is small. 3.5.6 Figure 3.18 compares the use of overdraft facilities and bank loans across East Africa. While small firms (those with less than 100 employees) are less likely to have an overdraft facility or bank loan in all three countries, in Kenya the gap is much smaller, largely because the use of bank 49 credit by small firms is higher in Kenya. Loan use by large firms is almost identical across East Africa. 3.5.6.1 The use and cost of credit across East Africa Share with an overdraft facility Share with a bank loan Interest rate (%) on most recent loan 80% 44% 44% 44% 17.2 17.4 16.9 69% 16.2 15.0 35% 55% 12.3 47% 17% 24% 19% 12% Kenya Tanzania Uganda Kenya Tanzania Uganda Kenya Tanzania Uganda Small Large Small Large Small Large Source: Investment Climate surveys. 3.5.7 Large firms in Kenya, however, seem to have had access to cheaper credit than small firms in 2002/03. On average, large firms reported that they paid an interest rate of 12.3 per cent on their most recent loan, while small firms reported that they paid 5 percentage pints more. Such a gap did not appear in Tanzania or Uganda. The interest premium paid by small firms does not seem to be driven by the type of bank with whom they deal. The survey shows no significant difference in interest rates offered by large and small banks; in fact the large banks tend to lend at slightly a higher interest rate (17.5 per cent) than the smaller banks (16.3 per cent). Credit constrained? 3.5.8 This section investigates the claim that Kenyan firms are credit-constrained. A credit-constrained firm is, at the very least, one that applies for credit but is refused. More generally, one might think of a credit-constrained firm as one that possesses profitable investment or sales opportunities but is unable to take advantage of them for a lack of credit financing. This latter definition includes firms too discouraged to apply for credit in the first place. 3.5.9 While the heavy reliance on retained earnings and the gap in finance use between large and small firms might indicate difficulty in access to credit, in fact most firms do not self-report feeling credit constrained. In Figure 3.19, only 28 per cent of small firms reported that they were credit constrained in Kenya, compared to 20 per cent of large firms. While this level was similar to that in Uganda, access to finance in Tanzania seems much more problematic, with twice as many firms reporting that they feel credit-constrained. 50 3.5.9.1 Share of firms self-reporting that they are credit constrained 56% 37% 28% 20% 21% 19% Kenya Tanzania Uganda Small Large Source: Investment Climate surveys. 3.5.10 Further evidence that credit constraint is not a barrier to firms is that almost half of all Kenyan firms--44 per cent--have never applied for a loan, largely because they say they do not need one. In Figure 3.20, 45 per cent of said the reason that they did not apply for a loan is that they did not need one. 15 per cent said they didn't want the debt. This implies that at least 60 per cent of firms were not interested in a loan. Firms were much more likely to apply for a loan in Kenya than in Tanzania and Uganda, and whereas Ugandan and Tanzanian firms likely to cite inadequate collat- eral or a too-difficult process as the reason, comparatively few Kenyan firms expressed this opin- ion (see Figure 3.20) 3.5.10.1 Why didn't firms apply for loans? An East African comparison % of firms that never Reasons given for never applying for a loan applied for a loan 100% Didn't need one 59% 60% Interest rate too high 80% Didn't w ant debt 44% 60% Inadequate collateral / Did not think w ould get it 40% Already heavily indebted Process too difficult 20% Other 0% Kenya Tanzania Uganda Kenya Tanzania Uganda Source: Investment Climate surveys 3.5.11 In Figure 3.21, larger firms were more likely to have applied for the loan, and those firms that did not apply overwhelmingly said it was because they did not need one or did not want the debt. 21 per cent of all Kenyan firms said the interest rate was too high. Most of these were smaller 51 firms--a third of small firms said that interest rates were too high for a loan, while very few me- dium, large and very large firms did so. 3.5.11.1 Why didn't firms apply for loans? A look at Kenya by firm size % of firms that never Reasons given for never applying for a loan applied for a loan 100% Didn't need one 53% 90% Interest rate too high 46% 80% 70% Didn't w ant debt 34% 60% 50% Inadequate collateral / 26% Did not think w ould get it 40% Already heavily indebted 30% 20% Process too difficult 10% 0% Other Small Medium Large Very Small Medium Large Very Large Large Source: Investment Climate surveys 3.5.12 Of the 106 firms in the sample that applied for a loan, only 8 reported being rejected--4 small firms and 4 medium ones. A similarly small number of firms had their loan applications rejected in Uganda. 3.5.13 Worldwide, a common reason for credit rejection is a lack of collateral. In Figure 3.22 it can be seen that collateral requirements in Kenya are high--86 per cent of loans required collateral, the average value of collateral was nearly twice the value of the loan. The share of loans that require collateral was nearly identical across all firm categories. Overall, collateral requirements were significantly higher than those required for Uganda, Tanzania and China--a feature that may be reflective of the inadequacies of contract enforcement and the legal system in Kenya. 3.5.14 In spite of the seemingly high collateral requirements, there is little evidence to suggest that col- lateral is a binding constaint in Kenya. · Of the 106 firms that applied for a loan, only 2 of the 8 rejected cited lack of collateral as the reason for rejection. Lack of collateral, of course, may have prevented many firms from ap- plying for credit in the first place, of course, but such a conclusion is not consistent with the fact that most firms reported that they need not need a loan. · Figure 3.22 shows that in Kenya, as in all of East Africa, many firms appear to possess sources of collateral--two thirds of firms owned their land and three quarters owned their buildings. · Small firms were somewhat less likely own collateral, of course--just over half owned their land and almost two-thirds owned their buildings. In this respect, it seems likely that small firms feel collateral to be a binding constraint more than large and medium ones. 52 3.5.14.1 Percentage of loans backed by collateral and ratio of loan to collateral Collateral requirments by country Average value of collateral required (as % of loan) in Kenya 178% Exporter 166% 115% 116% 86% 91% 92% 83%87% Non-Exporter 200% Foreign 169% Domestic 180% Kenya Tanzania Uganda China >100 employees 160% Share of loans that required collateral <100 employees 197% Average value of collateral required (as % of loan) Source: Investment Climate Surveys 53 4 Chief Constraints to Competitiveness: Corruption, Crime and Infrastructure 4.1 Overview 4.1.1 Why do Kenyan firms struggle to be competitive on an international scale? Why has firm growth and investment been stagnant over the period under study, and why are signs of firm growth in 2003 still so limited? As recently as July of 2004, manufacturing firm owners and industry repre- sentatives argued that firms are being forced to close down or cut back on operations, that profits are too low to upgrade equipment, and that this decline in production and investment is due to a poor business environment in the country. 4.1.2 Based on the responses of firm owners and managers, this report identifies four critical con- straints to doing business: corruption, the cost of finance, and crime. Figure 4.1 presents the full list potential constraints to doing business, along with the percentage of firm managers that said the item presented a "major" or "severe" constraint to doing business. The figure displays results for all firms as well as exporters specifically. The top three constraints--corruption, finance, and crime--were common to firms small and large, domestically and (part) foreign-owned, and ex- porting and non-exporting. Meanwhile, several infrastructure-related constraints received signifi- cant response, and together infrastructure rated firms' top constraint in terms of overall mipor- tance. 4.1.3 The barriers associated with cost and availability of finance were discussed in the previous chap- ter. This chapter will focus exclusively on corruption, crime, and infrastructure. · For each constraint this chapter look at Kenyan performance nationally, as well as in interna- tional perspective. While the responses from firm managers are subjective, differences across sectors and firm sizes are insightful. Moreover, responses are benchmarked globally. · Finally, wherever possible this report attempts to use operational data to investigate the actual impact of various constraints on business for a more objective look at the problem. 4.1.4 While corruption, finance, infrastructure, and crime were the most commonly cited constraints, they were not the sole barriers to growth and investment identified. Other important barriers raised by business managers and owners include the business and political climate, the legal sys- tem and contract enforcement, and the administrative and regulatory framework (including taxes). These additional barriers are examined in detail in Annex VII. 4.2 Corruption 4.2.1 Corruption has long been seen as a major impediment to attracting investment to Kenya. Various international ratings have continually placed the country at the bottom of the scale. For example, Figure 4.2 illustrates the performance of several countries in Transparency International's Cor- ruption Perception Index. Kenya, with a score of 1.9 out of 10 (where 10 is incorrupt) was ranked 122nd out of 133 countries. 4.2.2 Our data from manufacturing firms confirm that the perceptions of the Kenyan private sector largely mirror the stated views of the current government: Corruption is one the biggest obstacles to the growth of the economy. 54 · Corruption was rated as a severe or major obstacle by 74 per cent of the sample firms and generally seems to have the same effect on firms across the spectrum. More foreign firms, however, are seemingly more affected by corruption, as 81 per cent of them rated it as a ma- jor or very severe problem. · Foreign firms may be targeted by officials because they are seen as having ample resources. An alternative interpretation is that the international experiences of foreign firm owners and managers, and their expectations of what is normal and acceptable could influence them to perceive corruption as a greater problem and to complain more loudly. 4.2.2.1 Barriers to business in Kenya--Firms rating the constraint as a "major" or severe" im- pediment to business Corruption 74% 73% Cost of finance 73% 73% Crime, theft and disorder 70% 73% Tax rates 68% 62% Anti-competitive or inf ormal 65% practices 64% Economic and regulatory policy 52% uncertainty 57% Macroeconomic instability 51% 52% Tax administration 51% 51% Electricity 48% 56% Telecommunications 44% 56% Access to finance 44% 39% Customs and trade administration 40% 45% Transportation 37% 44% Skills and education of workers 28% 31% Access to land 25% 21% All firms Labour regulations 23% Exporters 21% Licensing and permits 15% 16% Note: Source is Investment Climate survey 4.2.3 When asked how much a typical firm in their industry pays in "unofficial payments" to "get things done," 37 per cent of the firms said zero--a curious response given that three-quarters of firms cited corruption as a "major" or "severe" problem. · One explanation is that the responding firms themselves as targets of bribe requests, but erro- neously perceive themselves to be exceptional. 55 · Another explanation is that firms receive bribe requests, but do not comply (or stop seeking the government service). Clearly in such cases the bribe, although unpaid, could pose a chal- lenge to doing business. In fact, firms told surveyors that they did not pay the bribe in 64 per cent of the cases (although 48 per cent of firms report paying at least one bribe). · Finally, it may be that firms underreport bribe activity simply out of discretion. Figures re- ported may underestimate the amount of funds being illegally collected for two reasons: 1) it is widely suspected that firms hesitate to admit to paying bribes, and 2) some firms explained how it is not always clear what percentage of the taxation is legitimate and what is illegal. 4.2.3.1 Corruption Perceptions Index--score and ranking [in brackets] 4.4 3.4 2.8 2.2 2.3 2.5 2.5 1.9 Kenya Uganda Zimbabw e Tanzania Zambia India [83] China [66] South [122] [113] [106] [92] [92] Africa [48] Notes: Source is Transparency International 2003 Corruption Perceptions Index. [#] is ranking in index. 4.2.4 Half of all firms--48 per cent--reported that at least one bribe was requested from them in the past year. Of the firms that had at least one bribe requests, the average number of requests was 3. · When firms reported a figure, bribe amounts averaged 3.8 per cent of annual sales revenue. The figure for Uganda was 2.4 per cent, and 1.8 per cent in China. · Alternatively, the average bribe per employee was more than 1,500 Ksh. Table 4.1 gives the median and average bribe levels by firm size. 4.2.4.1.1 Bribe levels (for firms that paid bribes), in Ksh Median Average Std Dev Firm Size Bribe Bribe of Bribe Small 10,000 40,785 90,047 Medium 25,000 49,935 57,223 Large 37,500 219,310 495,593 V Large 30,000 96,489 192,880 Source: Investment Climate surveys 4.2.5 Firms were asked if informal payments were requested for utility connections, government ser- vices, and during the inspections of a number of government agencies. Figure 4.3 displays the percentage of firms that reported a bribe request from each government agency, conditional on the firm having had an interaction with that agency. 56 · 55 per cent of firms that required a telephone connection in Kenya were asked for an informal payment, compared to less than a fifth of firms in Tanzania and Uganda. The median pay- ment made by firms was 5,000 Ksh. · 38 per cent of firms that sought a construction permit were also asked for a bribe--more than three times as often as in Uganda and more than twice as often as in Tanzania. The median payment made was 30,000 Ksh. · The worst offending inspections agencies include the taxation authorities, the health inspec- torate, and municipal authorities. More than a third of firms having interaction with these agencies reported receiving a bribe request. The median bribe paid to the Taxation Authority was 30,000 Ksh. 4.2.6 Regression analysis of bribery activity reveals14 than the most significant determinant of the inci- dence and value of bribe requests is the ethnicity of the firm owner. · Asian-owned firms were far more likely to be asked for a bribe, and the bribe was likely to be larger, even controlling for firm size. The probability of being asked for a bribe was 57 per- centage points greater for an Asian-owned firm, and the probability of paying the bribe was 70 percentage points greater. The average Asian-owned firm paid 2,613 Ksh more per em- ployee in bribes. · Foreign owned firms were slightly less likely to be asked for a bribe, and even less likely to pay the bribe, although these figures are not statistically significant given the relatively small number of foreign firms in the sample. · Export status and city of origin do not appear to impact the probability of being asked for a bribe or the size of the payment. 4.2.7 Many firms also admitted to being party to grand corruption-- payments made to policy makers or senior bureaucrats in order to win government contracts and influence lawmaking. · Judges and government officials appeared to be among the most partial to bribery. 28 per cent of the firms felt that they were able to affect the outcome of commercial cases which directly affected their businesses. · 61 per cent of firms reported that a gift or informal payment was "typically expected" in or- der to secure a government contract, compared to 33 per cent in Tanzania. For firms that re- ported that a positive payment was needed, the median firm reported that about 10 per cent of the value of the contract was needed to secure it. This was similar to the median amounts re- ported in Uganda and Tanzania (both 10 per cent) and was significantly higher than the me- dian amount reported in China (2 per cent). · Roughly 40 per cent of managers said that payments to government officials to affect the con- tent of government decrees had at least a moderate impact on their business, while 26 per cent of enterprises said that payments to Parliamentarians in order to affect their votes had had at least a moderate impact on their business. These figures are higher than that reported in Uganda (30 per cent and 20 per cent) but lower than that reported in Tanzania (47 per cent and 45 per cent). Overall, it appears that most firms are not confident in their ability to influ- ence binding government decisions using illegal practices. 14The figures reported are from tobit and probit regressions of the size of the bribe paid (for the tobit regression) and an indicator for being asked for/paying a bribe (for the probit regression) on indicators for location, asian ownership, export status, foreign ownership, and firm size. 57 4.2.7.1 Bribe requests by public agency or service, as a % of firms that used the service % of firms reporting a gift/payment was requested for: 55% Telephone connection 18% 19% 38% Construction permit 12% 16% 37% Taxation Authority 7% 22% 36% Health Inspectorate 34% Municipal Authorities 9% 25% 29% Labor and Social Security 2% 18% 22% Electrical connection 21% 27% 16% Sanitation/Epidemiology 3% 14% 13% Bureau of Standards Kenya 13% Fire and Building Safety 2% Uganda 8% 10% Tanzania Trading license 4% 17% 10% Environmental agencies 3% 8% 2% Import license 4% 10% Source: Investment Climate surveys 4.3 Crime and Security 4.3.1 Poor governance, including problems of law enforcement associated with weaknesses in the po- lice and in the judicial system, has been linked to rising crime and deteriorating security in Kenya during the 1990s. According to official statistics, crime in Kenya rose by 51 per cent between 1994 and 2000. The 2000 UN Habitat Survey suggests that crime is even more widespread than official figures indicate. The survey results reveal that police officers themselves are often impli- cated in criminal activity and as a result, many crimes go unreported. 4.3.2 An overwhelming indication from the ICA survey is that Kenya's law enforcement agencies have failed to protect the majority of local businesses. 34 per cent of firms reported at least one inci- dent of theft or arson in the previous year. Of those firms experiencing a crime, they reported an 58 average of 4.8 incidents. Almost 70 per cent of firms identified crime, theft or disorder as a "ma- jor" or "severe" constraint--the third most common complaint. · Generally, firm security complaints were unaffected by firm size, although it appears that Nairobi-based businesses are more severely affected. · Interestingly, non-exporters were particularly vulnerable to crime. 42 per cent of the non- exporting firms reported a loss of sales from theft during 2002. In value terms, the loss trans- lated to 3.6 per cent of sales for that year. There was a smaller incidence of direct theft, rob- bery, vandalism and arson among exporters and the proportion of sales lost in value terms is higher for exporting firms. 4.3.2.1.1 Incidence and cost of security in Kenya Firms perceiving provision of security (police) as "poor" or "very poor" 51% Percentage of firms that lost sales to theft, robbery or arson 34% Of those firms experiencing a crime: Average sales loss as a percentage of total sales 4% Average number of incidents reported 4.8 Percentage of incidents reported to the police 79% Percentage of incidents solved 18% Source: Kenya ICA 4.3.3 In our survey, firm owners and managers were asked to rate the services provided by the police. 56 per cent of business owners or managers said that they were either "poor" or "very poor". While 80 per cent of all incidents were reported to the police, only 20 per cent were solved. 4.3.4 According to the firm survey, crime is extremely costly to businesses. · The costs of economic crime, (fraud, embezzlement, extortion, money laundering, breach of trust and corruption) are a heavy burden for business. A Price Waterhouse Cooper survey of this problem in East Africa found that the most serious problem is embezzlement by employ- ees. Crime and insecurity also negatively affect the image of Kenya in the international in- vestment community, which places a premium on locating in countries with good living con- ditions for expatriates. · The cost of inadequate security becomes visible when firms are asked to estimate the per- centage of revenue lost each year. One third of the sample firms lost sales due to crime, the average loss was 4 per cent of annual sales revenue. · Firms also incurred direct costs protecting themselves from criminal acts. In response to their dissatisfaction with public security services, 82 per cent of firms invested in private security measures such as fences, alarms, and vehicles. These firms spent an average 2.7 per cent of sales on security--the median expenditure being Ksh 100,000 (or roughly US$1,300). 4.4 Infrastructure 4.4.1 Compared to results from recent investment climate surveys in other countries, Kenyan firms' opinion of infrastructure services were extremely poor. Roughly half of all firms rated electricity, transport, water, and telecommunications services as a major constraint to their business. Not only is this level high in absolute terms, but the number of dissatisfied firms is typically greater 59 than that seen in Uganda, Tanzania, China, and elsewhere. Exporters, moreover, are generally less satisfied with infrastructure than non-exporters. 4.4.2 Poor infrastructure has direct and indirect costs to manufacturing firms. · Many firms sacrifice their profits to purchase generators, dig their own wells, and repair their own roads as the provision of public goods like roads, water, and electricity has been ex- tremely poor and unpredictable. · Poor infrastructure reliability may also require higher inventories and shape investment choices and locational decisions, such as when an agro-processor locates in a city rather than near the source of a bulk commodity. · Not only may poor infrastructure (and the forced private provision of such services) be ineffi- cient in an economy-wide sense, but on an individual level they erode profits, discourage in- vestment, and further reduce international competitiveness. 4.4.3 Corruption and bribery are also common in customs clearances, utility connections, and other infrastructure-related services. These costs will be discussed in this sub section as well as in the discussion of corruption. Transportation 4.4.4 Kenyan firms find transport infrastructure to be a much more serious constraint than firms in other countries. In Figure 4.4, while 37 per cent of firms found transport a "major" or "severe" constraint to doing business in Kenya, the figure was just 23 per cent in Uganda and Tanzania, and 19 per cent in China. 4.4.4.1 Benchmarking Kenyan transport satisfaction %of firms rating transport as a "major" or "severe" business constraint 37% 30% 23% 23% 19% Kenya Uganda Tanzania Zambia China Source: Various ICAs 4.4.5 Roads. The principal source of discontent with transport infrastructure appears to be the dramatic deterioration in road quality. · Nearly three-quarters of firms reported roads to be "poor", "very poor" or "not available"-- ratings that were generally consistent across regions, and much greater than the levels of dis- satisfaction expressed for other transport services (see Figure 4.5). · After deteriorating steadily during the 1980s, road quality collapsed during the 1990s. The reasons were insufficient resources, and mismanagement of the resources that were allocated. Government allocation of funds was insufficient, and a decline in donor funding for road in- frastructure was not fully offset by domestic spending on road maintenance. Meanwhile, cor- 60 ruption has resulted in award of contracts to incompetent contractors and poor quality road works. In TI Kenya's 2001 survey on bribery, the Ministry of Public Works topped the list of public services in average size of bribe paid, and requests for bribes were encountered in 83.3 per cent of the dealings with that ministry. 4.4.6 Poor quality roads directly and dramatically diminish firm competitiveness and profitability. · The costs, delays, and uncertainties created by a failing road infrastructure affect businesses badly, particularly those that handle highly perishable products and face tight export dead- lines, such as the horticulture industry. In 2002/03 2.5 per cent of exporter's cargo was re- jected, returned or discounted as a result of delays. · Poor road quality increases vehicle maintenance and trucking costs. 84 per cent use trucking services and, while they appear relatively satisfied with the quality of services (See Figure 4.5), operators report that truck maintenance may absorb up to 8 to 10 per cent of overhead costs. · Firms are also forced to provide roads out of their own pocket. 24 per cent of the firms in the sample reported spending resources to improve roads in their surrounding area. Anecdotal ac- counts explain that a common practice is for a number of adjacent firms to pool resources to fix shared roads. 4.4.6.1 Firms perceiving service to be "poor", "very poor" or "not available" 80% 76% 73% 74% 77% 58% 60% 51% 47% 38% 21% 20% 13% 12% 9% 10% 9% 5% 5% 3% All Kenya Nairobi Mombasa Nakuru Eldoret & Kisumu Roads Railways Air Freight Services Trucking Services Source: RPED/KIPPRA 2002/03 Kenyan firm survey 4.4.7 Rail. Kenyan railway service has greatly deteriorated in the last two decades. As a result, only 35 per cent of firms in our sample used Kenya Railways, compared to the 84 per cent that used trucking services. Those that do use the railways rank them just as they did the roads--poor. · Kenya Railways (KR) has fallen from carrying the dominant share of freight traffic between Mombasa and Nairobi (and almost all freight traffic into Uganda) to now carrying roughly a fifth of Mombasa port and Ugandan cargo. Its prices for moving containers can be up to dou- ble those charged by road transport. Tanzania Railways have already won much of the Bu- rundi market and a substantial part of the Rwanda market, and is actively pursuing the Uganda market.15 15CEM, 2003. 61 · Almost two-thirds of firms rated rail services as "poor", "very poor", or "not available" (see Figure 4.5). 4.4.8 Air. Firm satisfaction with airport services is high, supporting anecdotal evidence that air trans- port is operating well in a liberalized environment. · Kenya has three international airports, Nairobi's Jomo Kenyatta International Airport, Mom- basa's Moi, and the Eldoret Airport, as well as a number of domestic airports. In addition to passenger services, it has air cargo handling facilities. The 1996 privatization of Kenya is viewed as broadly successful, and the airline is now an African market leader. · Three-quarters of firms in the sample use air freight services, and only 13 per cent rated the quality of service as a constraint to their business (see Figure 4.5). This satisfaction is striking in comparison to the dissatisfaction with road and rail services. 4.4.9 Ports. While ports were not examined in the ICA survey, the 2003 CEM argues that ports are Kenya's single most important infrastructure constraint. For example, a recent single shipment from Felixstowe (UK) to Mombasa, the charge for unloading at Mombasa was around six times the charge for loading at Felixstowe. Costs relating to corruption and delays are also high. · The CEM notes that the port of Mombasa has historically suffered from outdated equipment, poorly trained personnel and management, overstaffing, corruption, and political interference. · Port users complain of high port charges and poor levels of service. A 2001 TI Kenya survey reported that firms were asked for bribes in 75 per cent of their dealings with the port author- ity, and paid an average of Ksh 9,700 in bribes. · Mombasa's container productivity is also reckoned to be between a third and a half of ac- cepted international norms. · While customs clearances were reduced to roughly 10 days in 2003, down from over 20 days in the mid-1990s, the management of the port authority estimates that around 6 days can be accounted for by delays in clearances and paperwork. 4.4.10 Interestingly, firms in Nakuru are consistently less likely to report dissatisfaction with transporta- tion infrastructure. Later in this subsection it will be seen that dissatisfaction with electric power and telecom services are similarly low in relative terms. The evidence seems to support the hy- pothesis that infrastructure services are superior in Nakuru to other cities. · With slightly more than 10% of the sample in Nakuru, the different levels of satisfaction are not likely to be the result a small sample problem. · Meanwhile, levels of dissatisfaction with corruption, finance and crime are similar to those in other urban areas. · Nakuru firms were less likely to report having to provide their own power infrastructure, and less likely to generate their own energy (although they claim to have lost amount the same amount in merchandise value from outages as the Nairobi average). They were less also likely to build their own roads. Electric Power 4.4.11 Of infrastructure-related issues, electric power is unquestionably one of the most problematic. The loss in production time and sales from outages, the loss of equipment from power surges, and the efficiency loss caused by interruption and uncertainty are severe competitive disadvantages. · The existing electric network is inefficient and volatile. It is predominantly hydro-based, thus exposing the country to power shortages in times of drought, as happened in year 2000. The electric utilities are also subject to considerable inefficiencies. Power losses in transmission 62 and distribution average 21 per cent of total energy produced. Transmission and distribution margins are severely eroded by high operating costs, particularly staffing costs. Arrears from power sales are a major cause of liquidity constraints. The Government has estimated that be- cause of neglect over the last 15 years, it needs $1.5 billion to meet the demand for energy. 4.4.12 As seen in Figure 4.6, 37 per cent of the manufacturing firms in the Kenyan sample rated electric- ity service as "poor", "very poor", or "not available". Service was perceived as poorest in Nai- robi. 4.4.12.1 Firms perceiving electricity service to be "poor", "very poor" or "not available") % of firms perceiving electricity service to be "poor", "very poor" or "not available" 43.2 37.2 34.9 33.3 12.5 All Kenya Nairobi Mombasa Nakuru Eldoret & Kisumu Source: Investment Climate survey 4.4.13 Kenya's electricity service appears to be poorer and more costly than that of Uganda, Tanzania, Zambia and China. Figure 4.7 benchmarks Kenya against its competitors along six dimensions. · 48 per cent of Kenyan firms rated electricity as a major or severe constraint, versus 45 per cent in Uganda, 40 per cent in Zambia, and 28 per cent in China. Only Tanzania was worse. 4.4.14 Electricity outages and surges are extremely costly to Kenyan firms. · In 2002, Kenyan firms reportedly experienced 33 outages--less than other countries but still a large amount and, with the greatest loss of sales, probably more severe and long-lasting than in competitors. · The average value of lost production due to power outages or surges, as a percentage of total annual sales, was 9 per cent in Kenya. This level was equivalent to that in Tanzania, but far greater than Tanzania (6 per cent), Uganda (5 per cent) and China (2 per cent). · To cope with frequent outages, 70 per cent of the firms own one or more generators--a much higher number than other countries surveyed. In 2002, Kenyan firms met 14.5 per cent of their electricity requirements with these generators. · Firms also lose capital and production capacity to surges and outages. 64.4 per cent of firms experienced damage to--or complete loss of--equipment due to power fluctuations or outages. For these firms, this loss was valued at an astonishing average of 1,147,182 Ksh (or $14,918 dollars) per firm in 2002--or (at the median) 3 per cent of output. Comparable figures are 5 per cent in Tanzania and zero in Uganda and China. 4.4.15 Utility costs were cited by the fourth largest proportion of firms (23.6 per cent) among the top three constraints. The cost of electricity per kilowatt-hour was reported as 7.8 Ksh (or 0.10 cents 63 US), which includes fixed monthly fees. When compared to recent surveys in other countries, electricity costs in Kenya are generally 10 to 30 per cent greater. 4.4.15.1 Benchmarking Kenya's energy sector % of firms rating electricity as a % of production lost due to power "major" or "severe" business outages constraint 9% 9% 58% 48% 6% 45% 28% 2% Kenya Uganda Tanzania China Kenya Uganda Tanzania China Average number of power outages Firms owning own geneator last year 70% 67 55% 39 35% 33 17% Kenya Uganda Tanzania China Kenya Uganda Tanzania China Number of days to obtain an Cost of electricity ($US/KwH) electricity connection $0.11 66 $0.10 $0.10 $0.09 $0.07 $0.07 38 23 18 Eritrea Mozam- India China Kenya Nigeria Kenya Uganda Tanzania China 2002 bique 1999 2000 2002/03 2001 Note: Data drawn from World Bank ICAs. Data for Zambia is for power outages and power surges. 4.4.16 Finally, firms face delays and heavy costs in obtaining electricity hook-ups. Kenyan firms report that it takes more than two months to obtain a new electric connection. The delay is roughly twice that in Uganda and three times that in Tanzania and China (see Figure 4.7). Industrial customers are often expected to bear a substantial part of the costs of supplying standard power and connec- tions, which appears an unfair burden on the customer. 64 4.4.17 Addressing the energy problem is even more urgent when taking into account that the govern- ment's growth strategy depends in part on increasing exports and attracting foreign direct invest- ment. These firms are much more sensitive to disturbances in electricity provision. Water and Sewage 4.4.18 Water service is rated extremely poorly in Kenya. In Figure 4.8 more than half of all firms in Kenya rate water services as "poor", "very poor", or "not available". The number rises to three- quarters in Mombasa and Nakuru. Also in Figure 4.8 more than two-thirds of all Kenyan firms rate waste disposal services as "poor", "very poor" or "not available". Ratings are consistently poor across all regions. 4.4.18.1 per cent of firms perceiving service to be "poor", "very poor" or "not available" Water Service Waste Disposal 74% 69% 70% 69% 78% 72% 54% 40% 49% 27% All Kenya Nairobi Mombasa Nakuru Eldoret & All Kenya Nairobi Mombasa Nakuru Eldoret & Kisumu Kisumu 4.4.19 The 2003 CEM reports that underinvestment in maintenance has resulted in the collapse of the water and sewerage infrastructure, and yet tariffs are relatively high. · The typical tariff of 40 U.S. cents per cubic meter compares with 27 cents in Ghana, 56 cents in Senegal and 73 cents in Uganda. The industrial charge for water in Mombasa is said to be higher than in some desert Middle Eastern cities. · In addition, neglect of water resource management issues in urban water and sewerage ser- vices has contributed to destruction (and in some cases, complete abandonment) of major in- vestments. 4.4.20 In Figure 4.9, in response to the poor quality of water service, a third of Kenyan forms have built their own wells--a level similar to that in Tanzania and more than twice that seen in Uganda and China. Well-construction is, however, less prevalent that in India and Zambia where water service is presumably even poorer. 65 4.4.20.1 Benchmarking water service internationally Median wait for a water Share of firmsthat have built own well connection (in days) 60% 7 51% 34% 35% 2 16% 13% 0 Kenya Uganda Tanzania Uganda China* Keny a Tanzania India* Zambia Notes: Sources are country Investment Climate Assessments. *=Number of firms that own a well. 4.4.21 Firms also incur unreasonable or excessive costs in obtaining a utility connection. · Extending lines from the main water distribution grid to the development site is currently the responsibility of the firm. Firms are also being required to pay connection deposits, which the 2003 CEM reports may run up to $3,850. In addition, they have to make significant meter rent payments, for water meters are the property of the local authority. Telecommunications 4.4.22 Kenya's performance in the fixed telecommunication sector is poor, mostly due to the weak man- agement and financial performance of the public monopoly telecom company, Telkom Kenya. The arrival of mobile technology has dramatically eased the constraints of poor landline tele- communications, and mobile subscribers dwarf the number of fixed line subscribers. Yet tariffs are still high, and fixed line Internet access is poor and expensive. 4.4.22.1 Firms perceiving telecom services to be "poor", "very poor" or "not available" Land Telecommunications Mobile Telecoms 56% 53% 50% 44% 22% 9% 8% 7% 3% 0% All Kenya Nairobi Mombasa Nakuru Eldoret / All Kenya Nairobi Mombasa Nakuru Eldoret / Kisumu Kisumu Source: Investment Climate Assessments 66 4.4.23 As a consequence of poor service, fixed line (or "land") services were deplored by more than of firms in Nairobi, Eldoret and Kisumu (see Figure 4.10). 4.4.24 A look at the basic indicators reveals the difficulty firms encounter in dealing with telecommuni- cation services. · It took firms an average 124 days to obtain a connection. The median connection time was just 42 days (still high relative to competitors) but 15 firms reported waiting at least a year. · 56 per cent of firms indicated that an informal payment was asked for or expected for a con- nection. The actual payment was often relatively low, on average Ksh 5,000. · Firms reported a median of 14 days in the preceding year without main telephone service available, with each interruption lasting an average of 12 hours. Only 17 per cent reportedly received continuous service over the last year. This is an improvement on the electricity situa- tion, but still a burden for businesses. 4.4.25 The cost of fixed telecom services is high and the quality is poor. International calls are expensive and outgoing call volumes are low. Table 4.3 indicates that the per minute cost of a call is two to ten times more expensive in Kenya than in the OECD, while the ability to pay in Kenya is con- siderably lower. 4.4.25.1.1 The Cost of Telkom Kenya Services in 2002 Telkom Kenya OECD Average Monthly rent US$3.64 US$15­20 Local call per minute 0.7 cents 3­5 cents Long distance call per minute 40 cents 10 cents International call per minute US$2.50 10­30 cents Source: CEM 2003, from World Bank database 4.4.26 Evidently, the arrival of mobile technology has eased the constraints of poor landline telecommu- nications. Over 90 per cent of firms regularly use a mobile phone in their interactions with clients and suppliers, and a vast majority was satisfied with the services received, with just 7 per cent of firms complaining about the quality of service (see Figure 4.11). It appears that the availability of wireless services is more imperative for businesses operating outside the capital, as reliance on mobile phones was higher for firms in the other regions. 4.4.27 Kenyan telecommunications also fare poorly when compared internationally. In Figure 4.11 nearly half of Kenyan forms found telecommunications to be a "major" or "severe" constraint to doing business--roughly two and a half times that in China, four times that in Tanzania, and nine times that seen in Uganda 4.4.28 Firm Internet access and usage is moderate. · Almost 80 per cent of firms had internet access. There were significant regional disparities, however, and Eldoret had the lowest access rate of 66 per cent. The majority of internet use was email-related, although 32 per cent regularly used a website in their business operations. · A recent survey has found that about 87 per cent of organizations in Nairobi have an email address (although outside of Nairobi only 60 per cent have one), that the country has about 1,000 cyber cafes, and that 15 per cent of the workforce in Nairobi use computers .16 16CEM 2003, quoting a report from the Ministry of Finance and Planning, 2002. 67 · About 56 per cent of surveyed institutions in Nairobi have also developed in-house training for ICT applications.17 4.4.28.1 Telecommunications as a business constraint in international perspective % firm s rating telecom munications as a Average number of days to obtain a "m ajor" or "severe" business constraint telephone connection 132.5 44% 123.7 33% 17% 12% 33.2 23.1 5% 12.5 Kenya Uganda Tanzania Zambia China Kenya Uganda Tanzania Zambia China Source: Investment Climate Assessments Exporters' Evaluations of Infrastructure 4.4.29 Generally, exporters are more dissatisfied with all the infrastructure services. For instance, 45 per cent of exporters perceive electricity services as poor or worse, whereas only 28 per cent of non- exporters perceive electric services so. Figure 4.12 illustrates the perception gap between export- ers and non-exporters for a variety of infrastructure services. 4.4.29.1 Firms rating service as "poor", "very poor", or "not available", by export status 77% 69%69% 65% 66% 60% 58% 58%61% 53%54% 45% 37% 28% 18%18% 13% 9% 9% 9% 3% 3% Mobile Trucking Air services Postal Electricity Land Water Security Railw ay Roads Waste phone services services telephones services Disposal Non-exporters Exporters 4.5 Other Key Barriers to Investment 4.5.1 Several other barriers were considered important by firm owners and managers, and they are de- tailed in Annex VII and summarized below. CEM 2003, quoting from ICT Plan Working Group, 2001. 68 4.5.2 Business and political uncertainty. Investment is a forward-looking activity. Uncertainty, cou- pled with corruption and taxation, probably contributed to the low and declining rates of invest- ment by firms in the sample period. · The survey was conducted in the run-up to a competitive national election, and more than half of the firms listed macroeconomic instability and economic and regulatory policy uncer- tainty as "major" or "severe" constraints. · Uncertainty appears, however, to go beyond that created by the looming 2002 election. More than 45 per cent of Kenyan firms disagreed with the statement that "interpretations of gov- ernment regulations are consistent and predictable. 4.5.3 The legal system and contract enforcement. Secure property and contractual rights play a vital role in modern economies. When enterprise owners are unsure about the security of their property rights, they will be unwilling to risk investing their capital in projects that yield profits only in the medium- to long-term. Several studies have found that the `rule of law' is relatively poorly pro- tected in Kenya when compared to other countries. Looking at the firm survey data, it is seen that perceptions of the legal system are very poor. 4.5.4 Administrative, legal, and regulatory framework. Administrative, legal, and regulatory com- pliance can be a heavy burden on many businesses. Direct costs include taxes, managerial time, lawyer and other professional fees, meetings with and inspections from local authorities, fees and penalties, and unofficial payments. · When the regulatory burden is particularly time-consuming or costly, business can be dis- couraged. Licensing and registration, for instance, can delay the pursuit of investment oppor- tunities. Excessive regulation can also drive firms into the informal sector where they remain unregulated and untaxed, but also short of capital and public services. · In general, there is evidence to suggest that the regulatory burden in Kenya appears to be greater than elsewhere in East Africa. · Firms reported taxation and tax administration to be a particularly serious concern--tax ad- ministration and tax levels were identified as problematic by the majority of the sample, and were named among the top three problems of doing business in Kenya by more than a third. Both tax rates and tax administration were reported to be more onerous by the small, non- exporting and domestic firms. 69 5 Policy Reforms 5.1.1 The GoK and donors have recognized the need for reform in each of the key areas of the invest- ment climate. The election of a new government in December 2002 offered an opportunity to break with the past and usher in reform. Twenty months have now passed since the change in government and the collection of much of the firm data. This section outlines the recent changes in the business environment, including government reforms and donor responses in each of the key areas of the investment climate. It also discusses the way forward in each of the key areas that need improvement--factors of production, infrastructure, corruption and crime and the pub- lic-private dialogue. 5.1.2 In general, the new government has planned and announced major reforms, and demonstrated a commitment to promoting private sector development and public sector reform in words and with action. The reforms and actions taken thus far, however, have been mild. Naturally, widespread and ambitious reforms like those planned for the Kenyan economy and public sector take time, and so the pace of reform is not necessarily a concern. Even so, many of the planned goals and timelines of the new government have passed without implementation of the reform, and there is a growing concern in the media and among donors that the reform process has been delayed or stalled by political discord at the national level. 5.1.3 There has been a slight reversal of the trend in declining GDP growth of the last two decades, with a growth rate of 1.8% in 2003/04, As discussed earlier, export performance in the past three years has been strong and is expected to persist, due to growth in the garments, cut flowers, and tea sectors. The gradual depreciation of the shilling, which persisted through the first 6 months of 2004, is having a positive impact on Kenya's export competitiveness, although it is raising the cost of imported capital and intermediate goods. Firms continue to take advantage of government export platforms, with the number of firms and employment in the EPZs roughly tripling between 2001 and 2003. Trade liberalization--including progress towards freer trade in the EAC and COMESA, further opening of the EU and North American markets, and the extension of AGOA to 2015, and third country sourcing of fabric to 2007--should continue to boost exports. Various tax measures have been introduced, including duty waivers on capital goods and plant and equipment, and an increase in the investment allowance from 60% to 100%. 5.1.4 The analysis of the ICA results, supplemented by results from the Growth and Competitiveness and the FIAS Administrative Barriers reports, suggests that the overarching objectives of Kenya's Private Sector Development (PSD) policies should be twofold: a. Formalization and growth of micro and small enterprises through the correction of eco- nomic incentives to formalization (such as administratively costly regulation) and the re- moval of key barriers to expansion (such as access to finance, streamlined business regu- lation and introduction of simplified taxation for MSMEs); and b. Enhancement of the productivity and international competitiveness of medium and large firms through improvements in the provision of public services (such as power and trans- port infrastructure), the removal of administrative barriers (such as corruption in regula- tion), and the provision of investment incentives (such as appropriate training incentives). 5.1.5 This section of the report describes policy suggestions that may improve the investment climate in Kenya. Micro and small enterprises, particularly those in the informal sector, may avoid costly and inappropriate corruption and regulation, but they avoid legitimate regulation as well-- especially taxes, but also labor and environmental controls. Informality also limits their access to 70 finance, the courts, and government services. Structural reform should be directed at correcting the incentives that have pushed economic activity into the informal sector and encouraging the graduation of these firms from the informal to the formal sector. 5.1.6 Reform should also be directed at encouraging the sustained growth of these firms into larger and more productive enterprises. While growth in the informal sector accounts for nearly all of the employment growth in Kenya in recent years, it should be noted that such growth may not have been possible in the more rigid and regulated formal sector. A focus on correcting incentives and opportunities rather than simply increasing enforcement will better preserve the dynamism of smaller firms. 5.1.7 Medium and large firms are currently discouraged from new investment by high levels of busi- ness uncertainty, and appear especially constrained by the inadequate access to and reliability of public services, the historically high cost of finance, and high wages in combination with poor overall productivity. Transport, policing and power services seem especially problematic. It is both inefficient and costly for firms to privately provide their own infrastructure (such as roads, security, water and electricity). Uncertainty in the policy regime has also resulted in outdated plant and equipment, low investment levels, and poor training. The uncompetitive levels of wages economy-wide are also a concern, and need to be examined further. New policy will need to balance competitiveness in the cost of labor with the goals of fair remuneration and poverty al- leviation. 5.2 Improving the Quality of Labor 5.2.1 Kenyan labor productivity is low relative to competing export countries such as India and China, given the amount of capital per worker. Although worker education is quite high, formal training is considered poor in Kenya. As noted in the World Bank's 2004 report on Growth and Competi- tiveness in Kenya, what is required is an unequivocal commitment from the Government for a demand-driven, private sector-led TVET policy and system where the role of the Government is focused primarily on policy and strategy formulation, planning and regulation of the system. The report's assessment of skills demands from the growth sectors (e.g. the garments sector) suggests that reform in the delivery of training is urgent to ensure that these sectors remain competitive. 5.2.2 As discussed in Chapter 4, current training curricula are obsolete, and major deficiencies are ob- served in public training facilities and instructional capacities. Moreover, the principal incentive system for firm training, the Industrial Training Levy (ITL), not only appears to be in a state of financial crisis, but also does not fully reimburse firms for their expenses, and does not cover the specialized skills required by many firms to compete in export markets. 5.2.3 As noted in the most recent CEM, wage increases have not been commensurate with productivity increases. The problem is economy-wide. Little is known about the causes of these real wage in- creases, and so recommendations regarding minimum wages, collective bargaining, labor taxa- tion, and other issues may not address the problem. 5.2.4 To address training and skills, the Ministry of Labor recently announced that it is working on a national training strategy. In addition, Ministry of Trade and Industry is beginning to implement a World Bank financed Micro, Small and Medium Enterprises (MSME) project, of which skills development will be a focus. For industrial skills development, the project proposes to consider options for restructuring the Industrial Training Levy Scheme, which is criticized for failing to cover relevant industrial training. For management, entrepreneurship and skills development, the 71 project will introduce an innovation competition and strengthen the institutional capacity of busi- ness schools. Specific recommendations Establish National Stakeholder Committee on TVET reform (representative, lean, mandated deliver- ables and timeline, to adopt and implement a national TIVET policy that is responsive to private sec- tor and labor market needs Facilitate and support the provision of training by the private sector 5.3 Improving Access to Finance 5.3.1 The analysis in Chapter 3 suggests that small and medium-sized forms encounter the most diffi- culty in obtaining finance. Moreover, the financial market is characterized by generalized high in- terest rate spreads which invariably depress demand for finance and consequently pose invest- ment hurdles for all firms. 5.3.2 A recent Financial Sector Assessment Program (FSAP) produced by the IMF and the World Bank, in cooperation with the GoK, suggests that the major obstacles to developing the financial system, especially access to finance by small and medium-size enterprises, are the weak legal framework, lack of information on borrowers, and inefficient judiciary. The report also suggests that high interest rate spreads are primarily the result of several weaknesses in the banking sys- tem, including: a very high proportion of non-performing loans (NPLs) in publicly-owned institu- tions; relatively high banking costs owing to high overhead costs and outdated infrastructure; the serious deficiencies in the legal framework and infrastructure detailed above; the presence of a number of weak banks that have been allowed to continue in operation; and poor regulatory gov- ernance and lack of transparency of financial sector supervision. 5.3.3 Banks are currently not well-equipped or experienced enough to adequately deal with the SME loan market, while at the same time SME managers may not have the skills to produce business plans for obtaining finance, as well as meeting reporting requirements. 5.3.4 Meanwhile, two recent government initiatives have raised uncertainty in the financial sector. Firstly, the potential repossession of illegally obtained public land has concerned bankers, since some of this land will have been charged as security for loans. Two potential outcomes of this policy are an increase in the level of non-performing loans and a sharp fall in new credit. Sec- ondly, the Ministry of Finance has indicated it may exercise the right to approve all changes to non-interest bank fees and charges, possibly retroactively. The right is a holdover from the 1990s when interest rates and fees were skyrocketing, and has not been used in some time. While the initiative is popular with the public and the business community, the banks and financial sector specialists have warned of serious negative consequences on the sector. 72 5.3.4.1 In order to address the deficiencies in the legal and institutional framework for finance, GoK, with financing from the World Bank and DFID, have initiated a Financial and Legal Sector technical Assistance Credit (FLSTAC). The FLSTAC will support the GoK in: (i) formulating a financial sector development strategy, (ii) restructuring and privatizing publicly-owned financial institutions, (iii) strengthening sector regulators, (iv) improvements in the access to credit by small and medium enterprises, (v) strengthening debt management institutions and debt mar- kets, (vi) encouraging judicial and legal reforms related to financial markets, and (vii) moderni- zation of the National Payments System. 5.3.4.2 In order to build the capacity of a range of financial institutions to better provide financial ser- vices to different segments of the MSME sector, DFID and the GoK, through World Bank fi- nancing (Micro, Small, and Medium Enterprise Competitivness project), are cooperating on a Financial Sector Deepening Trust. Specific recommendations in the FSAP for improving access to financial services Modernize key commercial registries to provide access to current, accurate, and reliable infor- mation and establish the legal basis for credit information sharing among all financial service providers. Remove barriers to creation, registration, and enforcement of security, and integrate the land registry systems, including the removal of hidden liens and excessive registration costs. Reform and modernize insolvency procedures contained in the Companies and Bankruptcy Acts. Strengthen capacity in the Commercial Court to achieve efficient case administration, and pro- mote training among judges. Expand the specialized Commercial Court to other regions, includ- ing Mombasa. 5.4 Addressing Corruption and Crime 5.4.1 The analysis in chapter 4 suggests that corruption is the most important constraint to doing busi- ness in Kenya. While the GoK has taken a number of laudable steps to address corruption, there are a few disturbing trends in the Governments stance. 73 5.4.1.1 While media reports suggest that high-level corruption is in resurgence, the Kenya Anti- Corruption Commission (KACC) had its funds cut in the 2004 budget by close to Ksh 100 mil- lion, and has only recently (and controversially) received a new Director--Appellate Judge Aaron Ringera, supported by NAK and vehemently opposed by LDP and KANU ministers. In particular, recent events indicate that the government is reluctant to pursue high-level corruption amongst its ranks. 5.4.1.2 In May 2002/03, Parliament enshrined wealth declaration requirements into law with the Public Officer Ethics Act, which demands that all public officials and employees declare their family's income, assets, and liabilities. In June 2004, public employees that did not comply had their salaries suspended. While the policy has been welcomed, it has also been criticized for a lack of focus on high-level officials, a lack of public access to records, ambiguity about what must be declared, and no framework for inspection. 5.4.1.3 In January 2002/03 the post of Permanent Secretary for Governance and Ethics was created for internationally respected anti-corruption activist John Githongo in the Office of the President. The (temporary) relocation of Githongo from the Office of the President to the Ministry of Jus- tice and Constitutional Affairs in July 2004 was widely interpreted as a relegation and with- drawal of crucial Presidential support for anti-corruption. His recent resignation is a further set- back and undermines the government's anti-corruption credentials. Recent appeals from within the cabinet for the president to take action are encouraging. Strong political leadership from the president and the Cabinet on governance issues is essential in building trust in government and in the reform process. The next few months will be a crucial test of the government's resolve to deal with allegations of high profile corruption. 5.4.2 The discrete drop in petty corruption observed in 2003 cannot be explained by increased levels of enforcement or scrutiny, or to reduced regulation. Anecdotally, the improvement appears to have arisen from a change in perceptions and sensitivity to corruption, largely as a result of the change in government. Grand corruption and scandals at the highest levels of government threaten to un- dermine the progress that has been made in petty corruption since 2002. 5.4.3 Funding and support for anti-corruption institutions continues to be limited. What resources have been allocated have focused on grand corruption. Institutions focused on the elimination of day- to-day corruption faced by firms in inspections or transactions have yet to be developed, but are arguably just as important as institutions to fight grand corruption. The recent withdrawal of funds for anti-corruption activities by some donors exacerbates the financing dilemma of anti- corruption institutions. 5.4.4 Corruption in public service delivery to firms goes hand-in-hand with the efficacy of business regulation--the appropriateness of regulatory requirements, monitoring and enforcement proce- dures, and institutional oversight. As noted above, the current lack of clarity, consistency and transparency clearly contributes to discretionary and predatory behavior by government officials at the operational levels. Increase the staff and financial resources of anti-corruption institutions and establish systems for monitoring the impact of corruption reforms. Options include surveys of enterprises, households and other users of public services. Develop and reinforce institutions to increase scrutiny of firm inspectors and regulators. Target particularly offensive agencies, such as the taxation authority, municipal authorities, and utilities 74 Enforce public officer codes of conduct more strictly and publicly, and with officials at the firm- level. Establish an anti-corruption authority or ombudsperson for the reporting and investigation of petty (firm transaction-level) corruption 5.4.5 In a recent strategic document, the Kenya Police Force (KPF) noted that the public's view of the justice system as corrupt and the KPF as lacking competence and integrity is largely a correct one. The authorities have sought to tackle the surge in violent crime, so far unsuccessfully ac- cording to media reports. Even so, a number of changes in the KPF are apparent: In order to raise morale, combat police corruption and improve service and image, in July 2003 the government announced substantial pay rises, investment in living quarters, the purchase of new equipment, human rights training, and (in five years) a tripling of the force. In January 2004 junior police officers had their pay doubled. In May 2004, 59 senior police officers lost their posts, the controversial Kenya Police Reserve was disbanded, and the KPF Chief announced new recruitment procedures. In 2004 the KPF also produced a strategic plan that, while criticized for over-ambition, is a frank admission of the problems facing the force and sets out relatively clear priorities and actions. While the police force retained their top position in the TI Kenya bribery index, their 2004 score index improved by almost 20 per cent (dropping from 69.4 to 57.3). 5.4.6 The government's GJLOS reform program appears to have resulted in some real gains in the past year, though there is much more to do. As noted above, TI Kenya's 2004 Bribery Index regis- tered a substantial improvement in petty corruption in the past year. TI Kenya suggests that the reduction in bribery is consistent with a transformation of public attitudes of the acceptability of bribery in the wake of the new government and its high-profile anti-corruption talk and efforts. It is also consistent with the perception of increased likelihood of being punished if caught. In spite of improvement in the bribery index, the Kenyan civil service remains one of the most corrupt institutions in the country. Transparency International argues that the fight against corrup- tion is hindered by weak incentives and poor enforcement, particularly in the civil service. These include weak and unaccountable enforcement structures, poor design of oversight and monitoring systems, and excessive bureaucracy and over-regulation. Partly in an effort to raise morale and combat corruption, in July 2004 the government announced a substantial pay increase for its 130,000 staff. For this move to be effective, it needs to be accompanied by greater transparency and a meritocratic system for promotions and raises. Specific Recommendations Keep up the momentum on current reforms of the Kenya Police Force. Examine viable alternatives for a transparent and meritocratic system for promotions and raises. 5.5 Improving the Commercial Legal Framework and Removing Administrative Barriers to Investment 5.5.1 FIAS has recently completed a comprehensive review of Administrative Barriers to Investment and Improving the Commercial Legal Framework, which covered the Legal Framework for In- vestment, Licensing Procedures and Inspections, Access to Land for Investment, Customs and Trade Administration, and the Taxation System. 5.5.2 The ICA and FIAS findings also indicate that business regulation and inspections are principally an opportunity for low-level public officials to extract bribes from firms, and that these bribes represent a significant portion of revenue. The FIAS report also finds that most regulatory sys- tems are outdated and do not serve an identifiable purpose. For instance, the current business reg- 75 istration in Kenya is archaic, inefficient and unreliable. Licensing procedures were similarly found to be overly complex, and more importantly to contain significant redundancies. The GoK, through the World Bank financed Micro, Small, and Medium Enterprise Competitiveness project, will be designing and implementing a simplified business registration process, possibly through a decentralized one-stop shop approach. In addition, the streamlining of sector licenses will be tackled under the PSD Action Plan process, as discussed above. 5.5.3 Reviews of the legal sector have found that the court systems are currently in disarray. The back- log of cases in the Magistrates Courts is huge and growing. The Commercial Court, which has been relatively effective, also suffers from a growing backlog. The entities that implement, en- force, and prosecute the laws are under-staffed and under-trained. The GoK, is addressing these problems through the Governance, Justice, Law & Order Sector Program, which is supported by a large number of donors through basket funding. 5.5.4 The time and cost of contract enforcement in Kenya compared very poorly with neighbouring countries. Contract enforcement has historically been a problem, on account of inefficiencies in the judicial system. This is one of the major impediments in improving firms' access to finance. 5.5.5 Customs systems and procedures have come under particular scrutiny, as they contribute to ex- cessive delays in the processing of imports, exports and transit cargo and present a significant barrier to business activity in Kenya. The costliness of regulation and the associated corruption not only impacts the bottom line of firms that comply, thus lowering the profitability of invest- ment opportunities, but also gives smaller firms an incentive to stay informal. Specific recommendations Simplify and streamline the business registration process and other costly administrative proce- dures for on-going businesses such as sector licensing Simplify and streamline the court procedures for commercial cases. Improve court recording and records management. Increase the resources available to the courts and appoint more Judges and Magistrates specialized in commercial disputes settlement and strengthen alternative mecha- nisms of dispute resolution to ease the pressure on courts In order to reduce regulatory corruption, several general principles can be followed, including: (iv) minimize direct contact between public officials and firms by streamlining of regulations, the elimination or merging of inspections, automating and computerizing procedures, and increasing the use of third-party data and services; (v) rotate regulatory responsibilities, so that the same inspector or auditor is not perma- nently assigned to a firm; and (vi) spread the regulatory process across more than one individual, department, or organiza- tion (such as a reorganization of a regulatory agency along functional lines) so that au- diting, payments, customer service, and so forth are performed by more than one individ- ual. . 76 5.6 Accelerating Improvements in Infrastructure 5.6.1 There has been notable improvement in the quality of some infrastructure services since 2002. Road construction has begun, and there have been increases in the volume and speed of freight traffic. Collaborative projects between donors and the GoK have begun or are at advanced stages of planning. Even so, the speed of implementation of reform in the delivery of infrastructure ser- vices leaves a lot to be desired. 5.6.1.1 The privatization program is in an indeterminate state. Deregulation and privatization of utilities and infrastructure is proceeding at a slow pace and in piecemeal fashion, without a clear man- date or oversight. Privatization plans set out in the IP-ERS envisage private sector participation in water, energy, roads, transport, and communications. Recognizing the importance of a clear mandate for privatization, as well as for consistency, transparency and accountability, the Cabi- net approved and sent to parliament a Privatization Bill. The passage of the Privatization Bill, however, has been severely delayed in Parliament. 5.6.1.2 While widely supported, the Privatization Bill has been criticized on several grounds, including: (i) for developing a process which is not guided by clear objectives; (ii) for allowing too little autonomy of the Privatization Commission while requiring close Cabinet approval of many ac- tions; (iii) for too little public access to information; (iv) for the absence of a competition pol- icy; and (v) for insufficient accountability for the management of the proceeds. Once discussed, it is also not clear that the Bill will pass, not simply because of opposition to privatization itself, but also opposition in some corners to any bill proposed by the government, regardless of its merits. In general, the government as well as individual supervisory boards has the power to privatize individual entities, and to farm out certain services to the private sector. In the absence of the mandate and framework provided by the Privatization Bill, some of these executive ini- tiatives are being delayed, slowed down, or scaled back. 5.6.2 Power. The most critical area of infrastructure reform is the power sector. The GoK plans to dramatically increase power generation and service quality, but the Government expects the en- ergy sector to continue to be plagued by low efficiency, high cost of power and supply character- ized by high incidences of black outs. Generation, transmission and distribution will ultimately be privatized in order to improve management and fund the necessary investments. The GoK plans to sell large stakes in KenGen and KPLC in the next 2 years. 77 5.6.2.1 In preparation for privatization, the GoK plans to un-bundle transmission and distribution of power, enhance corporate governance, the institutional structure, rationalization and streamlin- ing of the regulatory framework, and complete deregulation of the petroleum sub-sector. The principal goals of the reform strategy are a transformation of the industry structure to remove the monopoly power of the KPLC in transmission and distribution, pave the way for more effi- cient development, and create the possibility of a power market characterized by an autonomous open access transmission company, multiple generators, distributors and large customers. The GoK would also like to achieve full integration into the regional power market. 5.6.2.2 The GoK, with World Bank and other donor financing, is commencing a $225 million Energy Sector Recovery Project to support implementation of this new policy framework. In addition to financing equipment investments, the operation will also support implementation of the new regulatory framework, assist in the internal restructuring of KPLC, support PSP in KenGen, and reduce taxes on liquid petroleum gas-related equipment. The responsible agencies are the Min- istry of Energy, Kenya Power and Lighting Company, and KenGen. 5.6.2.3 The project development objectives are (1) to enhance the policy, institutional and regulatory environment for private sector participation in the power sector (2) support efficient expansion of power generation capacity to meet the economy's projected supply deficits by FY06/07 and (3) increase access to electricity in urban and peri-urban areas. This includes the development of an adequate energy policy to achieve the separation of the transmission and distribution busi- nesses by Dec 2006, proper charging for power transmission services and implementation of power purchase agreements between KPLC and KenGen. 5.6.3 Roads. While power is the most critical area of infrastructure reform, other areas need attention as well. It is estimated that 90 per cent of the road network in the country is in disrepair and could take more than Sh130 billion to rehabilitate, plus an additional Sh15 billion annually for maintenance. Several initiatives are underway to coordinate road improvement. The Kenya Roads Board has been established to coordinate redevelopment and maintenance. Private sector repre- sentatives have majority representation on the board. The GoK is moving ahead with the plans set out in the IP-ERS, in particular issuing concessions for the construction and maintenance of major roads to the private sector. A feasibility study for the rehabilitation of the Northern Corri- dor was completed in June 2002/03 and recommends concessioning. A consultant has been hired to manage the tender process, and a roads conference was held in July 2004 to raise awareness in government and among investors. 78 5.6.3.1.1 Numerous major construction projects are also currently underway. The Kisumu-Busia road has been resurfaced. The European Union will help rebuild the Mai Mahiu-Naivasha-Lanet road, perhaps by the end of the year. The World Bank has also provided a Sh17 billion grant for the rehabilitation of the Northern Corridor Highway, which connects the port of Mombassa with Nairobi, Uganda, Rwanda, Burundi, and DRC.. The project is expected to enhance re- gional and domestic trade. 5.6.3.1.2 The recent road levy fund initiative has succeeded in slowing the deterioration of the road network. In the year ending June 2002, 55 per cent of the levy fund went for highways and main roads, 17 per cent was allocated for district roads, 11 per cent was given to local gov- ernment for care of district roads, 14 per cent was allocated to constituencies, and the rest funded the operations of the road board. 5.6.3.2 Yet, at the recent roads conference, the roads effort was criticized for the slow current pace of construction and repair. While the GoK committed to allocate Sh59 billion to the task, stringent procurement procedures introduced by the Finance Minister to avoid contractor corruption were said to slow down progress in building of roads. Further, as noted in the ESW, around 50 per cent of the fuel levy is generated in urban areas, and yet no funding is specifically allocated for maintenance of urban roads. This is both inefficient and inequitable and has a particularly ad- verse impact on private businesses. Also, only 33 per cent of the total revenue derives from heavy commercial vehicles, and yet they are reckoned to be the primary cause of severe road damage. 5.6.4 Rail. Kenya Railways (KR) is now offering passenger service between Nairobi and Mombasa, and has expanded freight traffic by more than 37 per cent since 1996 (although cargo handled by the Kenya Railways, however, declined slightly by 2.1% in the first five months of 2004).18 The system, however, is still only running at about a third of potential freight capacity. KR has also put in place measures to enhance service. These include an agreement with KPA to release more trains for freight business, as well as a seamless train service that operates three times a week be- tween the Port of Mombasa and Kampala to serve the transit market. KR is currently tendering line expansions to foreign investors, and a foreign developer should be selected for a rail link to the Sudan by the fall of 2004. Ultimately there are proposals to break up and privatize the state railway as early as July 2005, although there could be a delay for passage of the Privatization bill. KR recently announced that it will lay off one quarter of its workforce in preparation for the sell- off. 5.6.5 Ports. Under new management that took charge in 1999, performance and service quality have improved. The average container dwell time fell to around 10 days in 2003, a considerable im- provement over the 22-day average of the mid-1990s.19 The Kenya Ports Authority (KPA) has re- ported that the performance of its ports is up 3 per cent in the first six months of 2004. Yet the media has reported that a lack of investment in equipment is contributing to a cargo pile-up prob- lem at the port, and that most of the cargo handling equipment is obsolete. The KPA has an- nounced that it intends to spend more than Sh3 billion on new cranes and speeding, and is plan- ning a Sh1 billion programme to set up its own cargo train service. The coordination with KR on this cargo train service is unclear. 5.6.6 Airports. Administrative barriers and petty corruption appear to have decreased--one airport ground handling company suggested dramatic improvements in such costs and obstructions in the last 18 months. Reductions in corruption led to the reinstatement of air freight traffic to Eldoret 18CBK 2004. 19CEM, 2003. 79 after a year-long government ban (initially imposed because of corruption and smuggling). In or- der to effect further improvements in airport management, a PPIAF study to determine private sector participation (PSP) options in the management and financing airport activities is underway. Airport privatization has been given a boost by the success of Kenya Airways (KA). Since priva- tization and taking on KLM as a strategic partner, KA has become a leading African carrier, and is currently expanding its fleet and European destinations. 5.6.7 Water. GoK water policies and IP-ERS objectives to improve water quality and accessibility for households, and service quality to business have received much less attention. Nationally, the de- livery of water supply and sanitation services in Kenya is fragmented into various regimes. In Nairobi, water management is characterized by low coverage and unreliable service, distribution losses, and poor financial management. The Water Act calls for a uniform service delivery insti- tutional framework to be put in place country-wide, and clarifies the new mechanisms and the role of the various actors within that framework. Most of the new institutions, including local ser- vice boards, have now been established. The World Bank has also proposed a grant project to fo- cus on operationalizing and strengthening new institutions for Nairobi to ensure effective func- tioning. The GOK has also started implementing structural reforms to make water and sewerage services autonomous (including introducing commercial and private sector principles), and mobi- lizing investment for construction and rehabilitation. 5.6.8 ICT. Telecommunications reforms have been proceeding relatively rapidly. Since its introduc- tion, mobile telephony has been expanding fast. There are currently two providers with an overall subscription of more than 2 million. The telecoms regulator--the Communications Commission of Kenya (CCK)--is in the final stages of authorizing a third provider. While cross-subsidization schemes by Kenya Telkom with its subsidiary Safaricom are reported to have kept cellular phone rates high, Safaricom recently announced a decision to lower rates in the near future. For landline services, Kenya Telecom's monopoly over national, long-distance and international telecom services expired on June 30, 2004. The CCK was to name a second national landline telephone service provider, and has evaluated a number of potential (largely foreign) bidders, but in July 2004 announced that the decision had been postponed to an indefinite later date. Kenya Telekom's monopoly on internet service provision also ended in June, and a total of six firms have applied to the CCK for licenses to operate Internet node and backbone services. CCK has not yet announced how it will award the licenses. The regulator is however said to be weighing two options: award the license to only three operators through a tendering process (which could take up to a year to complete); or fully open up the market (licensing applicants on a `first come first served' basis). 5.6.9 World Bank Support. The World Bank's Board approved financing in June 2004 of a total US$263 million (approximately equivalent to 20.5 billion in Kenyan Shillings) for development projects in the transport, agriculture, and water sectors in Kenya. The funding comprises US$207 (KSh. 16.1 billion) for the Northern Corridor Transport Improvement Project, US$40 million (KSh. 3.1 billion) for the first phase of the Kenya Agricultural Productivity Improvement Project and US$15 million (KSh. 1.17 billion) for the Nairobi Water & Sewerage Institutional Restruc- turing Project. The US$15 million (KSh. 1.17 billion) for the water sector, as well as slightly more than one-third (KSh. 1.03 billion) of the amount for agriculture, are non-repayable grants. The balance is repayable over 40 years, which includes a 10-year grace period, at a nominal ad- ministration fee of 0.75 per cent. 5.6.10 The bulk of the funds will go to the "Northern Corridor" project, which involves upgrading 373 kilometers of the Mombasa-Uganda highway and the creation of an independent roads' monitor- ing agency. A sub-component of this project involves upgrading the Jomo Kenyatta and Moi In- ternational Airports to international standards which will allow for direct flights from Kenya to 80 any international destination. An additional element will be used to strengthen the Kenya Civil Aviation Authority and East African School of Aviation, and improve air navigation safety in Kenya. 5.6.11 The KSh. 1.17 billion grant for the water sector will help build an effective governance and insti- tutional structure for the provision of water and sewerage services to the population of Nairobi. This will involve strengthening of the newly-created Nairobi City Water and Sewerage Company (NWSC) and of the Nairobi Water Services Board (NWSB), the autonomous entity that super- vises the performance of the NWSC. A portion of this grant will be used to design the framework for much larger programs in Nairobi and Mombasa, which will include providing water and sani- tation services to low-income urban settlements. Specific recommendations The Government should finalize the privatization strategy and ensure passage of the privatization bill. Fully implement the $225 million, donor-financed power sector project, including the develop- ment of an adequate policy, institutional and regulatory environment; expansion of power gen- eration capacity; and better access to reliable electricity, as described above. Accelerate preparations for the concessioning of major roads and increase the pace of road con- struction and repair, which has been criticized as slow. Road usage tariffs should be drawn up to reflect wear and tear due to different forms of traffic. Vehicle license collections should also be improved to bolster funding for road maintenance. Complete the privatization of the Kenya Railways by means of a long-term concession. Convert the Kenya Ports Authority into a landlord port authority. Private provision and competi- tion should be introduced into all services. Clearance processes and customs procedures should be radically simplified to reduce the scope for discretion and rent seeking and to reduce costs to port users. 5.7 Improving the Public-Private Dialogue 5.7.1 The design and implementation of PSD policy is poorly coordinated across government minis- tries.20 Responsibility for private sector development policy is widely spread across numerous in- stitutions, and specific roles and responsibilities are not well defined. Several ministries, parasta- tals and donors have prepared strategic plans, but these typically focus on their individual role and sphere of influence. Where plans cross institutional spheres, they have usually been devel- oped in isolation from other institutions, and do not have widespread acceptance. 5.7.2 GoK, under the leadership of Ministry of Trade and Industry, has embarked on a PSD Action Plan/strategy process that will specify concrete steps to be taken by the Government of Kenya in the next 12-24 months, with a view to creating practical and quick results for the investment cli- mate improvement essential to the private sector. The Government has established an inter- ministerial and public-private Technical Committee to lead this process and is comprised of Min- istry of Trade and Industry, Ministry of Finance, Ministry of Planning, Ministry of Labour and Attorney General's Chambers, KEPSA, KIPPRA, KAM, and is supported by a core Working Team. The Committee has identified a number of priority areas where reform efforts are particu- 20In this section, we draw upon some of the proposals presented in the recent Growth and Competitiveness report for Kenya. 81 larly required, including sector licensing reform, land administration, crime control, customs and tax administration, legal reform (including revision of the Companies Act), and streamlining of business registration. 5.7.3 Donor projects in private sector development, while historically not closely coordinated, are now increasingly harmonized. A donor coordination group for private sector development meets monthly to promote the exchange of information and project collaboration, and to find possible synergies. 5.7.4 Ultimately, the GoK, the relevant ministries and agencies, private sector representatives, and do- nors will need to work together to agree on priorities, develop appropriate strategies, and design specific implementation actions. Prioritizing and sequencing the recommended reforms will be- come critical at the planning stage, both at the highest levels and within each institution. 5.7.5 The Kenya Association of Manufacturers (KAM), appears to be the strongest and best-organized of Kenya's private-sector representative bodies. It is the undisputed voice of locally-controlled private industry, dominated by Kenyan Asian-owned family businesses . However, its member- ship extends beyond this core, and includes multinationals and service businesses. KAM has 14 industrial sector groupings, including building, foods, pharmaceuticals, mining, paper & board, plastics & rubber, and wood & wood products. It has 8 sub-committees, covering a range of cross-cutting issues, including export development, local authority infrastructure, standards, legal & regulatory and international relations. 5.7.5.1 KAM has taken important initiatives on behalf of its members. For instance, when the AGOA clothing concessions were introduced, KAM took the initiative and set up and staffed its own monitoring unit within the association, to ensure that AGOA rules were being followed. This unit is relied on by Customs, when certifying individual shipments for AGOA concessions. KAM publishes its own comprehensive directory of Kenyan manufacturing. It prepares de- tailed annual budget proposals for consideration by the government. Its approach has gone well beyond protectionism, now having as its motto, "promoting competitive manufacturing in liber- alized markets." 5.7.5.2 Although the Kenyan manufacturing units of multinationals are well represented within KAM, multinationals as a group also have their own separate voice. The Eastern Africa Association (EAA) has its head office in London, but its most active chapters are in Nairobi and Kampala. Its aim is to "facilitate participation in the economic development of Eastern Africa and the In- dian Ocean region by overseas firms, companies and individuals ..." The EAA has a full-time representative in Nairobi, as well as a local Advisory Committee. It acts as a channel of com- munication with government specifically for those businesses controlled outside Kenya. 5.7.6 During the preparation of the Government's Economic Recovery Strategy in early 2003, the new Government made it clear to the private sector that it would welcome the emergence of an apex body, with which it could deal at the highest level. The result was the formation of the Private Sector Alliance [KEPSA]. The Private Sector Forum still exists, and appears to have strong rep- resentation within KEPSA, which currently uses the Forum's offices. 5.7.7 Private-sector respondents report that they have already noticed a positive change in their deal- ings with the new government. Ministers are reportedly more accessible and appear more re- sponsive to private-sector inputs. The new government talks about a relationship based on part- nership, and there are signs that it is starting to do so. For instance, it is reported that there are 82 now regular meetings every two months dealing specifically with taxation and customs issues. Problems are now being discussed more openly, and genuine attempts being made to solve them. Specific Recommendations Support the new inter-ministerial and public-private steering committee on the design and im- plementation of the PSD action plan, including clear measurable indicators for success of these reforms Use existing fora for a public-private dialogue, while allowing KEPSA time to establish its use- fulness to its member organizations. The National Investment Council can also serve as a key player in the dialogue on investment. 83 cibl it pufo y,rotne and -nairt - ild cred tional .e bur zein for on,it sys- nceamrof cessaryen Invs KAM Na eatgits fo SMEs.e oderm aser Need ashcus hem nvei ofyervi es earcot stryi reg placere sc per ills or stumr delrof rofgnidnufd ativ serv stum sisabla an K altern legeth rseir security. of ewvire Sk socsa TLIfo bo tosknab Goht bar landeth restructu mr or cil. ope La ove ent ater stumr rfoep sc of sect odelmphi opecsd tea lish alu stions bo andsnoit restructure unoC ev wireh rem ate den expan . tegin La stumr priv stum Min ners nginai mmercial and co registries.l stum stume rcemofned stum bor Tr or parte in getot,ro an Sugge of stituin ercia stice sharing-n with oarBrob stumrob stumecnan estab sect nanc rystnii Labo n,oi ngi of Policy M train Min erthegto La sect A ali of str Lafoni vatrip-cibl Fi acity Ju Land of ng atio comm of rm ratst of KESP Min nduI Lafoni M Private pu ng.i M ILS. Min capgin nkiaB key Min foin Fifoni M regi Min s ialcnanfi rmfi e entci -idjut facilities of e,etlosbo anthe ctiv stomrofo ratt ghih mework, resetni efficienind state is zer in la ghhi ans,lognimr defid an fra re,u legal an is cu produ earn by ntse t. less ed Levy curri rs. been on-perfon uctrtsarfnid e.r weak by wers,orrob or, po ficiened is Training are andredlo etitopm ve fectaf m on has infrastructud frog an affected ngi Matrix iskc cod an velel s.raey train acities sto ntem nancefirof outdate, oniat ltin costs worke pecially 84 Industrial al resus es rm capd bors veral ital nda rmofnifo Observations/Comm The crisis. Fo an Cap ighen vest ser read rhead framla In fo Dem sp ove leg SMEs ackl Policy - of ainrT ialcna ed ne Policy s teau ratesgnid fin in ills len is . eq Specific Issue adnI Sk/gin ile low, m rmo Wh are syste ref fo ot ality sse Policy of Qugnivorp Acc ng provi nance Area Concern Im Labor Im Fi - - oce- - . - s prycnev Court oce- court spe lien ease cialer Anti- stituni regud ansr imeht d . the angn to erty solni ze mmercialoCeth nya ring line dure force ductnocfo gistrates Ke ecto tionp rdio oprp Comm rein the spin stream ofn proces rni in and of and itonomr prdnanoiat corrur rectr Ma odem izedal firm odescrec fos gulres fo and cou cases. es.t ratiosti claim acity ation. all speci urceso ofy s. esn fylip dgesuJ and rm fore capnehtg on. lopeved prove spuid the res tin ffiocibl system rmo stum itiesnurt sim im pu ref .tn reom regeth inform sma scru rceo lish busienil oni ppoo stum commercial stum mmercial litate courts. stren expand increase stry on .smte stumstruoC enf estab amrest cing for meegan appoint co faci editrcot introduce stum stum .snogire Indu redu sticeuJ in reu res. urt. du GoK Co GoK herotot stum GoK ssiimmoCnoitpurroC of creaseinotsn stum stum of uresd stum stum access stum rs. stum uptrrocfo K Min tio lato KPF GoK pact Go res,ud ceistuJfoni Min proce M masdrocer press GoK cialized GoK and GoK the d . ht an rof pro- wi re-g g.olk ng nos corrup- . ity eht tun ands and dealotd lendi cu rds problema reportin in firsttnatrop .hsKno edti fall lliim0 fo waot lim ugehsis bacgniwo d. im lack too been systems corrupt enceri ands gra ibes.rb are rts is urtoCse neairt- pporoearsn as xpee anlp 10ybt m markeda .e perception efforts ectio custom ordeppui ssensi KACC licb ptabl rattsgia der oricallyt tract ex integrity.dna his to tion ithw steys ce . been has spind bu and cuerews efforehtod an pu rrup in Cour ann etencep eq-l rketam has Act undf unacce Act entm officials com illed ereht CC cials. ineg an Mehtnises omfrserffust undnad affest-r latio ssociateda stijuethfo welton tion skt ca de nancefi no s.nte is KAt offi ch forcene guer ewiv ingk 2002, bu Officers elv tal thingemos anti-cor ercial lac 85 E rem s, lic ecdo to ofgo g.n mmoC sse licbuple as ciary. nksaB rrupoCti fognid lic's SM SMEs qui Since rates. An step Pub high-le An tion Fun acklB owi gr The unerahtoB sin Contract Bu w-levlo Corruption cedures. Pub KPF rrup-oC ousir on se sts ande posemi cola s. Crim onit itiond ad firm andemirCgn tion essi dr rrup Ad Co dis- -ni d a read d ilvci ss to -am d of ga . d-vi -pur r an ordna nyi rut ansalci datyrtap sp an the ions of cor ofs andtn in secto ,ycilope pan ss eslc scd tomat- ilities, ng padnae acce echanismsm escin ffiocibl d-riht ndiieno wer ext; au,sn sib ofe anht ternalint en ers.wol reform arepsn raisesd bat po uatq pair.redna an ade better vehiyv age ns deot ced enmn ive latio respon essirddar traa of fo ss wh rrentuc an roi and for as: ent env concessioningeht truction betw regu zat hearofs ind on es tioom ry alternat as: ticamelbo creasenidnanoi punee us, reom .noi ndepe tlebsi uresd esgie for gani ch well pmo nsocd ger m pror ntemairl nor-fin pacity; zat reg su fo as vel lato ca roa cha hen well pry ofgin atorylu acro ocerp ratst ectingt contact ntue ice, m de of ngt as illb regu syste stre stum tionlu arlulcirt ganir ngiz tate ro process dera pro alternative Paegaruo ng arationsp ce ngsia reor direct eri bro servil its, neration pre aud viabl enc ge creni pa fo zei put ices, orro,ntemrt ent momeht andlan civ electricity. paeht al up ine cratic atization udiclni, tio .sd GoK resoetup onsi streamlinybs erd com servd gulatoryre depa, empl inn . stum doethtnemelpmi tern K power easer Target zat Minim firm ng/i an the ual Im tio ex Keep KPF Exam merito service. Go priveth lly ectjo Fu pr stituin of reliable Accelerate roarjo Inc onsiC -in eb es an of issu will formre 52 rises,yap hum, set infra- als and ent esehtelv hghi, $2a ure cy ruct enci ngi tial pm rce. crimin corrupt . reso ffie bstan quie pace infrast wol Project. su KPF: wen,sre foeth atthn tilitiesufo of of tio slowa area byd .s artsterasronodr ry ling inst artuq rcepep stomehtfoe ue at tripd ons try. atization todepoleved outk un heotd Recovero ed. menevorpmiem ngivilni an,gni creasedin fate.n acbl an ort nt Sect remain an punishd ice coehtnisn privd Billn critical agplsi ann proceeding stom sec ue is certai the ntem train is ant tio latio atizatio nkaBdrl gyernE 86 sector. ts ere gh servil un is gyerne eqrfdna Wo So vest righ Th cau Civ stituin Prive Deregu structure Th ansah the Power is The cost The onillim yr Rail, s, lato ad invest- Ro guerd ents. need, ant provem Power, Ports men im - - fra Im In in ents emvo Accelerating pr structure .d yb - s, overp lord and r- keam )4( im adorn ccessan pe onsi ss. (1) landa to rities,oirp oni be baru baru Railwaysay sperd natdi of toin alogueid sector progre and and,ycilop on ress. oroc could keydna Keneth on.i ityr teavir anse es le. private rolla or prog llectionsoc nanceteinamr data rks ofn tho ro of ess Au lic-pb committee"g DSPno its objectiv tea mmittee.ocgn palair conc rts pua onsi alu atizatio fora easuresm annual teerins" PSD ev ectsetavrip- steeri license fogin Poay lopeved eristniimno on oK fund hicle ve dustniniylal to ive andr the priveth ng-termola collect vise Keneht forg ndent onsi ad ndatemmo ity.r and rec of tho istin indepe (2) itonom viseda crease utes. letepm ert KEPSA au objectpo endatm -Gronodae to nv how In especi ro Co means Co rtop exesU w ance allo Devel form Create recom ilities,b keam) (3 liclybup eatrC group - d der re- tey . uneras is s.daor as areas,n banru ba rtoPnisnte spee orly ,A sg reihtot seaer po ylgnis is MK( ectjo pace, pr po res onitcur rrentuc urnide ofe delayedebdl bill. inc licy eacrinera restetnievi onsi dealinnie veisnop cou provem zatni ang raten way slow tizationav nst imemos would PSD DSP ga che reoms ons ofn ins actnanekat orro established. en sitiv co ador atgn gesi nancetniamrof Pri tatio has be po vyel raileth ed the been ve concessi en project K has ted joram eluf onya eml and GOd secteatv seemhcihw PSA nte us proceediera of catollasi del private imp chr an prirof KE nosahro t.u nt atizeivrpot ng of inpd roe but cer resea zed sect ve 87 .r pe ndiuf sals haerehthguoht .de rnm and etc) an rations, efficiency natdir oni odybx ate goht Num way pai 50 no Propo because Al ope and Design coo Donor harm Ape EAA, Priv wi eedsn edd -in neesi ort creaseinrehtr teanid eatv pri pp fu coord omfr Su to an put sector. -cilbuP ng Dialogue provi Im Private Bibliography African Centre for Economic Growth. 2003. 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