H N P D I S C U S S I O N P A P E R Economics of Tobacco Control Paper No. 6 Past, Current and Future Trends in Tobacco Use G. Emmanuel Guindon and David Boisclair February 2003 TobaccoFreeInitiative WorldHealthOrganization PAST, CURRENT AND FUTURE TRENDS IN TOBACCO USE G. EMMANUEL GUINDON AND DAVID BOISCLAIR MARCH 2003 i Health, Nutrition and Population (HNP) Discussion Paper This series is produced by the Health, Nutrition, and Population Family (HNP) of the World Bank's Human Development Network ( HNP Discussion Paper). The papers in this series aim to provide a vehicle for publishing preliminary and unpolished results on HNP topics to encourage discussion and debate. The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s) and should not be attributed in any manner to the World Bank, to its affiliated organizations or to members of its Board of Executive Directors or the countries they represent. 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The editors for the Economics of Tobacco Control papers are: Joy de Beyer (jdebeyer@worldbank.org), Emmanuel Guindon (guindone@who.int) and Ayda Yurekli (ayurekli@worldbank.org). For free copies of papers in this series please contact the individual author whose name appears on the paper, or one of the editors. Papers are posted on the publications pages of these websites: www.worldbank.org/hnp and www.worldbank.org/tobacco ISBN 1-932126-66-X © 2003 The International Bank for Reconstruction and Development / The World Bank 1818 H Street, NW Washington, DC 20433 All rights reserved. ii Health, Nutrition and Population (HNP) Discussion Paper ECONOMICS OF TOBACCO CONTROL PAPER NO. 6 PAST, CURRENT AND FUTURE TRENDS IN TOBACCO USE G. Emmanuel Guindona and David Boisclair a aTobacco Free Initiative, World Health Organization, Geneva, Switzerland Paper prepared for the World Health Organization's Tobacco Free Initiative Abstract: This paper first estimates the number of tobacco users in 2000 and cigarette consumption from 1970 to 2000 by regions and levels of development and briefly discusses the advantages and disadvantages of estimating tobacco use on the basis of prevalence surveys or aggregate data. Secondly, prevalence (and its associated number of smokers) and cigarette consumption (total and per capita) are projected in the future using several scenarios of changes in tobacco use (prevalence and cigarette consumption), as well as different assumptions about population and income growth. The results show that even if all countries immediately implement a comprehensive set of tobacco control policies, the reduction in the number of tobacco users and the total consumption of cigarettes will be gradual. This should give comfort to farmers and others who fear the impact of tobacco control on their livelihoods. It is however, discouraging news for public health, since it implies that the number of tobacco- attributable deaths will continue to rise for decades to come. Keywords: tobacco, cigarette; consumption; trends; economics of tobacco; economics of tobacco control; smoking; tobacco policy; demand for cigarettes. Disclaimer: The findings, interpretations and conclusions expressed in the paper are entirely those of the authors, and do not represent the views of the World Bank or the World Health Organization, their Executive Directors, or the countries they represent. Correspondence Details: G. Emmanuel Guindon, Tobacco Free Initiative, World Health Organization, Geneva, Switzerland, tel: 41-22-791-1111; fax: 41-22-791-4832; email: guindone@who.int iii iv Table of Contents INTRODUCTION.........................................................................................................................................................1 SOURCES AND METHODS .....................................................................................................................................2 ESTIMATING TOBACCO USE............................................................................................................................2 COMPUTING CONSUMPTION............................................................................................................................3 POPULATION ADJUSTMEN TS...........................................................................................................................4 COMPUTING PREVALENCE...............................................................................................................................5 SCENARIO ANALYSES.........................................................................................................................................5 Prevalence and cigarette consumption ..............................................................................................................5 United States.....................................................................................................................................................6 South Africa......................................................................................................................................................6 Thailand.............................................................................................................................................................6 Population...............................................................................................................................................................7 Income.....................................................................................................................................................................7 RESULTS: PAST, CURRENT AND FUTURE TRENDS IN TOBACCO USE..........................................9 CIGARETTE CONSUMPTION .............................................................................................................................9 PREVALENCE OF TOBACCO USE..................................................................................................................13 DISCUSSION ...............................................................................................................................................................16 DATA QUALITY AND RELIABILITY AND SENSITIVITY OF ASSUMPTIONS...............................16 STRONG TOBACCO CONTROL MEASURES WILL NOT LEAD TO MASSIVE JOB LOSSES AND POVERTY......................................................................................................................................................18 CONCLUSION.............................................................................................................................................................19 REFERENCES .............................................................................................................................................................45 TABLES TABLE 1: PER CAPITA CIGARETTE CONSUMPTION, 1970-2000, BY WHO REGIONS AND LEVELS OF DEVELOPMENT........................................................................................................................10 TABLE 2: TOTAL CIGARETTE CONSUMPTION, 1970-2000, BY WHO REGIONS AND LEVELS OF DEVELOPMENT (MILLION STICKS)...........................................................................................................11 TABLE 3: TOBACCO USE PREVALENCE AND NUMBER OF SMOKERS, 2000 BY WHO REGIONS AND LEVELS OF DEVELOPMENT; (% OF THE POPULATION AGED 15 YEARS AND OLDER AND THOUSAND SMOKERS) .........................................................................................................................14 TABLE 4: NUMBER OF SMOKERS: TOBACCO USE PREVALENCE SCENARIOS (+2% INCOME, MEDIUM POPULATION VARIANT; THOUSANDS) ..................................................................................15 FIGURES FIGURE 1: TOTAL CIGA RETTE CONSUMPTION, 1970-2000, PER CAPITA CONSUMPTION SCENARIOS (2% ANNUAL INCOME INCREASE, MEDIUM VARIANT POPULATION PROJECTION) .....................................................................................................................................................12 FIGURE 2: TOTAL CIGA RETTE CONSUMPTION, 1970-2025, BY LEVELS OF HUMAN DEVELOPMENT (2% ANNUAL INCOME INCREASE, MEDIUM VARIANT POPULATION PROJECTION) .....................................................................................................................................................13 FIGURE 3: TOTAL CIGA RETTE CONSUMPTION, 1970-2025 (2% ANNUAL INCOME INCREASE, LOW, MEDIUM, HIGH VARIANT POPULATION PROJECTION)..........................................................17 FIGURE 4: TOTAL CIGA RETTE CONSUMPTION, 1970-2025, SENSITIVITY OF INCOME ASSUMPTIONS (MEDIUM VARIANT POPULATION PROJECTION) .................................................17 v APPENDICES Appendix 1: Cigarette production 1970-2000, selected years (million pieces) .................20 Appendix 2: Cigarette imports 1970-2000, selected years (metric tons/million pieces)................................................................................................................................23 Appendix 3: Cigarette exports 1970-2000, selected years (metric tons/million pieces) ..............................................................................................................................26 Appendix 4: Sources, cigarette production, imports, exports 1970-2000 selected years .........................................................................................................29 Appendix 5: Total cigarette consumption estimates 1970-2000, selected years (3-year moving average, million pieces)................................................................37 Appendix 6: Per capita cigarette consumption estimates 1970-2000, selected years (3-year moving average)...............................................................................40 vi FOREWORD In 1999, the World Bank published "Curbing the Epidemic: governments and the economics of tobacco control", which summarizes the trends in global tobacco use and the resulting immense and growing burden of disease and premature death. By 1999, there were already 4 million deaths from tobacco each year. This number is projected to grow to 10 million per year by 2030, given present trends in tobacco consumption. Already about half of these deaths are in high-income countries, but recent and continued increases in tobacco use in the developing world is causing the tobacco-related burden to shift increasingly to low- and middle-income countries. By 2030, seven of every ten tobacco-attributable deaths will be in developing countries. "Curbing the Epidemic" also summarizes the evidence on the policies and interventions that have proved to be effective and cost-effective in reducing tobacco use in countries around the world. Raising taxes to increase the price of tobacco products is the the most effective way to reduce tobacco use, and the single most cost-effective intervention. It is also the most effective way to persuade young people to quit or not take up smoking. This is because young people, like others with low incomes, tend to be highly sensitive to price increases. Why are these proven cost effective tobacco control measures not adopted or implemented more strongly by governments? Many governments hesitate to act decisively to reduce tobacco use because they fear that tax increases and other tobacco control measures might harm the economy by reducing the economic benefits their country gains from growing, processing, manufacturing, exporting and taxing tobacco. The argument that tobacco contributes revenues, jobs and incomes is a formidable barrier to tobacco control in many countries. Are these fears supported by the facts? In fact, these fears turn out to be largely unfounded when the data and evidence on the economics of tobacco and tobacco control are examined. A team of about 30 internationally recognized experts in economics, epidemiology and other relevant disciplines who contributed to the analysis presented in "Curbing the Epidemic" reviewed a large body of existing evidence. The team concluded that in most countries tobacco control would not lead to a net loss of jobs and could, in many circumstances actually generate new jobs. Tax increases would increase (not decrease) total tax revenues, even if cigarette smuggling increased to some extent. Furthermore, the evidence shows that cigarette smuggling is caused at least as much by general corruption as by high tobacco product tax and price differentials. The team recommended that governments not forego the benefits of tobacco tax increases because they feared the possible impact on smuggling. Rather, they should act to deter, detect and punish smuggling. Much of the evidence presented and summarized in "Curbing the Epidemic" was from high-income countries. However, the main battleground against tobacco use is now in low- and middle-income countries. If needless disease and millions of premature deaths are to be prevented, then it is crucial that developing counties raise tobacco taxes, vii introduce comprehensive bans on advertising and promotion of tobacco products, ban smoking in public places, inform their citizens about the harm that tobacco causes and the benefits of quitting, and provide advice and support to help people quit. In talking to policy-makers in developing countries, it became clear there was a great need for country-specific analytic work to provide a basis for policy making within a sound economic framework. The World Bank and WHO's Tobacco Free Initiative (as well as several other organizations, acting in partnership or independently) began to commission and support analysis of the economics of tobacco and tobacco control in many countries around the world. The report presented in this paper makes a valuable contribution to our understanding of the issues and likely economic impact of tobacco control. Our hope is that the information, analysis and recommendations contained herein will prove helpful to policy makers and result in stronger policies to reduce the unnecessary harm caused by tobacco use. Joy de Beyer Tobacco Control Coordinator Health, Nutrition and Population World Bank viii ACKNOWLEDGMENTS The authors would like to thank Joy de Beyer for her comments, Gael Kernen and Gisele Biyoo for their formatting assistance and Jean-Philippe Meloche for his formidable programming skills. The authors alone are responsible for the remaining errors in this paper. The authors are also grateful to the World Bank for publishing the report as an HNP Discussion Paper. ix x INTRODUCTION There is little debate surrounding the health hazards associated with the use of tobacco products. Evidence implicating tobacco as a potential health hazard emerged in the early 1950s (Doll and Hill 1954, 1956; Wynder and Graham 1950). There are now more than 70,000 scientific articles that link smoking with a pervasive range of health problems (USDHHS 1994). Recent epidemiological studies performed in China summarize the magnitude of the tobacco epidemic. If current smoking patterns persist, about 100 million of the 300 million Chinese males now aged 0-29 will die as a result of tobacco use (Liu et al. 1998). Currently, an estimated 4.9 million deaths per year are caused by tobacco. Without further action, it is predicted that in 2020 the mortality burden attributable to tobacco will nearly double (WHO 2002). However, there are signs of hope: effective policies and interventions exist that can make a difference. The World Health Organization recently examined the cost-effectiveness of various tobacco control interventions for population health through the impact of reduced tobacco use on the incidence of cardiovascular disease, respiratory disease and various forms of cancer (WHO 2002). The combination of higher tobacco prices through taxation, comprehensive bans on advertising and promotion and information campaigns in the form of package and labelling measures or counter-advertising was found to be affordable and cost-effective in the majority of subregions examined. Including smoking restrictions in public places resulted in even greater improvements in health, albeit at a higher cost. These results tally with an influential World Bank report that examined the effectiveness of an array of interventions and concluded that both price (taxes) and non- price (advertising bans, information campaigns, smoking restrictions, etc.) measures can reduce the demand for cigarettes (World Bank 1999). Despite the increasing evidence that tobacco use kills, many governments still fail to act because of fears that tobacco control interventions might hurt their country's economic development. The World Bank examined concerns such as loss of employment, tax revenues and export earnings and concluded that tobacco control policies could bring unprecedented health benefits without harming economies. This paper will attempt to show that even if all countries immediately implement a comprehensive set of tobacco control policies, the reduction in the number of tobacco users and the total consumption of cigarettes will be gradual at best. To this end, this paper first estimates the number of tobacco users in 2000 as well as cigarette consumption from 1970 to 2000 by WHO regions and levels of development. The paper briefly discusses the advantages and disadvantages of estimating tobacco use on the basis of prevalence surveys or aggregate data. Secondly, prevalence (and its associated number of smokers) and cigarette consumption (total and per capita) are projected in the future using several scenarios of changes in tobacco use (prevalence and cigarette consumption), population increases and changes in income levels. 1 SOURCES AND METHODS Estimating tobacco use Estimates of consumption and prevalence of use of tobacco products can originate from various types of data. First, they can be based on (self-reported) tobacco use prevalence surveys. Prevalence surveys provide information on the proportion of tobacco users in a given population. Prevalence data combined with tobacco use intensity data can also yield total consumption estimates. Secondly, consumption can be derived from aggregate production and trade statistics. Production plus imports minus exports will yield `apparent' consumption estimates. Thirdly, consumption can also be estimated from national cigarette sales data based on tax records. Prevalence surveys can provide important insights into patterns of ­ and changes in ­ consumption according to gender, age, income and education (Warner 1977). They also allow distinguishing between a change in the number of smokers and changes in consumption per smoker (Warner 1977). On the other hand, consumption data (the number of cigarettes consumed) based on surveys suffer from significant underreporting (Hatziandreu et al. 1989; Jackson and Beaglehole 1985). Moreover, it has been argued that increased awareness of the health consequences associated with tobacco use and the increased social undesirability of tobacco use may lead to higher underreporting of cigarette consumption, making trend data less reliable (Warner 1978). Another potential inconvenience is the infrequent unavailability of trend data. The subjective nature of surveys and differences in survey methodology (questions, definitions, languages, etc.) also make comparison of estimates across countries difficult. Aggregate production and trade statistics are objective data that eliminate the underreporting problem inherent in data based on subjective survey responses (Warner 1977). These data are also readily available across time and countries. This feature, as well as the availability of centralized data sources using common methodologies, allows for good comparability. However, most of these large-scale tobacco statistics are only available for manufactured cigarettes. Although about 80 percent of all tobacco consumed in the world is in the form of cigarettes (Chapman and Lazarus 1992), other forms of tobacco use are significant in some countries such as India and Norway (Chapman 1992). The major problem with aggregate data is perhaps that, unlike prevalence survey-based data, they cannot be used for analysing changes in gender, age, income and education distribution and they do not permit a distinction between a change in the number of smokers and changes in consumption per smoker (Warner 1977). Other important problems include illicit trade in cigarettes, which may lead to under- or over-estimating consumption of tobacco products (WHO 1998)1, as well as the question of measurement 1`Apparent' consumption will under-estimate true consumption in countries where tobacco products are illegally imported and consumed while it will over-estimate true consumption where tobacco products are illegally exported to another country. 2 units yielding diverging trends2 and biased point estimates3. Production data can be used at the global level as a proxy for world consumption. Production data will be a poor proxy for consumption in most countries, but as world exports must equal world imports, aggregating cigarette production for all countries would do away with the problems associated with smuggling and attenuate the problems associated with measurement units. Unfortunately, because of unequal data availability through time, adding all production data points in a particular year can lead to severe underestimation. The problem of stockpiling may also emerge, as not all cigarettes will be consumed in the year they are produced or imported. If this stockpiling is significant it may bias consumption estimates. However, stockpiling is unlikely to affect trends since it is not likely to vary from year to year ­ although tobacco companies have been known to time cigarette stockpiling against health measures so that they appear less effective (WHO 1998). Finally, transient populations will affect aggregate trade and production statistics to a varying degree: `apparent' consumption will over-estimate true consumption in countries with large transient populations (for example tourists or military) and small indigenous populations such as Malta and the Maldives. Sales data based on tax records are also aggregate data and hence present the same general advantages and disadvantages as those described for production and trade statistics. It should be noted, however, that sales data are not as readily available across countries and are not available in centralized databases. On the other hand, they do not suffer from the limitations associated with measuring and reporting units or stockpiling. They also present the advantage (unlike estimates obtained from trade and production statistics) of yielding consumption estimates that exclude duty-free sales4, most of which are to non-residents and are not consumed in the country. Computing consumption Due mainly to data availability issues, and bearing in mind the important advantages and disadvantages presented above, the next section presents cigarette consumption figures calculated using production, import and export statistics found in various databases and 2Trade and production data can be reported in weight or in physical units. In countries where cigarette weights have not remained constant over time, cigarette consumption expressed in units and in weight can show diverging trends. For example, Australian cigarettes became progressively lighter in the late 1980s. When expressed in grams per capita, cigarette consumption in Australia fell by 4.9 percent between 1986 and 1990 while it increased by 5 percent when expressed in units (Chapman 1992). 3Trade and production statistics for an individual country can also be reported in different units. For example, manufactured cigarette imports and exports are often reported in metric tons while production is expressed in units. When this is the case, it can be assumed in the calculations that one cigarette weighs one gram. But this assumption may not hold and thus bias consumption estimates. The direction of the bias will depend on two factors: (1) the true `conversion factor', and (2) the respective size of imports and exports. For example if, in a country where production statistics are expressed in units while trade statistics are expressed in metric tons one cigarette weighs 0.8 gram, assuming that one gram of cigarette equals one cigarette will over-estimate true consumption if the country is a net importer of cigarettes, and under- estimate it if the country is a net exporter. 4Sales statistics are typically based on tax receipts. 3 publications. The best source for each country's indicators is selected according to the following process. Production and trade data from these trade and production data sources are compared and contrasted: ERC Statistics International, FAOStat Statistical databases, Official Statistics of the countries of the Commonwealth of Independent States (CIS), United Nations Industrial Commodity Production Statistics Database, Commodity Trade Statistics Data Base (COMTRADE), and United States Department of Agriculture databases (USDA). Where they are available, data from national sources are also considered. When the data are identical or very similar, the most complete source (the one with the most data points) is used. On some occasions similar data from different sources have been merged to expand data coverage. When data from any of the sources conflict with another, they are compared and contrasted with data reported in Tobacco or Health: A Global Status Report, the Pan American Health Organization's Tobacco or Health: Status in the Americas, Market Tracking International, OECD Health Data 2000, and the International Tobacco Guide. If no consensus emerges, the data are not reported. On rare occasions, cigarette consumption calculations may yield unrealistic estimates (for instance, negative consumption numbers). These estimates are also not reported. For the purposes of the calculations, when cigarette production and trade are expressed in weight, one gramme in weight is converted to one cigarette stick, with the results presented above. United Nations databases use international classifications (albeit different ones) to group commodities. The following commodity codes are used to identify the relevant data: United Nations Industrial Commodity Production Statistics Database. International Standard Industrial Classification of all Economic Activities (Revision 2): Code 3140-07. United Nations Statistics Division. Commodity Trade Statistics Data Base (COMTRADE); Standard International Trade Classification (Revision 2): Code 1222. FAO Cigarettes (includes cigarettes of tobacco substitutes): Code 0828. The formula used for computing consumption is the following: Total cigarette consumption = Production + Imports - Exports Regional and global estimates of past cigarette consumption are derived assuming that countries for which data are unavailable for a particular year or number of years experience a pattern of consumption equal to that of the region and the world over that period. Population adjustments Total cigarette consumption can be useful to gauge the size of a tobacco market, but it does not allow for comparison across time and across countries. To achieve the latter, total cigarette consumption or sales can be weighted by population in order to provide an indicator of individual consumption, usually by dividing total cigarette consumption by the population aged 15 years and above. The age group 0-14 is normally omitted because of its limited contribution to tobacco use (Chapman 1992). However, differences between 4 countries in demographic distribution and tobacco use prevalence in the 10-20 age group can be significant and diminish comparability. In the present case the formula used to obtain per capita consumption figures is simply: Per capita cigarette consumption = (Production + Imports - Exports) / (Population 15+) where the population figures are taken from the United Nations Population Division. This formula is applied to observations where consumption and population data are available, and then weighted to obtain the group estimates presented below. Computing prevalence In order to obtain prevalence figures, 131 male and 131 female prevalence estimates taken from the American Cancer Society prevalence database, the WHO EURO tobacco control database and the WHO EMRO country profiles on tobacco control and covering about 95 percent of the world's population were used to produce regional estimates.5 These regional estimates of smoking prevalence are derived under the assumption that all studies report current daily and occasional smoking among persons aged 15 years and older, and that they reflect the smoking status of the populations in 2000. The gender- specific prevalence estimates for each country are weighted by the size of the male and female populations aged 15 years and above. The values are averaged so as to obtain weighted adult prevalence estimates by geographical or economic regions. Each of these is assumed to apply to the entire grouping. The number of smokers in each group is estimated by multiplying the adult prevalence by the total population aged 15 years and above. Scenario analyses Prevalence (and its associated number of smokers) and cigarette consumption (total and per capita) are projected in the future using several scenarios of changes in tobacco use (prevalence and consumption), population increases and changes in income levels. The starting point for these projections is the year 2000. Prevalence and cigarette consumption Many jurisdictions of all development levels and geographical locations have implemented comprehensive tobacco control policies, some of them with great success. It is assumed here that all countries and areas implement effective and comprehensive tobacco control programmes starting in 2000, and achieve results similar to those obtained by the following countries or states, which have been among the most successful in this regard. 5For more information on the methodology used by the American Cancer Society, please see Corrao et al. 2000a and Corrao et al. 2000b. 5 United States tobacco control experiences over the past decade. Bitton et al. (2001), using data from state and federal sources, estimate the average rate of decline in prevalence in the four states. The authors find that on average the four programmes produced a rate of decline in adult prevalence of 1 percent a year over their duration. With respect to annual per capita cigarette consumption, California experienced dramatic declines The US States of California, Massachusetts, Arizona and Oregon have had highly successful (60%) between 1988 and 2001, while consumption decreased by 34 percent in the whole of the United States (including California). In other words, since 1988 per capita cigarette consumption in California has been declining at an average annual rate of about 6.7 percent (3.2 percent in the United States) (California Department of Health Services 2002). South Africa Within a relatively short period of time the South African government enacted one of the most comprehensive packages of tobacco control policies. This included large tax increases, tobacco advertising and sponsorship bans, a ban on smoking in all public places (including workplaces) and a ban on the sale of tobacco to minors. Between 1991 and 2001, total per capita cigarette consumption fell by more than 40 percent. Per capita cigarette consumption fell 11 years in a row at an average annual rate of 5.7 percent. Similarly, smoking rates have fallen in all age groups. Adult prevalence has decreased at an average annual rate of around 1.8 percent, from 33 percent in the early 1990s to 27 percent in 2001 (Van Walbeek, forthcoming). Thailand In 1992, partly as a response to the multinationals entering the market, the Thai government enacted some of the strictest tobacco control policies around. As a result, smoking prevalence among males and females fell from 46.6 and 3.8 percent in 1991 to 38.4 and 2.4 percent respectively in 1999. On average, total prevalence fell by about 3 percent per year (Vateesatokit et al. 2000). During the same period per capita cigarette consumption fell by close to 25 percent, or about 2.9 percent per year. In order to examine the potential impact of implementing comprehensive tobacco control programmes on future numbers of tobacco users and consumption of tobacco products, three scenarios are retained for both variables. The first scenario is that of constant prevalence rates or consumption patterns, which is also the "baseline" scenario. The other two scenarios reflect different degrees of optimism, given the results obtained by the countries presented above. The three scenarios are thus the following: Prevalence: no change, -1.0 percent per year, and -3.0 percent per year. Per capita consumption: no change, -3.0 percent per year, and -6.0 percent per year. 6 Population The low, medium and high variants of projected population from the United Nations World Population Prospects (2000 Revision) are used to project the number of smokers as well as total cigarette consumption to 2010 and 2025. The medium variant is used as the baseline. We report these two years mainly because of 1) the relative proximity of 2010, which nevertheless allows some of the cumulated reduction effect to kick in; and 2) the period up until 2025 is likely to be of greatest interest to the current generation of tobacco workers and growers, because by 2025 a large proportion of them will no longer be involved in the tobacco sector because of death or retirement. We then multiply these population projections by our own projections of per capita consumption and prevalence rates. Income It is generally accepted that world income (GDP) per capita will continue to grow over the next decades. This might affect tobacco use and consumption insofar as these variables have an income elasticity different from zero, which is certainly the case, as argued below. The world real GDP has been growing at an average annual rate of more than 3 percent over the past 30 years (IMF 2002). When looking at real GDP per capita however, the average for the period 1970-2001 was about one percentage point lower due to population growth. Since the two exhibit a similarly upward trend, it does not seem unreasonable to assume that the latter will grow at an average annual rate of 2 percent in the next two decades, the IMF itself predicting the trend to be above 3 percent by 2007. In particular, the latest detailed projections of total GDP growth published by the IMF stood, for 2003, at 2.5 percent for the industrialized world and 5.2 percent for developing countries. Thus, as our baseline we retain the conservative assumption of an average annual growth rate of the real GDP per capita of 2 percent. This assumption is applied evenly to the regional and development groupings. To test the sensitivity of this assumption, we also use an average annual growth rate of the real GDP per capita of 5 percent. Because aggregate data are used here, only the income elasticity of total cigarette consumption should be of interest to determine the final impact that the above changes in income will have on cigarette consumption. The hypothesis we make here will be crucial to determine the impact of a change in income on tobacco consumption, since it is the income elasticity that describes the link between a change in income and a change in consumption. This income elasticity will thus be combined with the assumption on the evolution of per capita income to predict the future number of smokers and total cigarette consumption. As Gallet and List report, estimates of income elasticity of cigarette demand vary widely, ranging from -0.80 to 3.03 in their meta-analysis (Gallet and List forthcoming). The 86 articles they review find a mean income elasticity of 0.42 from a total of 375 different estimates, the vast majority of which were obtained at country level. In a brief review of 7 the literature pertaining to developing countries, as defined by the classification used by the United Nations, WHO finds estimates ranging from 0.11 to 2.00. The review of 19 articles from 15 countries yields an average income elasticity of approximately 0.69 (WHO, forthcoming). In any case, income elasticity of cigarette demand is clearly different from zero. Thus it seems reasonable to assume, as our baseline, a conservative income elasticity of per capita cigarette demand of 0.3 throughout the projection period, translating the 2 percent income growth into a 0.6 percent annual growth in per capita consumption. Awareness of the dangers of tobacco use may well rise over time as a result of the comprehensive programmes assumed to be implemented in our different scenarios, but we work under the assumption that this income elasticity of 0.3 will be the mean elasticity over the period. We also use an income elasticity of 0.75 to test the sensitivity of our assumption. A further assumption we need to make for the prevalence analysis is on the portion of the income elasticity that comes from a change in the number of smokers (participation income elasticity), as opposed to a change in the consumption of existing smokers (consumption income elasticity). A participation elasticity of 0.15 which translates into an income effect of 0.3 percent of annual growth in prevalence is assumed. One should note that the assumptions on the evolution and effect of income are made independently from the ones on the evolution of prevalence and per capita consumption, even though they will evidently affect these two variables, as just described. That is to say, we first assume that, for instance, prevalence will decrease by 1.0 percent per year ceteris paribus ­ all other things being equal (including income). Then we add an income effect derived from a 2 percent annual growth in GDP per capita, which translates in a 0.3 percent increase in prevalence. Thus we assume that the 1.0 percent annual decrease in prevalence we use is the "real" effect of the tobacco control programmes implemented, i.e. it is net of income effects. This means that our assumptions are even more conservative, because in our analysis the income effect pulls prevalence (and per capita consumption) in the direction opposite to the tobacco control scenarios, whereas the "real situations" described above as justifications for the latter already included this small counter-effect ­ and thereby under-estimate the total effect of the policies alone. 8 RESULTS: PAST, CURRENT AND FUTURE TRENDS IN TOBACCO USE6 Cigarette consumption Tables 1 and 2 show per capita and total cigarette consumption by WHO regions and levels of development.7 As Table 1 shows, the world per capita consumption of cigarettes increased until the middle of the 1980s and has remained fairly stable since the mid-1990s, after a slight decrease. Per capita cigarette consumption peaked in 1986 at 1590 pieces and then decreased at an average rate of about 1.2 percent per year. However Table 2 indicates that ­ due mainly to population growth ­ the world total cigarette consumption has continued to increase over the past 30 years after a short slowdown and a light dip in the early 1990s. In the interest of transparency, Appendix A, B and C present cigarette production, imports and exports by country for the years 1970, 1980, 1990 and 1995 to 2000. Appendix D presents the source of each individual country data point. Appendix E and F present total and per capita cigarette consumption trends by country. It is clear from Table 1 that the WHO regions with the highest per capita cigarette consumption are Europe and the Western Pacific. The latter switched position with the Americas over the past three decades, most likely around the late 1980s. The Eastern Mediterranean and Africa, with rather poor and very poor data availability respectively, seem to have experienced a sizeable drop in the late 1980s and early 1990s, followed by a slight increase and relative stability thereafter8. The situation in South-East Asia, where a large proportion of the population is known to use smokeless tobacco, has deteriorated in phases since the 1970s with regard to cigarettes. 6The estimates of prevalence and consumption in this section are not, and should not be considered "official" WHO or World Bank data. 7It is important to note that there is no established convention for the designation of "developed" and "developing" countries or areas in the United Nations system. In this paper, Japan, Canada, the United States, Australia, New Zealand and Western Europe are considered "developed" while "countries in transition from centrally planned to market economies" are labeled "transition". All other countries fall into the "developing" category. 8The situation of Africa, in particular, should be interpreted cautiously in light of the very limited data available. 9 Table 1: Per capita cigarette consumption, 1970-2000, by WHO regions and levels of development 1970 1975 1980 1985 1990 1995 1996 1997 1998 1999 2000 WHO Regions African region 593 677 712 716 534 421 484 480 557 570 595 Pop. Covered 51.8% 52.6% 50.5% 48.4% 64.1% 67.4% 49.9% 45.1% 33.3% 29.0% 25.6% Nb. of countries 17 20 20 19 17 17 15 14 10 8 7 Region of the Americas 2,613 2,700 2,561 2,270 1,884 1,582 1,554 1,518 1,454 1,402 1,408 Pop. Covered 92.2% 90.5% 93.4% 92.0% 92.7% 94.5% 91.9% 89.5% 90.5% 91.0% 86.9% Nb. of countries 21 19 21 20 19 19 17 13 14 15 12 Eastern Mediterranean region 747 931 1,088 1,138 811 836 855 866 899 884 878 Pop. Covered 64.9% 71.4% 73.3% 66.3% 76.0% 75.4% 75.3% 74.3% 56.3% 56.2% 56.1% Nb. of countries 7 8 9 7 9 9 9 8 6 6 6 European region 2,272 2,421 2,363 2,347 2,144 2,116 1,948 1,952 2,030 2,063 2,058 Pop. Covered 96.4% 96.9% 92.4% 96.9% 96.9% 69.9% 95.1% 94.6% 92.2% 86.0% 85.9% Nb. of countries 25 26 25 25 25 30 36 35 35 35 35 South-East Asia region 285 296 351 348 322 357 369 374 369 361 355 Pop. Covered 94.9% 94.9% 95.0% 95.0% 95.0% 95.0% 95.1% 95.1% 95.1% 95.1% 95.2% Nb. of countries 6 6 6 6 6 6 6 6 6 6 6 Western-Pacific region 1,150 1,301 1,569 1,822 2,081 1,979 1,955 1,935 1,906 1,891 1,897 Pop. Covered 95.2% 95.2% 95.3% 95.1% 94.6% 98.2% 98.1% 98.1% 98.1% 98.0% 93.9% Nb. of countries 10 10 10 9 8 9 9 9 9 9 8 Levels of development Developed 2,811 3,021 2,991 2,762 2,484 2,363 2,298 2,254 2,220 2,188 2,148 Pop. Covered 99.4% 99.9% 95.3% 99.9% 99.9% 99.9% 99.9% 99.9% 99.9% 99.9% 99.9% Nb. of countries 22 23 22 22 22 22 22 22 22 22 22 Developing 712 792 960 1,091 1,147 1,081 1,086 1,074 1,076 1,047 1,041 Pop. Covered 87.0% 87.3% 87.9% 86.8% 89.0% 91.0% 88.6% 87.3% 84.5% 82.6% 79.8% Nb. of countries 58 60 63 58 56 57 53 46 41 39 34 Transition 2,300 2,414 2,390 2,403 2,099 2,082 1,851 1,929 2,087 2,168 2,154 Pop. Covered 93.6% 93.6% 93.7% 93.6% 93.5% 35.6% 89.6% 89.8% 84.7% 85.5% 85.5% Nb. of countries 6 6 6 6 6 11 17 17 17 18 18 World 1,410 1,498 1,548 1,575 1,497 1,366 1,376 1,366 1,373 1,355 1,346 Pop. Covered 90.4% 90.6% 89.9% 89.8% 91.3% 87.9% 90.5% 89.5% 87.0% 85.6% 83.4% Nb. of countries 86 89 91 86 84 90 92 85 80 79 74 Sources: See Appendices A, B, C, D, E and F. Despite the fact that per capita consumption remains much higher in the developed world than in developing countries, the trends indicate that the situation in the latter is much worse today than it was 20 or 30 years ago, while the former experienced a continued decline since the 1975 peak. It thus seems fallacious to pretend that tobacco use is a "developed world problem", all the more so because the population of developing countries as a whole is increasing at a much faster pace. Table 2 reflects this reality. It shows that total cigarette consumption has been increasing rapidly in this group as well as in the countries in transition over the past few years, while it has been massively decreasing in the group of developed countries over the past 20 years. 10 Table 2: Total cigarette consumption, 1970-2000, by WHO regions and levels of development (million sticks) 1970 1975 1980 1985 1990 1995 2000 WHO regions African region 91,232 118,237 142,351 165,782 143,670 131,181 212,788 Region of the Americas 859,470 998,786 1,062,204 1,039,338 944,886 868,425 845,337 Eastern Mediterranean region 89,952 128,347 175,647 214,387 176,720 208,379 255,519 European region 1,225,941 1,386,955 1,428,740 1,479,376 1,407,677 1,437,932 1,442,862 South-East Asia region 141,345 166,335 223,919 252,155 263,513 327,672 363,787 Western Pacific region 771,961 977,672 1,339,491 1,780,948 2,270,555 2,326,746 2,392,557 Levels of development Developed 1,462,484 1,671,140 1,755,758 1,705,064 1,604,389 1,588,411 1,496,606 Developing 1,093,936 1,381,203 1,917,390 2,503,841 2,982,487 3,126,193 3,344,068 Transition 580,797 656,639 687,635 715,036 647,541 659,302 703,195 World 3,261,565 3,853,906 4,452,619 5,060,363 5,328,264 5,308,016 5,710,889 Sources: See Appendices A, B, C, D, E and F. Figure 1 presents different scenarios for the future evolution of cigarette consumption, assuming a 2% annual income increase, 0.3 income elasticity and medium variant population projection. The scenarios described above are first applied to the per capita consumption rates, which are then multiplied by the medium variant of the United Nations Population Division's latest projections. It is clear from Figure 1 that the most probable scenario is that of constant per capita cigarette consumption if one uses the past 30 years as a predictor of future trends. A 3 percent annual decrease in per capita cigarette consumption seems very optimistic but perhaps not impossible while a 6 percent annual reduction implies quite a dramatic break in the time series. 11 Figure 1: Total cigarette consumption, 1970-2000, per capita consumption scenarios (2% annual income increase, medium variant population projection) 9,000,000 8,000,000 Constant annual per capita consumption 7,000,000 6,000,000 -1.2% annual per capita consumption sticks 5,000,000 cigarette 4,000,000 -3% annual per capita consumption Million 3,000,000 -6% annual per capita consumption 2,000,000 1,000,000 Projection period - 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 Souce: Authors' projections As Figure 1 suggests, total consumption would only decline if we assume a reduction in per capita consumption. With an unchanged situation in that regard, using today's rate we see a sharp increase in world total cigarette consumption. However it is interesting to note that even with a hard-to-attain reduction of 3% per year of per capita consumption everywhere in the world and starting in 2000, total consumption would be in 2025 ­ more than 20 years from now ­ just below the 1985 level. This illustrates the gradual nature of changes in tobacco consumption and of ensuing modifications in the economy. Figure 2 presents two scenarios of future total cigarette consumption, by levels of human development9, assuming a 2% annual income increase and a medium variant population projection. Trends between 1970 and 2000 clearly show the different rates of growth in cigarette consumption. Total cigarette consumption has steadily increased in countries of medium human development while consumption has steadily decreased in countries of high human development. Consumption in countries at a low level of human development was fairly stable in the 1970s and 1980s but increased quite significantly in the 1990s. Figure 2 clearly shows that a 3 percent annual decrease in per capita cigarette consumption is not an impossibility for high human development countries. However, a 3 percent annual decrease for low and medium human development countries would imply a dramatic change. 9Levels of human development are defined using the UNDP's Human Development Index (HDI). 12 Figure 2: Total cigarette consumption, 1970-2025, by levels of human development (2% annual income increase, medium variant population projection) 500 450 400 350 300 100 = 250 Medium Human Development 1970 200 150 Low Human Development Constant annual per capita consumption 100 High Human Development -3% annual per capita consumption 50 Projection period - 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 Source: Authors' projections Prevalence of tobacco use Table 3 presents tobacco use prevalence and the number of adult smokers by WHO regions and levels of development for the year 2000. Men were almost five times as likely to use tobacco as women, yet more than 18 percent of females were smokers in the Americas and in the European region. These estimates clearly show that most tobacco users reside in developing countries. Out of the 1.22 billion tobacco users, more than 1 billion lived in developing countries or in transitional economies. When presented by human development category, most tobacco users reside in countries that have reached a `medium' level of human development. A quick extrapolation to the year 2003 indicates that there are about 1.3 billion smokers today. 13 Table 3: Tobacco use prevalence and number of smokers, 2000 by WHO regions and levels of development (% of the population aged 15 years and older and thousand smokers) Prevalence Number of tobacco users Male Female Total Male Female Total WHO Regions African region 0.294 0.074 0.184 51,967 13,420 65,387 Pop. Covered 69.1% 67.5% 68.3% Nb. of countries 19 19 Region of the Americas 0.320 0.209 0.263 94,035 64,072 158,107 Pop. Covered 95.1% 95.0% 95.0% Nb. of countries 24 24 Eastern Mediterranean region 0.353 0.061 0.210 52,543 8,670 61,213 Pop. Covered 93.0% 93.0% 93.0% Nb. of countries 19 19 European region 0.449 0.187 0.312 150,628 68,545 219,173 Pop. Covered 97.5% 97.6% 97.6% Nb. of countries 44 44 South-East Asia region 0.481 0.053 0.273 251,699 26,484 278,183 Pop. Covered 98.3% 96.9% 97.6% Nb. of countries 7 6 Western-Pacific region 0.612 0.057 0.338 390,362 35,784 426,146 Pop. Covered 99.9% 100.0% 99.9% Nb. of countries 18 19 Levels of development Developed 0.339 0.212 0.274 114,783 75,891 190,673 Pop. Covered 100.0% 100.0% 100.0% Nb. of countries 24 24 Developing 0.498 0.072 0.289 809,725 114,718 924,443 Pop. covered 94.5% 93.7% 94.1% Nb. of countries 84 84 Transition 0.541 0.139 0.327 82,837 24,153 106,989 Pop. covered 94.6% 95.0% 94.8% Nb. of countries 23 23 Human development High 0.356 0.203 0.278 149,073 89,442 238,515 Pop. covered 96.9% 96.8% 96.8% Nb. of countries 46 46 Medium 0.524 0.077 0.302 747,951 108,326 856,277 Pop. covered 99.1% 98.6% 98.9% Nb. of countries 63 63 Low 0.367 0.067 0.219 87,057 15,865 102,922 Pop. covered 79.7% 77.9% 78.8% Nb. of countries 18 18 World 0.475 0.103 0.289 1,005,927 217,755 1,223,682 Pop. covered 95.3% 94.8% 95.0% Nb. of countries 131 131 Source: Authors' estimates using data from ACS 2003, WHO EMRO 2002 and WHO EURO 2003 14 Table 4: number of smokers: tobacco use prevalence scenarios (+2% income, medium population variant; thousands) -1% annual prevalence 2010 2020 2025 Male Female Total Male Female Total Male Female Total WHO regions African region 63,359 16,137 79,730 77,287 19,480 96,750 85,357 21,438 106,662 Region of the Americas 102,749 70,064 172,846 108,538 74,155 182,765 110,356 75,512 185,972 Eastern Mediterranean region 64,684 10,789 75,754 76,673 12,858 90,032 82,736 13,916 97,294 European region 146,689 66,362 212,730 137,957 62,177 199,677 132,848 59,812 192,178 South-East Asia region 286,327 30,266 318,993 312,907 33,295 349,738 321,962 34,408 360,634 Western Pacific region 414,159 38,138 453,105 416,106 38,626 457,049 412,973 38,514 454,664 Levels of development Developed 113,821 75,036 188,793 110,142 72,636 182,724 107,415 70,926 178,313 Developing 914,829 130,031 1,049,563 995,271 142,129 1,144,508 1,028,454 147,310 1,184,435 Transition 79,831 23,178 102,717 73,260 21,210 94,122 70,053 20,246 89,918 Human Development High 148,858 89,041 237,812 144,590 86,532 231,054 141,289 84,674 225,938 Medium 821,890 119,269 943,602 862,102 125,621 991,807 872,900 127,582 1,005,754 Low 107,634 19,571 128,118 132,731 24,059 157,749 146,815 26,591 174,419 World 1,102,160 238,439 1,342,786 1,168,104 253,074 1,424,167 1,193,198 258,926 1,455,933 Prevalence 44.3% 9.6% 26.9% 41.3% 8.9% 25.1% 39.8% 8.6% 24.2% -2% annual prevalence 2010 2020 2025 Male Female Total Male Female Total Male Female Total WHO regions African region 57,260 14,584 72,055 63,124 15,910 79,020 66,274 16,645 82,816 Region of the Americas 92,858 63,319 156,207 88,648 60,566 149,272 85,684 58,631 144,396 Eastern Mediterranean region 58,458 9,751 68,461 62,622 10,502 73,533 64,239 10,805 75,543 European region 132,568 59,974 192,252 112,676 50,783 163,085 103,148 46,441 149,215 South-East Asia region 258,765 27,352 288,286 255,565 27,193 285,646 249,983 26,716 280,010 Western Pacific region 374,291 34,467 409,488 339,851 31,547 373,292 320,648 29,904 353,018 Levels of development Developed 102,864 67,813 170,619 89,958 59,325 149,238 83,401 55,069 138,449 Developing 826,766 117,514 948,530 812,880 116,083 934,769 798,531 114,377 919,640 Transition 72,146 20,947 92,829 59,834 17,323 76,873 54,392 15,720 69,816 Human Development High 134,528 80,470 214,919 118,093 70,675 188,711 109,702 65,744 175,427 Medium 742,773 107,788 852,769 704,116 102,600 810,051 677,753 99,060 780,905 Low 97,273 17,687 115,786 108,407 19,650 128,840 113,993 20,647 135,426 World 996,064 215,486 1,213,527 954,041 206,696 1,163,178 926,444 201,040 1,130,441 Prevalence 40.0% 8.6% 24.3% 33.7% 7.3% 20.5% 30.9% 6.7% 18.8% Source: Authors' projections Table 4 presents two different scenarios for future tobacco use prevalence. On the assumption that there will be no change in prevalence in the next 10 and 25 years, it is predicted there will be close to 1.45 billion smokers in 2010 and more than 1.7 billion in 15 2025 (nearly 1.5 and 1.9 billion when assuming a modest increase in income per capita). When assuming that prevalence decreases at an annual rate of 1 per cent and a that there is a modest increase in income of 2 percent for the next 10 and 25 years, the total predicted number of smokers still stands at more than 1.3 billion in 2010 and 2025. Even the most optimistic scenario of a reduction in annual prevalence of 2 percent in every country every year for 10 and 25 years in a row, there would still be 1.2 billion smokers in 2010 and more than 1.1 billion in 2025. In other words, if countries achieve successes in excess of the scale experienced in the US states of California, Massachusetts, Arizona and Oregon, and similar to that of South Africa and Thailand, the number of smokers in 10 and 25 years time will be similar to that at the beginning of the century. It is important to note that the 2 per cent scenario would represent a formidable success in the battle to improve health by reducing the prevalence of tobacco use. Sucha sustained decrease would lead to a global prevalence of just 18.8 percent in 2025. DISCUSSION Data quality and reliability and sensitivity of assumptions After presenting such a detailed analysis, it is worth pointing out that a large amount of the data published and available are of poor quality. In particular, the trade data reported by the USDA, UNSD and the FAO sometimes differ widely, as explained above. This makes it important to use the best available data by carrying out the selection process described. There is also a more general argument to make in underscoring what seem like greatly implausible differences. For instance, the USDA's world trade and production estimates in 2000 yield a net trade balance (global exports minus global imports) of 18.9% of all cigarettes traded or 5.3% of all cigarettes produced. Using the same production data but replacing the trade data with the FAO's world figure (the FAO does not publish production data), we find the corresponding figures of 12.3% and 3.7% respectively. Thus the USDA-only estimates of what is often interpreted as the size of the smuggling problem turn out to be 45% to 55% higher, leading to a rather different picture of the situation. And although these discrepancies have been greatest in the second half of the last decade, there have always been smaller (albeit occasionally significant) differences between the two sources over the past 30 years. It is also important to note that country data published by the USDA are often significantly different from those published by other organizations such as the United Nations Statistical Division and the FAO or by national statistical agencies. For a great number of developing countries (e.g. Albania, Algeria, Bangladesh, Bolivia, Ecuador, Jordan, Lebanon and Viet Nam), USDA cigarette production and trade data appear at best to be an extrapolation based on a "guesstimate". For these reasons, it is strongly suggested to use published USDA data for developing countries with great caution. 16 It is also vital to note that when grouped by either WHO regions or levels of development, the calculated estimates depend significantly on the data from large countries such as China and India. As Figure 3 shows, using the different UN projections for future population to 2025 hardly makes a difference in the consumption (and prevalence) projections as they are similar to the year 2010, differing only slightly thereafter. Figure 4 presents five combinations of income elasticities and GDP per capita annual growth rates with two scenarios of per capita consumption. It is apparent from comparing together the constant income assumption with a 2 percent annual GDP per capita increase that the income assumption does not have a significant effect until late in the projection period. However, high income elasticity and GDP per capita growth rates can have a large impact on the predicted future total consumption of cigarettes. Figure 3: Total cigarette consumption, 1970-2025 (2% annual income increase, low, medium, high variant population projection) 350 300 250 -1.2% per capita Constant per capita consumption consumption 200 100 = High population variant 1970 150 -3% annual per capita consumption Low population variant 100 50 Projection period 0 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 Source: Authors' projections 17 Figure 4: Total cigarette consumption, 1970-2025, sensitivity of income assumptions (medium variant population projection) 25,000,000 20,000,000 A Constant per capita consumption A) 5% GDP growth, 0.75 income elasticity B) 2% [5%] GDP growth, 0.75 [0.3] income elasticity 15,000,000 C) 2% GDP Growth, 0.3 income elasticity sticks D) Constant GDP per capita -3.0% per capita consumption cigarette E) 5% GDP growth, 0.75 income elasticity B F) 2% [5%] GDP growth, 0.75 [0.3] income elasticity 10,000,000 E G) 2% GDP Growth, 0.3 income elasticity Million H) Constant GDP per capita C D F 5,000,000 G H Projection period - 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 Source: Authors' projections. Strong tobacco control measures will not lead to massive job losses and poverty From the results presented above it appears that any reduction in the number of smokers and in total tobacco consumption over the next 20 years would be very gradual, even assuming conservative growth of incomes and population and income elasticity, as well as the worldwide, immediate implementation of comprehensive tobacco control measures. This is to say that the current generations of tobacco farmers and workers have nothing to fear from tobacco control, as the shift towards other livelihoods will involve a slow process over several generations. That is not to say that tobacco farmers and workers are not economically vulnerable. Tobacco control is only one of many determinants of the profitability of tobacco farming and manufacturing. Other factors may significantly impact tobacco employment. As Jaffee reports for Malawi for example, the fall in tobacco auction prices in 2000 and 2001 has had adverse consequences for tobacco farmers (particularly smallholders), driving down the crop's profitability by as much as 50% compared with the previous year (Jaffee 2002). The FAO argues that decreased export demand and an influx of inexperienced farmers, leading to a poorer product quality, are the main sources of these changes which took place in a quasi buyers' market (FAO 2001a). Although partially offset by a reduction in production costs, this process may in the absence of reform have led ­ or 18 lead in the future ­ a number of tobacco growers to leave the business, independently of any government intervention in the farming or trading sectors. The FAO has also highlighted a somewhat similar case for China, the world's largest producer and consumer of tobacco products. The Chinese example is also striking because it was the result of a decision made by the public authorities that does not seem to have had unbearable adverse consequences for the sector or the farmers most directly affected. From 1997 to 1999, the area under tobacco cultivation in China dropped by 43% from 2.1 to 1.2 million hectares as a result of a large decrease in the number of farming contracts passed between the State and the farmers. The farmers left out of the tobacco contracting process were forced to shift to other crops in the context of a planned economy; although they disappeared from the tobacco employment statistics within a relatively short period, the switching process was reported to be quick and easy (FAO 2001b). The vulnerability of tobacco farmers and workers should not be dismissed; people who live on the edge of poverty may be very vulnerable to fairly small movements in crop prices. However, the catastrophic scenarios that are predicted occasionally in the media or propagated by the tobacco industry are pure fiction. For instance, the Framework Convention on Tobacco Control negotiated under the auspices of WHO does not, as it has been reported, "relate to the survival of millions of people whose livelihood is derived from tobacco farming" (Africa News Service, 2 October 2000). Even the most optimistic ­and very unlikely­ tobacco control scenario of a 3% per capita reduction in cigarette consumption every year for 25 years would merely bring total consumption of cigarettes to that of the early 1980s. It is also important to note that money no longer spent on tobacco will not disappear from the economy but will be spent on other goods and services. This increased demand for other goods and services will in turn create new employment opportunities. Thus for the foreseeable future, irrespective of tobacco control scenarios, tobacco production can and will remain an important part of some countries' economies. Hence strong tobacco policies should be implemented without delay; fears that farmers and workers may suffer from the direct effects of these policies are unwarranted. CONCLUSION The detailed cigarette consumption and prevalence estimates presented above demonstrate the urgency of the situation. Today, almost 1.3 billion adults use tobacco. If prevalence and per capita cigarette consumption remain unchanged, we predict that there will be close to 1.9 billion users in 2025 consuming more than 9 trillion cigarettes. As stressed by Gro Harlem Brundtland, Director-General of WHO, the reason to control the tobacco epidemic is its impact on health, poverty and development (Brundtland 2003). Currently, 4.9 million people die every year because of tobacco use. Without further action, it is predicted that the burden attributed to tobacco use will almost double by 2020 (WHO 2002). Further, since the impact of future consumption will lead to excess deaths well beyond 2020, action today could reap one of the greatest prevention dividends in public health history. The impact of tobacco control policies on the future of tobacco 19 farmers and workers should no longer be an acceptable excuse to prevent the implementation of comprehensive tobacco control policies that can save millions of lives. 20 APPENDICES Appendix 1: Cigarette production 1970-2000, selected years (million pieces) 1970 1980 1990 1995 1996 1997 1998 1999 2000 Afghanistan ... ... ... ... ... ... ... ... ... Albania ... 4,950 4,947 685 483 414 764 63 62 Algeria 6,063 15,444 18,775 16,419 15,840 15,543 17,891 18,324 17,058 Andorra ... ... ... ... ... ... ... ... ... Angola 2,016 ... ... ... ... ... ... ... ... Antigua and Barbuda ... ... ... ... ... ... ... ... ... Argentina 30,219 37,972 33,472 42,009 41,208 42,100 42,200 42,500 40,400 Armenia ... 9,776 8,102 1,043 152 815 2,490 3,132 2,096 Australia 26,848 35,185 35,575 31,271 30,767 30,035 29,939 28,018 23,576 Austria 12,617 15,260 14,961 16,297 19,366 19,973 22,512 24,370 25,400 Azerbaijan ... 7,673 6,520 1,970 788 800 200 416 2,126 Bahamas ... ... ... ... ... ... ... ... ... Bahrain ... ... ... ... ... ... ... ... ... Bangladesh 17,787 13,830 12,289 17,379 16,222 18,601 19,889 19,558 19,732 Barbados 162 224 135 65 ... ... ... ... ... Belarus ... 19,229 16,399 6,228 6,267 6,787 7,296 9,259 10,356 Belgium 19,727 28,167 27,758 18,826 17,471 18,061 17,519 14,712 12,625 Belize 80 63 101 95 79 88 94 91 84 Benin ... ... ... ... ... ... ... ... ... Bhutan ... ... ... ... ... ... ... ... ... Bolivia 730 ... 97 170 ... ... ... ... ... Bosnia and Herzegovina ... ... 9,208 1,500 2,000 3,032 3,717 4,945 4,670 Botswana ... ... ... ... ... ... ... ... ... Brazil 73,000 142,700 173,987 173,694 182,300 182,800 170,000 111,400 104,900 Brunei Darussalam ... ... ... ... ... ... ... ... ... Bulgaria 55,082 85,214 75,812 74,603 57,238 43,315 33,181 25,715 26,681 Burkina Faso ... 957 822 949 920 1,206 ... ... ... Burundi ... 123 384 ... ... ... ... ... ... Cambodia 3,874 ... ... ... ... ... ... ... ... Cameroon 975 1,340 ... ... ... ... ... ... ... Canada 50,170 67,180 46,111 50,775 49,362 47,263 48,730 46,908 45,252 Cape Verde ... ... ... ... ... ... ... ... ... Central African Republic ... 409 25 30 ... ... ... ... ... Chad 33 349 248 569 ... ... ... ... ... Chile 6,590 10,510 10,198 10,891 11,569 12,522 12,904 13,271 13,796 China 391,500 760,000 1,645,000 1,735,000 1,700,323 1,683,550 1,683,550 1,674,650 1,698,500 China, Hong Kong SAR 6,402 4,234 21,700 22,767 21,386 20,929 13,470 6,637 9,859 China, Macao SAR ... ... 500 450 450 ... ... ... ... Colombia 19,080 21,200 14,490 10,491 11,700 11,662 12,473 10,965 12,824 Comoros ... ... ... ... ... ... ... ... ... Congo 989 706 645 ... ... ... ... ... ... Congo, Democratic Republic of 3,753 2,739 3,600 3,240 3,425 3,200 2,300 2,300 2,100 Cook Islands ... ... ... ... ... ... ... ... ... Costa Rica ... ... ... ... ... ... ... ... ... Côte d'Ivoire 2,000 3,480 2,070 2,465 2,667 2,814 2,878 3,112 3,268 Croatia ... ... 12,437 12,110 11,548 11,416 11,987 12,785 13,692 Cuba 19,806 15,109 16,026 ... ... ... ... ... ... Cyprus 851 2,901 4,601 2,528 2,728 3,662 4,362 4,783 4,980 Czech Republic ... 14,805 18,119 22,000 23,400 23,950 30,200 ... ... Denmark 8,298 9,390 11,387 11,902 11,804 12,262 12,392 11,749 11,413 Djibouti ... ... ... ... ... ... ... ... ... Dominica ... 33 ... ... ... ... ... ... ... Dominican Republic 2,125 3,375 4,535 4,092 4,192 3,972 4,098 4,005 ... Ecuador 1,295 3,858 ... 1,734 1,745 1,678 1,997 2,178 ... Egypt 12,153 35,570 39,837 42,469 46,000 50,000 52,000 51,000 53,000 El Salvador 1,441 2,570 ... 1,701 1,756 ... ... ... ... Equatorial Guinea ... ... ... ... ... ... ... ... ... Eritrea ... ... ... ... ... ... ... ... ... Estonia ... ... 4,165 1,864 954 ... ... ... ... Ethiopia 870 1,458 2,258 1,583 1,862 2,024 2,029 1,829 1,931 Fiji 389 549 531 437 439 450 410 446 396 Finland 6,476 9,162 8,974 6,542 5,910 6,743 5,510 4,030 3,459 France 69,903 72,478 55,495 46,361 46,931 45,020 43,304 42,406 38,242 21 1970 1980 1990 1995 1996 1997 1998 1999 2000 Gabon - 315 328 297 ... ... ... ... ... Gambia ... ... ... ... ... ... ... ... ... Georgia ... 17,626 11,191 1,839 1,054 917 595 1,327 296 Germany 138,878 183,908 204,651 221,000 193,300 182,000 181,904 204,831 206,770 Ghana 1,536 2,028 1,805 1,713 1,747 1,764 ... ... ... Greece 17,011 24,889 29,438 38,617 39,152 38,500 35,800 34,322 34,381 Grenada ... 20 22 ... ... ... ... ... ... Guatemala 2,986 2,699 ... 2,616 1,725 2,198 4,184 4,376 4,262 Guinea ... ... ... ... ... ... ... ... ... Guinea-Bissau ... ... ... ... ... ... ... ... ... Guyana 474 578 247 ... ... ... ... ... ... Haiti 421 1,094 1,027 ... ... ... ... ... ... Honduras 1,266 2,475 2,690 2,410 2,109 2,603 3,814 4,586 5,655 Hungary 22,050 27,158 28,212 25,709 27,594 26,057 26,849 22,985 21,608 Iceland ... ... ... ... ... ... ... ... ... India 62,930 77,376 61,162 69,589 73,841 83,162 79,313 82,504 75,085 Indonesia 32,530 83,900 155,300 186,200 211,823 225,385 216,200 225,417 232,467 Iran, Islamic Republic of 11,898 12,884 12,319 9,787 11,860 10,304 14,335 ... ... Iraq ... ... ... ... ... ... ... ... ... Ireland 5,550 9,660 6,505 7,700 7,400 5,700 6,050 6,350 6,720 Israel 3,868 5,337 5,440 4,933 4,793 ... ... ... ... Italy 71,618 73,105 61,746 50,203 51,481 51,900 50,681 45,065 44,218 Jamaica 1,261 1,284 1,380 1,216 1,219 1,175 1,160 1,078 991 Japan 221,039 303,177 270,055 262,788 271,032 254,567 267,050 263,154 257,965 Jordan 1,610 4,188 3,185 3,675 4,738 ... ... ... ... Kazakhstan ... 11,966 12,485 12,080 19,121 24,109 21,747 18,773 19,293 Kenya 2,426 4,556 6,647 7,932 8,436 ... ... ... ... Kiribati ... ... ... ... ... ... ... ... ... Korea, Democratic People's Republic of ... ... ... ... ... ... ... ... ... Korea, Republic of 39,632 70,357 92,000 87,509 93,001 94,252 103,586 97,135 98,286 Kuwait ... ... ... ... ... ... ... ... ... Kyrgyzstan ... 3,818 3,974 1,332 975 716 862 2,103 3,169 Lao People's Democratic Republic 361 ... ... 1,062 ... ... ... ... ... Latvia ... ... 5,209 2,101 1,876 1,775 2,018 1,916 ... Lebanon 1,281 ... ... 535 539 793 672 945 1,009 Lesotho ... ... ... ... ... ... ... ... ... Liberia ... 20 ... ... ... ... ... ... ... Libyan Arab Jamahiriya 1,639 2,134 ... ... ... ... ... ... ... Lithuania ... ... 6,654 4,876 4,538 5,755 7,427 8,217 7,207 Luxembourg ... ... ... ... ... ... ... ... ... Macedonia, The former Yugoslav Republic of ... ... 16,328 9,664 10,229 8,825 7,418 8,149 9,181 Madagascar 951 1,983 1,476 2,354 2,957 2,826 3,303 ... ... Malawi 444 630 1,061 1,160 975 731 501 ... ... Malaysia 7,566 13,529 18,430 21,827 23,000 27,400 29,190 30,567 28,390 Maldives ... ... ... ... ... ... ... ... ... Mali ... ... 17 22 21 ... ... ... ... Malta 509 1,115 ... ... ... ... ... ... ... Marshall Islands ... ... ... ... ... ... ... ... ... Mauritania ... ... ... ... ... ... ... ... ... Mauritius 590 959 1,000 1,215 1,193 1,144 1,034 979 976 Mexico 40,633 54,520 55,380 56,821 59,907 57,618 60,407 59,492 56,383 Micronesia, Federated States of ... ... ... ... ... ... ... ... ... Moldova, Republic of ... 7,559 9,088 7,108 9,657 9,539 7,512 8,731 9,262 Monaco ... ... ... ... ... ... ... ... ... Mongolia ... ... ... ... ... ... ... ... ... Morocco ... 11,491 12,797 12,139 12,769 12,642 12,600 11,916 11,800 Mozambique ... 1,100 1,030 106 250 250 950 1,084 1,417 Myanmar 1,513 2,724 979 752 1,727 1,991 2,040 2,270 2,559 Namibia ... ... ... ... ... ... ... ... ... Nauru ... ... ... ... ... ... ... ... ... Nepal 1,135 1,811 6,691 8,067 7,944 8,127 7,315 6,584 6,979 Netherlands 22,930 40,705 78,345 100,603 111,239 116,255 116,263 119,983 123,071 New Zealand 5,364 6,276 4,489 3,338 3,660 3,449 3,263 3,010 2,700 Nicaragua ... ... ... ... ... ... ... ... ... Niger ... ... ... ... ... ... ... ... ... Nigeria ... ... 10,380 9,413 ... ... ... ... ... Niue ... ... ... ... ... ... ... ... ... Norway ... 820 1,491 1,328 1,756 1,776 1,649 1,683 1,380 22 1970 1980 1990 1995 1996 1997 1998 1999 2000 Oman ... ... ... ... ... ... ... ... ... Pakistan 22,369 34,647 32,279 32,747 45,506 46,101 48,215 51,579 46,976 Palau ... ... ... ... ... ... ... ... ... Panama 1,011 1,084 810 1,136 663 752 320 ... ... Poland 69,193 93,446 91,500 101,000 95,200 95,842 96,741 94,600 83,440 Portugal 8,724 13,281 17,547 13,215 12,780 13,234 15,781 17,742 21,377 PuertoRico ... ... ... ... ... ... ... ... ... Qatar ... ... ... ... ... ... ... ... ... Romania ... ... 18,090 14,747 16,536 25,943 ... ... ... Russian Federation ... 181,345 150,533 140,973 137,214 176,146 210,730 266,031 333,953 Rwanda ... ... ... ... ... ... ... ... ... Saint Kitts and Nevis ... ... ... ... ... ... ... ... ... Saint Lucia ... ... ... ... ... ... ... ... ... Saint Vincent and the Grenadines ... ... ... ... ... ... ... ... ... Samoa ... ... ... ... ... ... ... ... ... San Marino ... ... ... ... ... ... ... ... ... Sao Tome and Principe ... ... ... ... ... ... ... ... ... Saudi Arabia ... ... ... ... ... ... ... ... ... Senegal 1,647 2,703 ... 2,129 1,566 1,556 ... ... ... Seychelles - 31 67 56 62 70 61 60 40 Sierra Leone 490 1,711 ... 467 ... ... ... ... ... Singapore 2,787 3,147 ... ... ... ... ... ... ... Slovakia ... ... 8,589 7,410 7,184 7,955 8,313 8,500 6,500 Slovenia ... ... 5,179 4,543 4,909 5,767 7,555 8,032 7,855 Solomon Islands ... ... ... ... ... ... ... ... ... Somalia ... ... ... ... ... ... ... ... ... South Africa 16,430 28,791 40,792 37,332 36,518 31,985 29,963 25,891 27,196 Spain 50,494 ... 75,995 78,676 77,675 77,315 81,940 74,873 74,799 Sri Lanka 3,035 5,225 5,621 5,822 6,160 5,712 5,797 5,333 4,889 Sudan 734 ... ... ... ... ... ... ... ... Suriname 187 379 487 472 483 ... ... ... ... Swaziland ... ... ... ... ... ... ... ... ... Sweden 8,975 10,933 9,648 7,193 7,251 6,237 5,692 6,060 5,958 Switzerland 29,229 31,264 31,771 41,976 42,955 37,638 34,453 32,139 34,299 Syrian Arab Republic 2,429 6,943 6,855 9,699 8,528 10,137 10,398 10,991 11,097 Tajikistan ... 4,728 5,022 964 604 153 191 209 667 Tanzania, United Republic of 2,599 4,735 3,742 3,699 3,733 4,710 ... ... ... Thailand 15,291 30,783 38,180 43,020 48,173 43,387 34,585 31,146 30,732 Timor Leste ... ... ... ... ... ... ... ... ... Togo ... ... ... ... ... ... ... ... ... Tokelau ... ... ... ... ... ... ... ... ... Tonga ... ... ... ... ... ... ... ... ... Trinidad and Tobago 825 849 701 920 1,102 1,386 1,680 1,945 2,050 Tunisia 3,286 4,419 6,852 7,421 7,159 7,735 9,813 11,066 12,231 Turkey 37,253 51,977 60,427 99,939 105,066 103,153 105,443 ... ... Turkmenistan ... ... ... ... ... ... ... ... ... Tuvalu ... ... ... ... ... ... ... ... ... Uganda 1,536 636 1,290 1,576 1,702 1,864 1,866 1,688 ... Ukraine ... 78,084 69,397 48,033 44,900 54,488 59,275 54,052 58,679 United Arab Emirates ... ... ... ... ... ... ... ... ... United Kingdom 145,530 155,618 126,017 155,103 166,496 167,670 152,998 143,794 139,125 United States 583,200 714,100 709,700 746,270 758,000 719,600 680,000 606,600 594,700 Uruguay 3,121 ... 2,765 3,561 6,044 10,732 10,187 11,161 10,894 Uzbekistan ... 4,148 4,370 2,742 5,172 8,521 7,700 10,695 7,768 Vanuatu ... ... ... ... ... ... ... ... ... Venezuela, Bolivarian Republic of 10,463 21,300 23,560 27,806 22,522 23,270 27,000 ... ... Viet Nam ... 7,920 25,000 42,940 43,200 42,660 43,900 42,580 ... Yemen ... ... 5,968 6,540 6,740 6,800 ... ... ... Yugoslavia ... ... ... 12,686 13,176 10,988 14,597 13,126 14,451 Zambia 1,145 1,283 ... ... ... ... ... ... ... Zimbabwe 3,625 3,571 2,600 3,036 3,230 3,523 3,390 3,790 3,900 Czechoslovakia (Former) 20,472 22,543 26,708 ... ... ... ... ... ... USSR (Former) 322,687 363,971 313,082 293,000 ... ... ... ... ... Yugoslavia (Former Socialist Federal Republic) 32,072 59,103 58,200 ... ... ... ... ... ... 23 Appendix 2: Cigarette imports, 1970-2000, selected years (metric tons / million pieces) 1970 1980 1990 1995 1996 1997 1998 1999 2000 Afghanistan 76 ... ... ... ... ... ... ... ... Albania ... ... ... ... 969 117 584 2,132 2,260 Algeria 191 218 1 2,170 1,068 57 ... ... ... Andorra ... ... ... ... 1,924 3,488 1,032 632 541 Angola 473 ... ... ... ... ... ... ... ... Antigua and Barbuda ... ... ... ... ... ... ... 36 ... Argentina 46 603 5 13 25 183 26 7 102 Armenia ... ... ... 1,752 1,516 1,731 1,000 1,473 1,520 Australia 606 796 537 830 774 580 640 1,013 1,444 Austria 731 854 476 1,562 1,136 1,246 1,630 1,837 1,880 Azerbaijan ... ... ... 1,447 1,999 3,197 2,708 5,159 1,580 Bahamas 200 200 75 55 45 63 40 130 536 Bahrain 637 1,436 859 1,022 1,109 ... ... ... 1,003 Bangladesh ... 177 86 70 18 90 52 ... ... Barbados 51 28 60 82 185 184 115 200 190 Belarus ... ... ... ... ... ... 11,645 12,630 7,237 Belgium 2,399 2,575 3,885 12,750 8,968 8,657 9,648 11,610 12,215 Belize 41 113 22 97 148 100 35 35 29 Benin 805 1,354 ... ... ... ... 3,664 182 114 Bhutan ... ... ... ... ... ... 5 5 ... Bolivia 7 4 37 108 9 6 ... 1 1,883 Bosnia and Herzegovina ... ... ... ... ... 84 116 116 25 Botswana ... 500 678 590 416 383 383 383 350 Brazil ... ... ... 11 92 579 57 42 60 Brunei Darussalam 216 342 382 ... ... 135 97 ... ... Bulgaria 114 643 485 244 260 165 58 81 184 Burkina Faso 82 277 250 28 12 132 400 ... ... Burundi 90 44 ... 1 7 - - ... 1 Cambodia ... ... ... ... ... ... ... ... ... Cameroon 13 26 5 118 789 151 888 179 400 Canada 204 706 297 372 332 361 481 480 503 Cape Verde 23 111 1 1 1 4 4 30 41 Central African Republic 10 20 26 43 187 ... ... ... ... Chad 244 40 50 11 25 40 30 30 55 Chile 2 1,010 29 506 148 173 184 ... ... China 70 5,829 10,551 26,372 30,567 22,210 20,647 21,885 25,353 China, Hong Kong SAR 4,650 9,175 48,119 59,017 62,805 29,801 27,520 22,964 22,293 China, Macao SAR 550 699 1,787 4,096 2,227 1,774 1,135 1,562 1,097 Colombia 1,713 2,323 12 857 1,367 2,399 3,770 8,476 5,700 Comoros ... ... ... 134 102 91 71 88 39 Congo 14 8 7 1 1 1 1 1 1 Congo, Democratic Republic of 56 ... ... ... ... 259 259 610 630 Cook Islands ... 20 1 10 10 10 9 11 11 Costa Rica 88 10 ... 4 4 9 11 11 601 Côte d'Ivoire 468 ... ... 7 5 8 12 8 9 Croatia ... ... ... 12 11 12 1 6 34 Cuba ... ... ... ... ... ... ... ... ... Cyprus 102 239 3,584 24,577 40,463 36,931 22,225 21,549 25,855 Czech Republic ... ... ... 6,688 4,312 4,338 3,667 3,466 2,728 Denmark 792 173 178 710 438 689 524 473 854 Djibouti 921 1,102 492 ... ... ... ... ... ... Dominica 5 3 4 19 6 4 ... 10 4 Dominican Republic 14 5 15 25 50 40 30 30 30 Ecuador 119 ... ... 18 25 49 44 41 55 Egypt 49 1,156 138 11 8 25 10 6 - El Salvador 532 20 2 728 630 617 1,117 1,159 1,251 Equatorial Guinea ... ... ... ... ... ... ... ... ... Eritrea ... ... ... ... ... ... ... ... ... Estonia ... ... ... 676 1,677 3,635 2,904 2,620 2,749 Ethiopia ... ... ... 11 ... 13 100 28 76 Fiji 14 12 11 55 30 50 40 30 16 Finland 6 100 69 444 1,314 999 1,205 1,664 1,761 France 4,509 26,782 48,010 58,296 58,055 60,900 60,156 62,349 52,906 24 1970 1980 1990 1995 1996 1997 1998 1999 2000 Gabon 10 140 40 33 40 160 180 180 160 Gambia 164 250 ... 335 202 537 2,568 1,111 281 Georgia ... ... ... 847 433 1,949 390 2,266 ... Germany 6,141 7,308 10,224 16,485 14,204 26,793 29,269 26,236 33,291 Ghana 13 41 ... ... 75 87 3 ... 1,982 Greece 21 593 4,862 11,747 12,343 11,405 13,240 12,787 11,066 Grenada 16 5 4 30 35 67 67 60 85 Guatemala 11 10 ... 539 556 802 767 244 498 Guinea ... ... ... 2,809 1,645 1,988 3,697 7,641 8,390 Guinea-Bissau 91 96 20 40 40 60 60 90 90 Israel 130 400 2,041 3,600 3,000 3,080 3,255 4,276 4,317 Italy 3,583 30,320 34,483 38,566 39,372 41,479 43,182 50,562 56,626 Jamaica 26 2 2 12 17 8 20 36 33 Japan 1,740 5,054 41,405 57,530 77,192 77,581 80,594 82,651 83,520 Jordan 13 113 87 167 41 179 289 594 428 Kazakhstan ... ... ... 2,400 3,000 3,000 1,800 1,264 3,770 Kenya 60 74 144 70 54 192 1,070 50 42 Kiribati ... ... ... 13 12 13 13 13 90 Korea, Democratic People's Republic of ... ... 200 312 1,918 699 1,000 920 760 Korea, Republic of 49 10 4,473 13,953 12,544 11,324 4,896 6,319 9,991 Kuwait 2,739 3,994 1,674 2,916 2,984 2,685 2,715 2,966 1,678 Kyrgyzstan ... ... ... 204 1,385 ... 1,068 1,162 ... Lao People's Democratic Republic 99 ... ... ... ... ... ... ... 864 Latvia ... ... ... 185 624 1,748 2,499 3,553 2,882 Lebanon 668 ... ... ... ... 10,479 12,418 6,985 5,554 Lesotho ... ... ... ... ... ... ... ... ... Liberia 202 292 100 135 200 455 370 360 200 Libyan Arab Jamahiriya 336 4,277 96 14 222 919 1,197 ... ... Lithuania ... ... ... 1,806 2,694 3,271 2,666 2,007 1,107 Luxembourg ... ... ... ... ... ... ... 4,937 5,970 Macedonia, The former Yugoslav Republic of ... ... ... 218 188 459 202 289 130 Madagascar 346 119 21 16 16 15 30 14 24 Malawi 15 2 ... 24 64 205 786 ... 18 Malaysia 2,470 2,891 991 2,090 964 1,460 1,062 1,011 1,434 Maldives ... ... ... 232 274 335 ... ... ... Mali 6 233 1,030 ... 169 261 ... ... ... Malta 91 81 79 163 357 3,709 319 383 346 Marshall Islands ... ... ... ... ... ... ... ... ... Mauritania 27 ... 70 408 450 450 450 450 1,916 Mauritius 11 10 11 44 29 48 46 151 210 Mexico ... ... 1 68 50 170 75 166 747 Micronesia, Federated States of ... ... ... ... ... ... ... ... ... Moldova, Republic of ... ... ... 132 628 ... 132 159 3,427 Monaco ... ... ... ... ... ... ... ... ... Mongolia ... ... ... ... 673 ... ... ... ... Morocco 207 989 1,355 1,953 1,780 1,775 1,933 1,899 2,024 Mozambique 31 ... ... ... ... ... ... ... ... Myanmar ... ... ... 56 44 127 306 502 ... Namibia ... ... ... ... ... ... ... ... 1,420 Nauru ... ... ... ... ... ... ... ... ... Nepal ... 40 4 70 100 50 110 80 90 Netherlands 1,765 19,173 14,239 17,468 20,221 18,424 17,519 15,833 16,732 New Zealand 52 62 32 89 106 143 167 282 387 Nicaragua 134 1 ... 25 24 37 100 1,051 1,924 Niger 266 544 541 1,013 2,851 1,090 1,203 ... ... Nigeria 20 60 198 846 1,332 920 5,513 1,599 2,966 Niue ... ... ... ... ... ... ... ... ... Norway 1,593 1,877 1,522 1,363 992 1,021 919 1,058 1,217 25 1970 1980 1990 1995 1996 1997 1998 1999 2000 Oman 80 3,067 1,402 22,395 17,077 17,526 25,488 30,831 34,749 Pakistan 130 3 3 8 2 126 27 30 14 Palau ... ... ... ... ... ... ... ... ... Panama 1 2 - - 9 41 789 961 778 Papua New Guinea 188 15 5 13 50 50 50 50 - Paraguay 1,252 1,911 1,807 22,811 33,762 36,937 35,452 16,659 10,336 Peru 1 1 ... 125 183 278 531 499 624 Philippines 112 281 476 4,413 1,154 1,575 4,693 2,526 2,739 Poland ... 1,413 5,032 1,550 701 500 387 554 87 Portugal 190 67 127 4,210 4,987 3,013 2,524 2,241 1,987 PuertoRico ... ... ... ... ... ... ... ... ... Qatar ... 684 822 1,045 1,193 ... 950 1,143 ... Romania ... ... ... 22,335 8,706 5,460 2,766 1,991 3,474 Russian Federation ... ... ... ... 49,373 93,400 75,111 27,070 15,003 Solomon Islands 24 28 25 175 120 150 160 130 ... Somalia ... ... ... ... ... ... ... ... ... South Africa 1,675 1,139 597 694 803 539 532 417 324 Spain 4,512 6,634 906 7,146 7,673 11,458 16,036 23,726 29,416 Sri Lanka ... 44 84 41 170 230 254 175 188 Sudan 578 242 ... 76 43 329 73 ... ... Suriname 36 100 15 232 48 58 131 458 785 Swaziland ... ... ... ... ... ... ... ... 348 Sweden 2,122 2,247 2,030 1,684 2,175 1,877 2,037 2,229 2,844 Switzerland 1,676 247 345 117 172 187 172 167 200 Syrian Arab Republic 236 784 ... 1,296 1,738 737 449 429 441 Tajikistan ... ... ... ... ... ... ... ... ... Tanzania, United Republic of 10 - 230 10 25 5 13 19 14 Thailand 15 242 449 2,120 2,030 2,933 2,585 5,617 6,854 Timor Leste ... ... ... ... ... ... ... ... ... Togo 946 779 1,327 794 980 1,348 992 1,075 892 Tokelau ... ... ... ... ... ... ... ... ... Tonga ... ... 93 70 72 110 72 88 70 Trinidad and Tobago 10 92 12 14 4 11 11 132 16 Tunisia ... 1,419 1,757 3,988 3,662 4,768 3,946 1,681 1,582 Turkey ... ... 15,851 130 37 21 19 1 3 Turkmenistan ... ... ... 1,712 1,088 706 1,111 2,913 2,284 Tuvalu ... 5 3 5 7 7 7 7 4 Uganda 10 ... ... 11 12 3 4 33 135 Ukraine ... ... ... ... 9,081 10,132 8,265 3,722 2,145 United Arab Emirates 1,176 13,942 7,379 10,500 8,100 18,000 24,000 24,000 21,900 United Kingdom 926 2,835 15,747 17,946 17,805 15,820 14,051 12,704 7,669 United States 121 569 2,677 3,212 4,202 4,408 6,432 10,828 15,087 Uruguay 20 90 4 1 4 2 3 2 1 Uzbekistan ... ... ... 5,625 2,211 310 291 184 753 Vanuatu 35 33 30 21 21 21 21 21 55 Venezuela, Bolivarian Republic of 8 427 31 45 125 56 30 32 84 Viet Nam ... ... 90 24,546 19,000 10,000 13,000 9,600 17,200 Yemen 396 1,420 6 32 4 334 51 51 150 Yugoslavia ... ... ... 100 27 131 304 304 2,199 Zambia 1 ... ... 1 ... ... 15 2 26 Zimbabwe ... ... 1 11 34 132 336 910 734 Czechoslovakia (Former) 7,000 7,000 1,000 ... ... ... ... ... ... USSR (Former) 41,596 58,133 77,733 76,570 ... ... ... ... ... Yugoslavia (Former Socialist Federal Republic) 115 2 1,510 ... ... ... ... ... ... 26 Appendix 3: Cigarette exports, 1970-2000, selected years (metric tons / million pieces) 1970 1980 1990 1995 1996 1997 1998 1999 2000 Afghanistan ... ... ... ... ... ... ... ... ... Albania ... ... ... ... 20 ... 58 20 5 Algeria 104 635 ... ... ... ... 7 ... 108 Andorra ... ... ... ... ... 39 86 76 65 Angola 155 ... ... ... ... ... ... ... ... Antigua and Barbuda ... ... ... ... ... ... ... ... ... Argentina ... 11 724 2,452 1,788 2,708 2,077 3,102 2,555 Armenia ... ... ... ... ... ... ... 133 130 Australia 594 291 647 1,122 3,106 2,880 3,339 1,289 1,170 Austria 91 188 1,617 4,205 5,112 10,205 12,378 14,223 17,065 Azerbaijan ... ... ... ... ... ... 48 120 435 Bahamas ... ... ... ... ... 1 1 1 24 Bahrain 259 1,039 18 12 14 ... ... ... ... Bangladesh ... ... 2 - 15 40 47 50 15 Barbados 56 96 44 37 13 31 15 18 18 Belarus ... ... ... ... ... ... 299 699 1,030 Belgium 3,363 10,875 11,765 10,628 12,126 12,081 10,815 10,922 9,268 Belize 28 1 1 161 137 94 94 94 1 Benin 67 5 ... ... ... ... 388 392 284 Bhutan ... ... ... ... ... ... ... ... ... Bolivia ... ... ... 527 626 581 478 429 297 Bosnia and Herzegovina ... ... ... ... ... 10 ... 2 ... Botswana ... 1 1 - 50 2 2 2 2 Brazil 609 1 12,435 63,417 80,262 87,313 87,169 8,058 842 Brunei Darussalam ... ... ... ... ... ... ... ... ... Bulgaria 45,038 69,189 60,360 60,914 40,143 25,655 11,307 3,999 4,049 Burkina Faso 3 ... ... ... ... 83 194 ... ... Burundi ... 40 ... ... ... ... - 11 14 Cambodia ... ... ... ... ... ... ... ... 15 Cameroon ... 14 89 171 203 102 143 143 14 Canada 264 659 1,804 4,449 1,968 1,462 2,842 1,621 1,559 Cape Verde ... ... ... ... ... ... ... ... 1 Central African Republic 14 ... 17 29 4 ... ... ... ... Chad ... ... ... ... ... ... ... ... ... Chile ... ... 45 137 169 244 232 ... ... China - 1,010 8,361 64,803 58,835 24,877 22,876 7,548 8,499 China, Hong Kong SAR 3,121 4,090 75,712 74,327 79,572 45,874 35,229 18,536 34,464 China, Macao SAR 1 1 ... 1,258 1,496 1,543 1,151 573 762 Colombia ... 106 564 117 114 241 438 1,155 2,469 Comoros ... ... ... ... ... ... ... ... - Congo 162 29 ... 17 ... ... ... ... ... Congo, Democratic Republic of ... ... ... ... ... ... ... ... ... Cook Islands ... ... ... ... ... ... ... ... ... Costa Rica ... 1 ... ... ... 41 680 700 324 Côte d'Ivoire 35 ... ... 89 122 6 20 482 707 Croatia ... ... ... 1,627 1,035 2,462 2,603 3,511 6,117 Cuba 7,575 2,523 ... ... ... ... ... ... ... Cyprus 2 2,527 3,082 555 1,250 2,952 2,694 3,042 3,277 Czech Republic ... ... ... 8,025 11,671 18,509 18,521 10,641 8,718 Denmark 1,766 1,566 3,634 4,346 3,812 4,184 4,593 4,240 4,195 Djibouti ... ... ... ... ... ... ... ... ... Dominica ... ... ... 8 7 13 ... 5 6 Dominican Republic ... ... ... ... 16 4 ... ... ... Ecuador 28 26 443 60 37 59 79 10 177 Egypt 175 22 121 44 13 ... 1 16 ... El Salvador 1 14 ... 597 820 511 14 2 8 Equatorial Guinea ... ... ... ... ... ... ... ... ... Eritrea ... ... ... ... ... ... ... ... ... Estonia ... ... ... 59 193 577 404 250 65 Ethiopia ... ... ... ... ... ... ... ... ... Fiji 66 6 10 1 2 1 - - 8 Finland 315 3,119 1,307 1,377 3,313 3,765 2,086 553 460 France 3,795 5,627 5,410 8,514 11,172 14,851 14,721 15,795 14,390 27 1970 1980 1990 1995 1996 1997 1998 1999 2000 Gabon ... ... ... ... ... 30 ... 506 831 Gambia ... ... ... 85 ... 26 ... 35 ... Georgia ... ... ... ... ... ... ... ... ... Germany 5,002 36,590 65,982 80,344 92,754 80,520 89,198 106,832 112,411 Ghana ... ... ... ... 235 73 90 160 766 Greece 34 15 3,352 13,399 22,411 20,277 14,320 15,885 18,621 Grenada ... ... ... ... ... ... ... ... ... Guatemala 958 45 ... 611 580 3,112 1,280 1,312 1,069 Guinea ... ... ... 7 8 ... 42 54 23 Guinea-Bissau ... ... ... ... ... ... ... ... ... Israel - 86 8 15 25 45 50 90 104 Italy 114 311 417 244 235 211 314 238 283 Jamaica ... 73 32 14 14 26 32 36 27 Japan 58 159 5,336 13,977 12,517 14,642 11,957 13,536 13,775 Jordan 333 2,018 233 7 3 496 1,519 515 1,973 Kazakhstan ... ... ... 550 2,700 2,000 2,038 502 853 Kenya 45 49 389 5,046 1,963 2,453 2,335 2,124 2,826 Kiribati ... ... ... ... ... ... ... ... ... Korea, Democratic People's ... ... 10 3 - 21 21 21 25 Republic of Korea, Republic of 9 468 405 1,513 2,951 2,721 3,283 3,663 8,899 Kuwait 748 1,238 44 8 92 48 39 58 ... Kyrgyzstan ... ... ... ... ... ... 3,418 4,032 ... Lao People's Democratic ... ... ... ... ... ... ... ... ... Republic Latvia ... ... ... 2,128 875 193 247 648 1,386 Lebanon 1 ... ... ... ... 21 14 2 ... Lesotho ... ... ... ... ... ... ... ... ... Liberia ... ... ... ... ... ... ... ... ... Libyan Arab Jamahiriya ... ... 2 ... ... ... ... ... ... Lithuania ... ... ... 146 30 48 2,236 3,810 3,816 Luxembourg ... ... ... ... ... ... ... 5,756 7,382 Macedonia, The former Yugoslav ... ... ... 1,483 6,167 6,176 3,620 4,688 5,675 Republic of Madagascar 235 9 2 1 - 5 ... 1 2 Malawi ... 48 4 3 ... ... ... ... 61 Malaysia 1,759 31 614 3,395 5,321 9,341 10,221 13,715 11,171 Maldives ... ... ... ... ... ... ... ... ... Mali 1 ... 4 ... ... ... ... ... ... Malta 67 458 72 130 263 129 116 158 377 Marshall Islands ... ... ... ... ... ... ... ... ... Mauritania ... ... ... ... ... ... ... ... ... Mauritius ... ... 40 3 5 - 1 - ... Mexico 3 16 765 6,589 10,304 9,779 11,220 8,465 10,063 Micronesia, Federated States of ... ... ... ... ... ... ... ... ... Moldova, Republic of ... ... ... ... 7,212 ... 490 8,691 401 Monaco ... ... ... ... ... ... ... ... ... Mongolia ... ... ... ... 28 ... ... ... ... Morocco 1 ... 6 ... ... 1 10 ... 5 Mozambique 577 ... ... ... ... ... ... ... ... Myanmar ... ... ... ... ... ... ... ... ... Namibia ... ... ... ... ... ... ... ... 1,239 Nauru ... ... ... ... ... ... ... ... ... Nepal ... ... ... 1 1 1 1 1 ... Netherlands 4,973 30,117 69,333 82,180 116,035 118,003 103,722 105,113 101,550 New Zealand 52 156 83 96 108 146 164 181 184 Nicaragua 64 ... ... ... 32 50 353 8 2 Niger ... 261 ... 4 5 2 7 ... ... Nigeria ... ... ... ... ... ... ... 2 ... Niue ... ... ... ... ... ... ... ... ... Norway 52 7 70 35 34 25 37 37 11 Oman ... 1,006 152 18,168 18,265 16,730 12,888 9,756 11,590 Pakistan 40 496 796 478 92 47 - 4 22 Palau ... ... ... ... ... ... ... ... ... Panama 1 2 54 709 822 849 274 7 - Papua New Guinea ... ... 7 ... ... ... ... ... ... Paraguay ... ... ... ... ... 39 ... 2,875 3,740 Peru ... ... ... ... ... ... 156 1,130 1,498 Philippines 13 4 5,598 897 2,401 1,027 1,392 2,814 3,627 Poland ... ... ... 4,150 7,543 5,719 6,251 6,318 8,776 Portugal 141 295 229 266 316 242 571 2,739 6,697 PuertoRico ... ... ... ... ... ... ... ... ... Qatar ... ... ... 1 1 1 1 1 1 Romania ... ... ... 78 4 5 75 16 71 Russian Federation ... ... ... ... 4,409 1,238 298 167 545 28 1970 1980 1990 1995 1996 1997 1998 1999 2000 Rwanda ... ... ... ... ... ... 36 3 ... Saint Kitts and Nevis ... ... ... ... ... ... ... ... ... Saint Lucia ... ... ... ... ... ... 1 1 ... Saint Vincent and the ... ... ... ... ... ... ... ... ... Grenadines Samoa ... 15 13 14 5 15 15 15 10 San Marino ... ... ... ... ... ... ... ... ... Sao Tome and Principe ... ... ... ... ... ... ... ... ... Saudi Arabia ... 1,193 620 25 12 1 7 7 - Senegal 1,804 3 177 109 18 53 373 539 228 Seychelles ... ... 2 5 9 15 14 5 5 Sierra Leone ... ... ... ... ... ... ... ... ... Singapore 1,550 1,405 28,445 49,044 56,153 60,844 53,280 30,684 27,562 Slovakia ... ... ... 4,144 2,823 3,507 3,021 3,030 3,638 Slovenia ... ... ... 13,676 1,227 2,328 4,138 4,632 4,831 Solomon Islands ... ... ... ... ... ... ... ... ... Somalia ... ... ... ... ... ... ... ... ... South Africa 80 150 238 7,200 12,242 14,915 19,331 10,619 20,881 Spain 402 916 837 4,025 3,614 5,308 4,195 5,598 5,210 Sri Lanka ... 40 376 726 972 1,035 673 459 368 Sudan ... ... ... ... ... ... ... ... ... Suriname ... ... ... ... 1 6 6 ... ... Swaziland ... ... ... ... ... ... ... ... 257 Sweden 126 174 91 276 304 1,124 979 618 796 Switzerland 14,583 12,766 14,710 24,822 26,011 21,579 16,827 14,700 17,714 Syrian Arab Republic ... 1,112 343 ... ... ... ... ... ... Tajikistan ... ... ... ... ... ... ... ... ... Tanzania, United Republic of 1 1,076 309 ... ... 1,705 130 1,714 10 Thailand ... 1 ... 100 237 339 696 847 622 Timor Leste ... ... ... ... ... ... ... ... ... Togo 9 10 1 ... 15 6 6 6 119 Tokelau ... ... ... ... ... ... ... ... ... Tonga ... ... 1 ... ... ... - - - Trinidad and Tobago 2 7 26 111 183 166 92 1,356 1,494 Tunisia ... 30 451 1,043 2,244 2,872 3,030 1,729 1,476 Turkey 13 - 2,827 8,102 21,057 12,270 8,778 9,581 12,269 Turkmenistan ... ... ... ... ... ... ... ... ... Tuvalu ... ... ... ... ... ... ... ... ... Uganda 29 ... ... 74 16 94 ... 33 165 Ukraine ... ... ... ... 10,247 4,577 4,655 8,519 10,248 United Arab Emirates ... 2,304 ... ... ... ... ... ... ... United Kingdom 20,568 41,014 40,759 83,216 87,566 94,835 82,310 73,469 80,642 United States 29,147 81,998 164,301 231,100 243,897 217,004 201,358 151,223 148,261 Uruguay ... - 132 185 3,688 7,885 6,803 7,296 7,637 Uzbekistan ... ... ... ... 18 12 16 1,005 2,800 Vanuatu ... ... ... ... ... ... ... ... ... Venezuela, Bolivarian Republic ... 539 6,486 11,897 18,001 15,593 17,129 9,738 4,798 of Viet Nam ... ... ... 124 96 188 300 120 120 Yemen 3 36 580 370 500 390 121 147 250 Yugoslavia ... ... ... ... 5,545 4,200 720 720 100 Zambia ... ... ... ... ... ... 645 18 120 Zimbabwe 1,700 1,800 379 818 1,754 1,761 1,107 1,201 1,395 Czechoslovakia (Former) ... 800 1 ... ... ... ... ... ... USSR (Former) 405 947 2,500 5,170 ... ... ... ... ... Yugoslavia (Former Socialist 378 4,249 3,019 ... ... ... ... ... ... Federal Republic) 29 Appendix 4: Sources ­cigarette production, imports, exports 1970-2000, selected years 1970 1980 1990 1995 1996 1997 1998 1999 2000 Afghanistan Exports ... ... ... ... ... ... ... ... ... Imports COMTRADE ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Albania Exports ... ... ... ... COMTRADE ... COMTRADE COMTRADE COMTRADE Imports ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Algeria Exports COMTRADE COMTRADE ... COMTRADE ... ... COMTRADE ... COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE ... ... COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Andorra Exports ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Angola Exports COMTRADE ... ... ... ... ... ... ... ... Imports COMTRADE ... ... ... ... ... ... ... ... Production UNSD ... ... ... ... ... ... ... ... Antigua and Barbuda Exports ... ... ... ... ... ... ... COMTRADE ... Imports ... ... ... ... ... ... ... COMTRADE ... Production ... ... ... ... ... ... ... ... ... Argentina Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA ERC ERC ERC ERC ERC ERC ERC Armenia Exports ... ... ... ... ... ... ... COMTRADE COMTRADE Imports ... ... ... FAO FAO COMTRADE FAO COMTRADE COMTRADE Production ... CIS CIS CIS CIS CIS CIS UNSD UNSD Australia Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production USDA USDA ERC ERC ERC ERC ERC ERC ERC Austria Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD ERC ERC ERC ERC ERC Azerbaijan Exports ... ... ... ... ... ... COMTRADE COMTRADE COMTRADE Imports ... ... ... ERC ERC ERC COMTRADE COMTRADE COMTRADE Production ... CIS CIS CIS CIS CIS CIS ERC ERC Bahamas Exports ... ... ... ... ... FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Bahrain Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE ... ... ... ... Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE ... ... ... COMTRADE Production ... ... ... ... ... ... ... ... ... Bangladesh Exports ... ... FAO FAO FAO FAO FAO FAO FAO Imports ... FAO FAO FAO FAO FAO FAO ... ... Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Barbados Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD ... ... ... ... ... Belarus Exports ... ... ... ... ... ... COMTRADE COMTRADE COMTRADE Imports ... ... ... ... ... ... COMTRADE COMTRADE COMTRADE Production ... UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Belgium Exports ... ... ... ... ... ... ... COMTRADE COMTRADE Imports ... ... ... ... ... ... ... COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD ERC Belize Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Benin Exports COMTRADE COMTRADE ... ... ... ... COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE ... ... ... ... COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Bhutan Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... COMTRADE COMTRADE ... Production ... ... ... ... ... ... ... ... ... Bolivia Exports COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD ... UNSD UNSD ... ... ... ... ... Bosnia and Herzegovina Exports ... ... ... ... ... ERC ... ERC ... Imports ... ... ... ... ... ERC ERC ERC ERC Production ... ... ERC ERC ERC ERC ERC ERC ERC 30 1970 1980 1990 1995 1996 1997 1998 1999 2000 Botswana Exports ... FAO FAO FAO FAO FAO FAO FAO FAO Imports ... FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Brazil Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Brunei Darussalam Exports ... ... ... ... ... COMTRADE ... ... ... Imports COMTRADE COMTRADE COMTRADE ... ... COMTRADE COMTRADE ... ... Production ... ... ... ... ... ... ... ... ... Bulgaria Exports FAO FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD ERC UNSD UNSD UNSD UNSD UNSD UNSD Burkina Faso Exports COMTRADE ... ... ... ... COMTRADE COMTRADE ... ... Imports COMTRADE COMTRADE FAO COMTRADE COMTRADE COMTRADE COMTRADE ... ... Production ... UNSD UNSD ECOWAS ECOWAS ECOWAS ... ... ... Burundi Exports ... FAO ... ... ... ... FAO FAO FAO Imports FAO FAO ... FAO FAO FAO FAO ... FAO Production ... UNSD UNSD ... ... ... ... ... ... Cambodia Exports ... ... ... ... FAO FAO FAO FAO FAO Imports ... ... ... ... ... ... ... ... ... Production UNSD ... ... ... ... ... ... ... ... Cameroon Exports ... FAO FAO FAO FAO FAO FAO FAO FAO Imports COMTRADE COMTRADE FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD ... ... ... ... ... ... ... Canada Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA UNSD UNSD UNSD ERC UNSD UNSD Cape Verde Exports ... ... ... ... ... ... ... ... FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Central African Republic Exports COMTRADE ... FAO COMTRADE COMTRADE ... ... ... ... Imports COMTRADE COMTRADE FAO COMTRADE COMTRADE ... ... ... ... Production ... UNSD UNSD UNSD ... ... ... ... ... Chad Exports COMTRADE ... ... ... ... ... ... ... ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD ... ... ... ... ... Chile Exports ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD China Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production USDA USDA USDA USDA USDA USDA USDA USDA USDA China, Hong Kong SAR Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD USDA USDA China, Macao SAR Exports FAO FAO ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... UNSD UNSD UNSD ... ... ... ... Colombia Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA ERC ERC ERC ERC ERC ERC ERC Comoros Exports ... FAO FAO FAO FAO FAO FAO FAO FAO Imports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Congo Exports COMTRADE COMTRADE ... COMTRADE ... ... ... ... ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD ... ... ... ... ... ... Congo, Democratic Republic of Exports ... ... ... ... ... ... ... ... ... Imports FAO ... ... ... ... FAO FAO FAO FAO Production UNSD UNSD ERC ERC ERC ERC ERC ERC ERC Cook Islands Exports ... ... ... ... ... ... ... ... ... Imports ... FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Costa Rica Exports ... COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO ... FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Côte d'Ivoire Exports COMTRADE ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD ERC ERC ERC ERC ERC ERC ERC Croatia Exports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD 31 1970 1980 1990 1995 1996 1997 1998 1999 2000 Djibouti Exports ... ... COMTRADE ... ... ... ... ... ... Imports FAO FAO COMTRADE ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Dominica Exports ... ... ... COMTRADE COMTRADE COMTRADE ... COMTRADE COMTRADE Imports FAO FAO FAO COMTRADE COMTRADE COMTRADE ... COMTRADE COMTRADE Production ... UNSD ... ... ... ... ... ... ... Dominican Republic Exports ... COMTRADE ... ... COMTRADE COMTRADE ... ... ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD ... Ecuador Exports FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD ... UNSD UNSD UNSD UNSD UNSD ... Egypt Exports FAO FAO FAO FAO FAO ... FAO FAO ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD El Salvador Exports COMTRADE COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD ... UNSD UNSD ... ... ... ... Equatorial Guinea Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Eritrea Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Estonia Exports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... UNSD UNSD UNSD ... ... ... ... Ethiopia Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Fiji Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Finland Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD ERC ERC ERC ERC France Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Gabon Exports ... ... ... ... ... COMTRADE ... COMTRADE COMTRADE Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD ... ... ... ... ... Gambia Exports ... ... ... COMTRADE ... COMTRADE COMTRADE COMTRADE ... Imports COMTRADE COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Georgia Exports ... ... ... ... ... ... ... COMTRADE COMTRADE Imports ... ... ... ERC ERC ERC ERC ERC ... Production ... CIS CIS CIS CIS CIS CIS UNSD UNSD Germany Exports FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Ghana Exports ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO ... ... FAO FAO FAO ... FAO Production UNSD UNSD UNSD ECOWAS ECOWAS ECOWAS ... ... ... Greece Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA ERC ERC ERC ERC ERC UNSD UNSD Grenada Exports ... ... ... ... ... ... ... ... ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... UNSD UNSD ... ... ... ... ... ... Guatemala Exports COMTRADE COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD ... ... ... ... ... ... Haiti Exports ... ... ... ... ... ... ... ... ... Imports ... FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD ... ... ... ... ... ... Honduras Exports COMTRADE COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD ERC ERC ERC ERC ERC ERC ERC Hungary Exports FAO FAO FAO FAO FAO FAO ... FAO ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Iceland Exports ... ... ... ... ... ... ... ... ... Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... 32 1970 1980 1990 1995 1996 1997 1998 1999 2000 India Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Indonesia Exports ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Iran, Islamic Republic of Exports FAO ... ... ... ... FAO FAO ... ... Imports FAO FAO FAO FAO FAO FAO ... ... FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD ... ... Iraq Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Ireland Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD ERC ERC ERC ERC ERC ERC ERC Israel Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD ... ... ... ... Italy Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Jamaica Exports ... COMTRADE FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Japan Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Jordan Exports COMTRADE COMTRADE COMTRADE COMTRADE FAO COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD ... ... ... ... Kazakhstan Exports ... ... ... FAO FAO FAO FAO FAO FAO Imports ... ... ... FAO FAO FAO FAO FAO FAO Production ... CIS CIS CIS CIS CIS CIS UNSD UNSD Kenya Exports FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD ... ... ... ... Kiribati Exports ... ... ... FAO FAO FAO FAO FAO ... Imports ... ... ... FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Korea, Democratic People's Exports ... ... FAO FAO FAO FAO FAO FAO FAO Republic of Imports ... ... FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Korea, Republic of Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Kuwait Exports FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Kyrgyzstan Exports ... ... ... COMTRADE COMTRADE ... COMTRADE COMTRADE ... Imports ... ... ... COMTRADE COMTRADE ... COMTRADE FAO ... Production ... CIS CIS CIS CIS CIS CIS CIS UNSD Lao People's Democratic Exports FAO ... ... ... ... ... ... ... ... Republic Imports FAO ... ... ... ... ... ... ... FAO Production UNSD ... ... UNSD ... ... ... ... ... Latvia Exports ... ... ... FAO FAO FAO FAO FAO FAO Imports ... ... ... FAO FAO FAO FAO FAO FAO Production ... ... UNSD UNSD UNSD UNSD UNSD UNSD ... Lebanon Exports COMTRADE ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD ... ... UNSD UNSD UNSD UNSD UNSD UNSD Lesotho Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Liberia Exports COMTRADE ... ... ... ... ... ... ... ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... UNSD ... ... ... ... ... ... ... Libyan Arab Jamahiriya Exports ... ... COMTRADE ... ... ... ... ... ... Imports COMTRADE COMTRADE COMTRADE FAO FAO COMTRADE COMTRADE ... ... Production UNSD UNSD ... ... ... ... ... ... ... Lithuania Exports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... UNSD UNSD UNSD UNSD UNSD UNSD UNSD 33 1970 1980 1990 1995 1996 1997 1998 1999 2000 Luxembourg Exports ... ... ... ... ... ... ... COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... COMTRADE COMTRADE Macedonia, The former Yugoslav Exports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Republic of Imports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... ERC ERC ERC ERC ERC ERC ERC Madagascar Exports FAO FAO FAO FAO FAO FAO ... FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD ... ... Malawi Exports ... COMTRADE COMTRADE COMTRADE ... ... ... ... COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE ... COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD ... ... Malaysia Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD ERC ERC ERC ERC ERC ERC ERC Maldives Exports ... ... FAO FAO FAO FAO FAO FAO ... Imports ... ... ... COMTRADE COMTRADE COMTRADE ... ... ... Production ... ... ... ... ... ... ... ... ... Mali Exports COMTRADE ... COMTRADE ... ... ... ... ... ... Imports COMTRADE COMTRADE COMTRADE ... COMTRADE COMTRADE ... ... ... Production ... ... UNSD UNSD UNSD ... ... ... ... Malta Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD ... ... ... ... ... ... ... Marshall Islands Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Mauritania Exports ... ... ... ... ... ... ... ... ... Imports FAO ... FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Mauritius Exports ... ... FAO FAO FAO FAO FAO FAO ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Mexico Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Micronesia, Federated States of Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Moldova, Republic of Exports ... ... ... COMTRADE COMTRADE ... COMTRADE COMTRADE COMTRADE Imports ... ... ... COMTRADE COMTRADE ... COMTRADE COMTRADE COMTRADE Production ... CIS CIS CIS CIS CIS CIS CIS UNSD Monaco Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Mongolia Exports ... ... ... ... COMTRADE ... ... ... COMTRADE Imports ... ... ... ... COMTRADE ... ... ... COMTRADE Production ... ... ... ... ... ... ... ... ... Morocco Exports COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... UNSD ERC ERC ERC ERC ERC ERC ERC Mozambique Exports FAO ... ... ... ... ... ... ... ... Imports FAO ... ... ... ... ... ... ... ... Production ... UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Myanmar Exports COMTRADE ... ... ... ... ... ... ... ... Imports COMTRADE ... ... National National National National National ... statistics statistics statistics statistics statistics Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Namibia Exports ... ... ... ... ... ... ... ... FAO Imports ... ... ... ... ... ... ... ... FAO Production ... ... ... ... ... ... ... ... ... Nauru Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Nepal Exports ... ... ... FAO FAO FAO FAO FAO ... Imports ... FAO FAO FAO FAO FAO FAO FAO FAO Production National National National National National National National National National statistics statistics statistics statistics statistics statistics statistics statistics statistics Netherlands Exports USDA USDA USDA USDA USDA USDA USDA USDA USDA Imports USDA USDA USDA USDA USDA COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA USDA USDA USDA USDA USDA USDA New Zealand Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD ERC 34 1970 1980 1990 1995 1996 1997 1998 1999 2000 Nicaragua Exports COMTRADE COMTRADE ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Niger Exports COMTRADE COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE ... ... Imports COMTRADE FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE ... ... Production ... ... ... ... ... ... ... ... ... Nigeria Exports COMTRADE ... ... ... ... ... ... COMTRADE ... Imports FAO FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... UNSD ECOWAS ... ... ... ... ... Niue Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Norway Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... USDA ERC ERC ERC ERC ERC ERC ERC Oman Exports ... FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Pakistan Exports FAO FAO FAO FAO FAO FAO FAO COMTRADE COMTRADE Imports FAO FAO FAO FAO FAO FAO FAO COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Palau Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Panama Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD ... ... Papua New Guinea Exports ... ... COMTRADE ... ... ... COMTRADE ... COMTRADE Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Paraguay Exports ... ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD ... ... ... ... ... ... Peru Exports ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO ... FAO FAO FAO FAO FAO FAO Production ... UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Philippines Exports FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Poland Exports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Portugal Exports FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD PuertoRico Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Qatar Exports ... ... ... FAO FAO FAO FAO FAO FAO Imports ... FAO COMTRADE COMTRADE COMTRADE ... COMTRADE COMTRADE ... Production ... ... ... ... ... ... ... ... ... Romania Exports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... UNSD UNSD UNSD UNSD ... ... ... Russian Federation Exports ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... CIS CIS CIS CIS CIS CIS UNSD UNSD Rwanda Exports ... ... ... ... ... COMTRADE COMTRADE COMTRADE ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Saint Kitts and Nevis Exports ... FAO FAO FAO FAO FAO FAO FAO ... Imports ... FAO FAO FAO FAO FAO FAO COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Saint Lucia Exports ... ... ... ... ... ... FAO FAO ... Imports FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Saint Vincent and the Grenadines Exports ... COMTRADE ... ... ... ... ... COMTRADE ... Imports FAO FAO FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Samoa Exports ... FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... San Marino Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... 35 1970 1980 1990 1995 1996 1997 1998 1999 2000 Sao Tome and Principe Exports FAO FAO FAO FAO FAO FAO ... ... ... Imports FAO FAO FAO FAO FAO FAO ... ... ... Production ... ... ... ... ... ... ... ... ... Saudi Arabia Exports ... FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO COMTRADE COMTRADE COMTRADE COMTRADE FAO COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... Senegal Exports FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD ... ECOWAS ECOWAS ECOWAS ... ... ... Seychelles Exports ... ... FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO ... Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Sierra Leone Exports ... ... ... ... ... ... ... ... ... Imports FAO FAO FAO FAO FAO FAO FAO FAO ... Production UNSD UNSD ... ECOWAS ... ... ... ... ... Singapore Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD ... ... ... ... ... ... ... Slovakia Exports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... UNSD ERC ERC ERC ERC ERC ERC Slovenia Exports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... UNSD UNSD UNSD UNSD UNSD UNSD UNSD Solomon Islands Exports ... ... ... ... ... ... ... ... ... Imports FAO FAO FAO FAO FAO FAO FAO FAO ... Production ... ... ... ... ... ... ... ... ... Somalia Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... South Africa Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO National National National National National National statistics statistics statistics statistics statistics statistics Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Spain Exports COMTRADE COMTRADE FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE ERC Production UNSD ... UNSD UNSD UNSD UNSD UNSD UNSD UNSD Sri Lanka Exports ... FAO FAO FAO FAO FAO FAO FAO FAO Imports ... FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Sudan Exports ... ... ... ... ... ... ... ... ... Imports COMTRADE COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE ... ... Production UNSD ... ... ... ... ... ... ... ... Suriname Exports ... ... ... ... COMTRADE COMTRADE COMTRADE ... COMTRADE Imports FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD ... ... ... ... Swaziland Exports ... ... ... ... ... ... ... ... COMTRADE Imports ... ... ... ... ... ... ... ... COMTRADE Production ... ... ... ... ... ... ... ... ... Sweden Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Switzerland Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Syrian Arab Republic Exports ... COMTRADE COMTRADE ... ... ... ... ... ... Imports FAO FAO ... FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Tajikistan Exports ... ... ... ... ... ... ... ... COMTRADE Imports ... ... ... ... ... ... ... ... COMTRADE Production ... CIS CIS CIS CIS CIS CIS CIS UNSD Tanzania, United Republic of Exports FAO FAO FAO ... ... COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD ... ... ... Thailand Exports ... COMTRADE ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Timor Leste Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Togo Exports COMTRADE FAO FAO ... FAO FAO FAO FAO FAO Imports COMTRADE FAO FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... ... ... ... ... ... ... ... ... 36 1970 1980 1990 1995 1996 1997 1998 1999 2000 Tokelau Exports ... ... ... ... ... ... ... ... ... Imports ... ... ... ... ... ... ... ... ... Production ... ... ... ... ... ... ... ... ... Tonga Exports ... ... FAO ... ... ... FAO FAO FAO Imports ... COMTRADE FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Trinidad and Tobago Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Tunisia Exports ... FAO FAO FAO FAO FAO FAO FAO FAO Imports ... FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD Turkey Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD National National National National National National ... ... statistics statistics statistics statistics statistics statistics Turkmenistan Exports ... ... ... ... ... ... ... ... COMTRADE Imports ... ... ... ERC ERC ERC ERC ERC ERC Production ... ... ... ... ... ... ... ... ... Tuvalu Exports ... FAO FAO FAO FAO FAO FAO FAO ... Imports ... FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Uganda Exports FAO ... ... COMTRADE COMTRADE COMTRADE ... COMTRADE COMTRADE Imports FAO ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD ... Ukraine Exports ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports ... ... ... ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production ... UNSD UNSD UNSD UNSD UNSD UNSD UNSD UNSD United Arab Emirates Exports ... FAO ... ... ... ... ... ... ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... United Kingdom Exports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production USDA USDA USDA National National National National National National statistics statistics statistics statistics statistics statistics United States Exports USDA USDA USDA USDA USDA USDA USDA USDA USDA Imports USDA USDA USDA USDA USDA USDA USDA USDA USDA Production USDA USDA USDA USDA USDA USDA USDA USDA USDA Uruguay Exports ... FAO COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production UNSD ... ERC ERC ERC ERC UNSD UNSD UNSD Uzbekistan Exports ... ... ... ... ERC ERC ERC ERC ERC Imports ... ... ... ERC ERC ERC ERC ERC ERC Production ... CIS CIS CIS CIS ERC ERC ERC ERC Vanuatu Exports ... ... ... ... ... ... ... ... ... Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... ... ... ... ... ... ... ... Venezuela, Bolivarian Republic of Exports ... COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Imports COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE COMTRADE Production USDA USDA USDA USDA USDA USDA USDA ... ... Viet Nam Exports ... ... ... FAO FAO FAO FAO FAO FAO Imports ... ... FAO FAO FAO FAO FAO FAO FAO Production ... National National National National National National National ... statistics statistics statistics statistics statistics statistics statistics Yemen Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports FAO FAO FAO FAO FAO FAO FAO FAO FAO Production ... ... UNSD UNSD UNSD UNSD ... ... ... Yugoslavia Exports ... ... ... ... FAO FAO FAO FAO FAO Imports ... ... ... FAO FAO FAO FAO FAO FAO Production ... ... ... UNSD UNSD UNSD UNSD UNSD UNSD Zambia Exports COMTRADE ... ... COMTRADE ... ... COMTRADE COMTRADE COMTRADE Imports COMTRADE ... ... COMTRADE ... ... COMTRADE COMTRADE COMTRADE Production UNSD UNSD ... ... ... ... ... ... ... Zimbabwe Exports FAO FAO FAO FAO FAO FAO FAO FAO FAO Imports ... ... FAO FAO FAO FAO FAO FAO FAO Production USDA USDA ERC ERC ERC ERC ERC ERC ERC Czechoslovakia (Former) Exports ... FAO FAO ... ... ... ... ... ... Imports FAO FAO FAO ... ... ... ... ... ... Production UNSD UNSD UNSD ... ... ... ... ... ... USSR (Former) Exports USDA USDA USDA USDA ... ... ... ... ... Imports USDA USDA USDA USDA ... ... ... ... ... Production UNSD UNSD UNSD USDA ... ... ... ... ... Yugoslavia (Former Socialist Exports COMTRADE COMTRADE COMTRADE ... ... ... ... ... ... Federal Republic) Imports FAO FAO FAO ... ... ... ... ... ... Production UNSD UNSD UNSD ... ... ... ... ... ... 37 Appendix5: Total cigarette consumption estimates, 1970-2000, selected years (3 year-moving-average, million pieces) 1970 1980 1990 1995 1996 1997 1998 1999 2000 Afghanistan ... ... ... ... ... ... ... ... ... Albania ... ... ... ... 1,432 ... 1,733 1,927 2,246 Algeria 6,362 15,234 17,403 17,450 17,032 16,797 17,269 17,719 17,637 Andorra ... ... ... ... ... ... ... ... ... Angola 2,425 ... ... ... ... ... ... ... ... Antigua and Barbuda ... ... ... ... ... ... ... ... ... Argentina 30,574 37,549 32,597 39,879 39,530 39,723 39,710 39,167 38,676 Armenia ... ... ... ... ... ... ... 3,979 3,979 Australia 27,743 35,020 35,206 30,349 29,050 27,803 27,572 26,277 25,796 Austria 13,406 15,740 14,369 14,299 13,353 12,723 11,587 11,321 11,100 Azerbaijan ... ... ... 3,273 3,400 3,215 4,104 3,862 4,363 Bahamas ... ... ... ... ... ... ... ... ... Bahrain ... ... ... ... ... ... ... ... ... Bangladesh 16,394 14,213 13,369 15,478 17,442 18,257 19,351 19,706 19,753 Barbados 154 146 114 106 ... ... ... ... ... Belarus ... ... ... ... ... ... 19,916 18,798 18,877 Belgium 18,376 19,704 20,052 18,082 16,633 15,101 15,463 15,775 15,486 Belize 95 141 117 ... ... ... ... ... ... Benin ... ... ... ... ... ... ... ... ... Bhutan ... ... ... ... ... ... ... ... ... Bolivia ... ... ... ... ... ... ... ... ... Bosnia and Herzegovina ... ... ... ... ... 3,470 3,999 4,529 4,877 Botswana ... ... ... ... ... ... ... ... ... Brazil 74,104 137,995 154,641 106,153 102,828 93,695 94,113 96,797 105,474 Brunei Darussalam ... ... ... ... ... ... ... ... ... Bulgaria 11,533 17,066 17,526 15,503 16,371 19,037 20,518 22,182 22,307 Burkina Faso 228 1,077 1,115 995 1,055 1,094 ... ... ... Burundi ... ... ... ... ... ... ... ... ... Cambodia ... ... ... ... ... ... ... ... ... Cameroon 1,078 1,283 ... ... ... ... ... ... ... Canada 50,959 67,094 44,888 48,489 46,862 46,752 46,099 45,444 44,982 Cape Verde ... ... ... ... ... ... ... ... ... Central African Republic ... 411 ... ... ... ... ... ... ... Chad ... ... ... ... ... ... ... ... ... Chile 7,447 10,644 9,953 11,192 11,753 12,285 12,859 13,064 ... China 371,110 765,762 1,617,078 1,681,181 1,683,169 1,678,086 1,683,730 1,695,221 1,706,334 China, Hong Kong SAR 7,951 9,461 ... ... ... ... ... ... ... China, Macao SAR ... ... ... ... ... ... ... ... ... Colombia 21,004 22,189 13,643 12,091 12,668 14,193 15,970 16,715 17,171 Comoros ... ... ... ... ... ... ... ... ... Congo 950 713 655 ... ... ... ... ... ... Congo, Democratic Republic of 4,078 3,123 3,893 3,008 3,375 3,148 2,976 2,733 2,820 Cook Islands ... ... ... ... ... ... ... ... ... Costa Rica ... ... ... ... ... ... ... ... ... Côte d'Ivoire 2,418 3,765 2,096 2,370 2,583 2,745 2,775 2,693 2,604 Croatia ... ... ... 10,694 9,995 9,625 9,210 8,758 8,445 Cuba ... ... ... ... ... ... ... ... ... Cyprus ... ... ... ... ... ... ... ... ... Czech Republic ... ... ... 19,274 15,494 13,722 12,563 ... ... Denmark 7,461 8,115 7,933 8,294 8,488 8,507 8,357 8,126 8,027 Djibouti ... ... ... ... ... ... ... ... ... Dominica ... ... ... ... ... ... ... ... ... Dominican Republic 2,158 3,396 4,398 4,351 4,117 4,121 4,057 4,082 ... Ecuador 1,602 3,932 ... 1,973 1,698 1,788 1,946 2,086 ... Egypt 14,152 33,945 41,072 42,524 46,152 49,343 51,008 52,000 51,995 El Salvador 2,061 2,472 ... 1,699 1,699 ... ... ... ... Equatorial Guinea ... ... ... ... ... ... ... ... ... Eritrea ... ... ... ... ... ... ... ... ... Estonia ... ... ... 2,460 2,460 ... ... ... ... Ethiopia ... ... ... ... ... ... ... ... ... Fiji 412 564 520 498 486 472 475 443 440 Finland 6,738 5,148 7,411 5,507 4,499 4,172 4,582 4,843 4,951 France 70,842 90,912 98,525 97,733 93,675 91,207 89,589 84,819 84,572 38 1970 1980 1990 1995 1996 1997 1998 1999 2000 Gabon ... 475 393 333 ... ... ... ... ... Gambia ... ... ... ... ... ... ... ... ... Georgia ... ... ... ... ... ... ... ... ... Germany 145,058 155,117 144,687 137,731 133,388 121,666 124,828 124,620 125,679 Ghana 1,596 1,824 1,849 1,662 1,693 1,683 ... ... ... Greece 17,187 25,767 28,893 34,197 31,892 31,144 31,857 30,924 29,025 Grenada ... ... ... ... ... ... ... ... ... Guatemala 2,141 2,425 ... 1,981 2,123 ... 3,490 3,557 3,500 Guinea ... ... ... ... ... ... ... ... ... Guinea-Bissau ... ... ... ... ... ... ... ... ... Guyana 499 581 274 ... ... ... ... ... ... Haiti 395 1,065 1,091 ... ... ... ... ... ... Honduras 1,588 2,337 2,670 2,390 2,393 ... ... 3,534 3,534 Hungary 23,175 27,227 25,969 23,592 20,919 20,714 ... 22,359 22,359 Iceland 331 397 496 479 488 466 457 431 431 India 63,792 79,023 58,206 69,839 73,249 75,631 77,733 74,920 74,537 Indonesia 33,983 81,761 127,975 165,633 178,297 190,038 195,586 201,469 203,779 Iran, Islamic Republic of 12,769 22,999 22,136 29,192 29,943 30,521 ... ... ... Iraq ... ... ... ... ... ... ... ... ... Ireland 5,108 6,743 6,309 6,579 6,243 6,357 6,313 6,796 6,854 Israel 4,062 5,797 7,478 8,387 8,143 ... ... ... ... Italy 73,733 100,061 96,144 91,886 90,770 92,445 94,035 96,500 100,609 Jamaica 1,347 1,195 1,291 1,235 1,198 1,176 1,128 1,074 1,038 Japan 226,242 311,269 309,275 317,550 319,851 329,633 328,487 331,889 319,705 Jordan 1,303 2,412 3,019 4,280 4,306 ... ... ... ... Kazakhstan ... ... ... 16,676 19,487 22,013 22,051 21,085 20,873 Kenya 2,538 4,617 6,432 4,825 4,742 ... ... ... ... Kiribati ... ... ... ... ... ... ... ... ... Korea, Democratic People's Republic of ... ... ... ... ... ... ... ... ... Korea, Republic of 43,385 68,515 95,438 100,520 101,799 103,549 102,615 101,456 98,664 Kuwait 2,011 2,957 2,034 3,030 2,812 2,735 2,740 2,421 2,088 Kyrgyzstan ... ... ... ... ... ... ... ... ... Lao People's Democratic Republic ... ... ... ... ... ... ... ... ... Latvia ... ... ... ... ... ... ... ... ... Lebanon ... ... ... ... ... ... ... ... ... Lesotho ... ... ... ... ... ... ... ... ... Liberia ... 290 ... ... ... ... ... ... ... Libyan Arab Jamahiriya 1,925 5,262 ... ... ... ... ... ... ... Lithuania ... ... ... 6,869 7,572 8,012 7,750 6,256 5,456 Luxembourg ... ... ... ... ... ... ... ... ... Macedonia, The former Yugoslav Republic of ... ... ... ... 3,679 3,786 3,619 3,795 3,693 Madagascar 1,043 2,049 1,941 2,447 2,726 3,047 3,085 ... ... Malawi 453 642 1,020 1,018 1,052 1,087 1,112 ... ... Malaysia 8,655 16,675 18,214 19,351 19,561 19,398 19,138 18,849 18,258 Maldives ... ... ... ... ... ... ... ... ... Mali ... ... 1,043 ... ... ... ... ... ... Malta 492 750 ... ... ... ... ... ... ... Marshall Islands ... ... ... ... ... ... ... ... ... Mauritania ... ... ... ... ... ... ... ... ... Mauritius 621 1,046 1,026 1,271 1,222 1,163 1,134 1,132 1,158 Mexico 40,797 53,983 50,574 49,720 49,321 48,975 49,488 49,174 49,130 Micronesia, Federated States of ... ... ... ... ... ... ... ... ... Moldova, Republic of ... ... ... ... ... ... ... ... ... Monaco ... ... ... ... ... ... ... ... ... Mongolia ... ... ... ... ... ... ... ... ... Morocco ... 13,129 14,039 14,564 14,352 14,496 14,251 14,052 13,817 Mozambique ... ... ... ... ... ... ... ... ... Myanmar ... ... ... ... ... ... ... ... ... Namibia ... ... ... ... ... ... ... ... ... Nauru ... ... ... ... ... ... ... ... ... Nepal 1,143 2,121 6,660 7,924 8,118 7,881 7,421 7,052 6,866 Netherlands 20,749 28,311 22,887 25,765 22,664 20,720 25,813 33,005 35,979 New Zealand 5,227 6,151 4,208 3,470 3,478 3,457 3,274 3,093 3,007 Nicaragua ... ... ... ... ... ... ... ... ... Niger ... ... ... ... ... ... ... ... ... Nigeria ... ... 9,790 9,784 ... ... ... ... ... Niue ... ... ... ... ... ... ... ... ... Norway ... 2,493 3,051 2,654 2,714 2,672 2,669 2,607 2,645 39 1970 1980 1990 1995 1996 1997 1998 1999 2000 Oman ... ... ... ... ... ... ... ... ... Pakistan 23,406 33,800 30,920 37,718 41,291 46,613 48,676 48,938 52,280 Palau ... ... ... ... ... ... ... ... ... Panama ... ... ... ... ... ... ... ... ... Papua New Guinea ... ... ... ... ... ... ... ... ... Paraguay 1,640 2,626 4,006 ... ... ... ... ... ... Peru ... 3,805 2,573 3,195 3,338 3,446 3,248 3,057 2,840 Philippines 40,917 58,889 66,955 70,674 69,122 75,051 71,910 72,967 73,958 Poland 73,188 92,151 91,984 93,699 92,460 89,953 90,112 84,821 77,117 Portugal 8,922 13,257 16,765 16,943 16,872 17,063 16,994 17,215 16,956 PuertoRico ... ... ... ... ... ... ... ... ... Qatar ... ... ... ... ... ... ... ... ... Romania ... ... ... 29,999 31,213 28,318 ... ... ... Russian Federation ... ... ... ... 225,243 245,343 282,262 308,963 320,673 Rwanda ... ... ... ... ... ... ... ... ... Saint Kitts and Nevis ... ... ... ... ... ... ... ... ... Saint Lucia ... ... ... ... ... ... ... ... ... Saint Vincent and the Grenadines ... ... ... ... ... ... ... ... ... Samoa ... ... ... ... ... ... ... ... ... San Marino ... ... ... ... ... ... ... ... ... Sao Tome and Principe ... ... ... ... ... ... ... ... ... Saudi Arabia ... ... ... ... ... ... ... ... ... Senegal ... 3,006 ... 1,603 1,732 1,565 ... ... ... Seychelles ... 88 77 75 87 90 73 58 51 Sierra Leone ... ... ... ... ... ... ... ... ... Singapore 3,438 4,302 ... ... ... ... ... ... ... Slovakia ... ... ... 8,337 9,088 9,710 10,100 9,123 8,816 Slovenia ... ... ... ... 4,890 4,847 4,755 4,636 4,574 Solomon Islands 23 30 25 127 148 143 147 145 ... Somalia ... ... ... ... ... ... ... ... ... South Africa 16,050 25,920 37,360 34,447 33,167 31,747 29,960 28,333 26,847 Spain 55,746 ... 79,870 82,681 82,332 86,327 90,082 95,262 96,003 Sri Lanka 3,109 5,095 5,154 5,256 5,134 5,214 5,111 5,045 4,791 Sudan ... ... ... ... ... ... ... ... ... Suriname 229 452 499 561 617 ... ... ... ... Swaziland ... ... ... ... ... ... ... ... ... Sweden 10,493 12,520 11,713 9,163 8,238 7,621 7,137 7,476 7,839 Switzerland 16,001 15,214 17,161 17,192 16,878 17,053 17,217 17,396 17,196 Syrian Arab Republic 2,786 8,248 6,887 10,631 10,712 10,662 11,047 11,268 11,479 Tajikistan ... ... ... ... ... ... ... ... ... Tanzania, United Republic of 2,769 3,285 3,546 3,633 3,492 3,384 ... ... ... Thailand 15,698 30,447 38,900 47,270 46,996 44,140 39,457 36,451 36,440 Timor Leste ... ... ... ... ... ... ... ... ... Togo ... ... ... ... ... ... ... ... ... Tokelau ... ... ... ... ... ... ... ... ... Tonga ... ... ... ... ... ... ... ... ... Trinidad and Tobago 824 986 760 784 992 1,251 1,184 964 647 Tunisia ... 6,004 8,351 9,212 9,525 9,646 10,459 11,361 11,678 Turkey 40,431 54,489 76,748 90,004 88,972 90,545 93,794 ... ... Turkmenistan ... ... ... ... ... ... ... ... ... Tuvalu ... ... ... ... ... ... ... ... ... Uganda 1,543 ... ... 1,568 1,661 1,780 1,777 1,779 ... Ukraine ... ... ... ... 51,889 55,554 57,394 54,239 49,916 United Arab Emirates ... ... ... ... ... ... ... ... ... United Kingdom 123,228 115,192 97,481 102,681 91,741 90,043 85,474 77,973 74,591 United States 549,472 637,450 535,597 515,201 514,564 503,461 486,094 470,935 463,745 Uruguay 3,141 ... ... 2,869 2,862 2,865 3,368 3,504 3,563 Uzbekistan ... ... ... 6,980 8,184 8,053 8,889 7,857 7,798 Vanuatu ... ... ... ... ... ... ... ... ... Venezuela, Bolivarian Republic of ... ... 16,010 16,759 ... ... ... ... ... Viet Nam ... ... ... 60,569 60,646 57,059 53,711 54,330 ... Yemen ... ... 5,902 5,900 6,397 6,494 ... ... ... Yugoslavia ... ... ... ... 7,289 9,586 11,270 14,480 14,630 Zambia 1,122 1,207 ... ... ... ... ... ... ... Zimbabwe 1,963 1,882 2,547 1,995 1,878 2,008 2,671 3,119 3,369 Czechoslovakia (Former) 27,831 29,725 28,099 ... ... ... ... ... ... USSR (Former) 375,256 424,624 389,116 361,875 ... ... ... ... ... Yugoslavia (Former Socialist Federal Republic) 32,476 53,845 52,972 ... ... ... ... ... ... 40 Appendix 6: Per capita cigarette consumption estimates, 1970-2000, selected years (3 year-moving- average) 1970 1980 1990 1995 1996 1997 1998 1999 2000 Afghanistan ... ... ... ... ... ... ... ... ... Albania ... ... ... ... 659 ... 796 882 1,027 Algeria 882 1,518 1,204 1,027 974 929 926 925 907 Andorra ... ... ... ... ... ... ... ... ... Angola 753 ... ... ... ... ... ... ... ... Antigua and Barbuda ... ... ... ... ... ... ... ... ... Argentina 1,790 1,924 1,445 1,614 1,573 1,555 1,530 1,486 1,456 Armenia ... ... ... ... ... ... ... 1,389 1,389 Australia 3,071 3,215 2,671 2,141 2,021 1,906 1,863 1,752 1,708 Austria 2,368 2,620 2,250 2,156 2,004 1,903 1,728 1,684 1,650 Azerbaijan ... ... ... 636 647 600 749 691 774 Bahamas ... ... ... ... ... ... ... ... ... Bahrain ... ... ... ... ... ... ... ... ... Bangladesh 448 298 210 211 232 236 243 241 234 Barbados 1,014 832 586 523 ... ... ... ... ... Belarus ... ... ... ... ... ... 2,422 2,281 2,285 Belgium 2,484 2,494 2,457 2,175 1,994 1,802 1,838 1,868 1,830 Belize 1,442 1,826 1,131 ... ... ... ... ... ... Benin ... ... ... ... ... ... ... ... ... Bhutan ... ... ... ... ... ... ... ... ... Bolivia ... ... ... ... ... ... ... ... ... Bosnia and Herzegovina ... ... ... ... ... 1,207 1,350 1,465 1,546 Botswana ... ... ... ... ... ... ... ... ... Brazil 1,319 1,834 1,601 976 925 824 808 813 869 Brunei Darussalam ... ... ... ... ... ... ... ... ... Bulgaria 1,752 2,473 2,526 2,254 2,391 2,795 3,029 3,293 3,322 Burkina Faso 76 302 241 188 194 199 ... ... ... Burundi ... ... ... ... ... ... ... ... ... Cambodia ... ... ... ... ... ... ... ... ... Cameroon 278 263 ... ... ... ... ... ... ... Canada 3,313 3,544 2,045 2,075 1,980 1,951 1,900 1,850 1,820 Cape Verde ... ... ... ... ... ... ... ... ... Central African Republic ... 304 ... ... ... ... ... ... ... Chad ... ... ... ... ... ... ... ... ... Chile 1,273 1,436 1,087 1,116 1,152 1,185 1,221 1,230 ... China 733 1,186 1,937 1,875 1,853 1,824 1,806 1,794 1,780 China, Hong Kong SAR 3,146 2,530 ... ... ... ... ... ... ... China, Macao SAR ... ... ... ... ... ... ... ... ... Colombia 1,689 1,316 612 478 489 535 589 604 614 Comoros ... ... ... ... ... ... ... ... ... Congo 1,312 776 538 ... ... ... ... ... ... Congo, Democratic Republic of 354 215 204 127 139 128 119 107 109 Cook Islands ... ... ... ... ... ... ... ... ... Costa Rica ... ... ... ... ... ... ... ... ... Côte d'Ivoire 791 821 306 297 314 324 318 300 285 Croatia ... ... ... 2,861 2,659 2,549 2,429 2,303 2,218 Cuba ... ... ... ... ... ... ... ... ... Cyprus ... ... ... ... ... ... ... ... ... Czech Republic ... ... ... 2,294 1,835 1,616 1,476 ... ... Denmark 1,966 2,002 1,861 1,920 1,962 1,963 1,927 1,871 1,847 Djibouti ... ... ... ... ... ... ... ... ... Dominica ... ... ... ... ... ... ... ... ... Dominican Republic 912 1,033 1,000 890 820 800 767 762 ... Ecuador 474 849 ... 272 226 232 245 259 ... Egypt 674 1,282 1,217 1,111 1,174 1,221 1,229 1,219 1,201 El Salvador 1,050 980 ... 472 472 ... ... ... ... Equatorial Guinea ... ... ... ... ... ... ... ... ... Eritrea ... ... ... ... ... ... ... ... ... Estonia ... ... ... 2,092 2,092 ... ... ... ... Etiopía ... ... ... ... ... ... ... ... ... Fiji 1,372 1,460 1,155 1,011 965 920 908 833 819 Finland 1,929 1,351 1,842 1,333 1,083 998 1,091 1,148 1,171 France 1,847 2,172 2,178 2,089 1,990 1,927 1,882 1,772 1,757 41 1970 1980 1990 1995 1996 1997 1998 1999 2000 Gabon ... 1,043 666 506 ... ... ... ... ... Gambia ... ... ... ... ... ... ... ... ... Georgia ... ... ... ... ... ... ... ... ... Germany 2,410 2,431 2,170 2,015 1,945 1,768 1,810 1,803 1,814 Ghana 336 307 223 171 168 164 ... ... ... Greece 2,592 3,464 3,521 3,938 3,639 3,520 3,576 3,452 3,230 Grenada ... ... ... ... ... ... ... ... ... Guatemala 742 651 ... 361 382 ... 571 572 553 Guinea ... ... ... ... ... ... ... ... ... Guinea-Bissau ... ... ... ... ... ... ... ... ... Guyana 1,330 1,296 591 ... ... ... ... ... ... Haiti 323 335 280 ... ... ... ... ... ... Honduras 1,167 1,244 985 757 745 ... ... 960 960 Hungary 2,820 3,257 3,140 2,823 2,503 2,480 ... 2,697 2,697 Iceland 2,374 2,402 2,596 2,368 2,385 2,253 2,182 2,035 2,013 India 191 187 108 116 119 121 121 114 112 Indonesia 483 911 1,096 1,255 1,321 1,379 1,388 1,400 1,388 Iran, Islamic Republic of 790 1,050 678 792 789 791 ... ... ... Iraq ... ... ... ... ... ... ... ... ... Ireland 2,497 2,859 2,467 2,405 2,246 2,245 2,186 2,316 2,316 Israel 2,063 2,304 2,406 2,223 2,118 ... ... ... ... Italy 1,811 2,282 2,016 1,886 1,857 1,886 1,914 1,960 2,041 Jamaica 1,350 937 840 755 721 698 659 618 592 Japan 2,835 3,486 3,068 3,012 3,013 3,086 3,059 3,076 2,950 Jordan 1,449 2,129 1,734 1,725 1,686 ... ... ... ... Kazakhstan ... ... ... 1,428 1,667 1,880 1,879 1,791 1,771 Kenya 429 565 541 329 316 ... ... ... ... Kiribati ... ... ... ... ... ... ... ... ... Korea, Democratic People's ... ... ... ... ... ... ... ... ... Republic of Korea, Republic of 2,304 2,721 3,002 2,916 2,909 2,915 2,848 2,778 2,668 Kuwait 4,644 3,633 1,512 3,003 2,777 2,584 2,409 2,000 1,616 Kyrgyzstan ... ... ... ... ... ... ... ... ... Lao People's Democratic ... ... ... ... ... ... ... ... ... Republic Latvia ... ... ... ... ... ... ... ... ... Lebanon ... ... ... ... ... ... ... ... ... Lesotho ... ... ... ... ... ... ... ... ... Liberia ... 273 ... ... ... ... ... ... ... Libyan Arab Jamahiriya 1,729 3,231 ... ... ... ... ... ... ... Lithuania ... ... ... 2,360 2,595 2,736 2,635 2,116 1,839 Luxembourg ... ... ... ... ... ... ... ... ... Macedonia, The former Yugoslav ... ... ... ... 2,443 2,497 2,354 2,441 2,360 Republic of Madagascar 269 410 295 320 347 377 376 ... ... Malawi 185 198 205 190 193 194 196 ... ... Malaysia 1,415 1,999 1,608 1,509 1,487 1,433 1,378 1,322 1,262 Maldives ... ... ... ... ... ... ... ... ... Mali ... ... 220 ... ... ... ... ... ... Malta 2,236 3,008 ... ... ... ... ... ... ... Marshall Islands ... ... ... ... ... ... ... ... ... Mauritania ... ... ... ... ... ... ... ... ... Mauritius 1,316 1,682 1,381 1,575 1,491 1,400 1,346 1,326 1,349 Mexico 1,484 1,456 988 846 819 794 783 761 752 Micronesia, Federated States of ... ... ... ... ... ... ... ... ... Moldova, Republic of ... ... ... ... ... ... ... ... ... Monaco ... ... ... ... ... ... ... ... ... Mongolia ... ... ... ... ... ... ... ... ... Morocco ... 1,193 933 852 817 803 769 739 717 Mozambique ... ... ... ... ... ... ... ... ... Myanmar ... ... ... ... ... ... ... ... ... Namibia ... ... ... ... ... ... ... ... ... Nauru ... ... ... ... ... ... ... ... ... Nepal 159 245 622 659 660 626 575 533 512 Netherlands 2,172 2,581 1,872 2,044 1,789 1,623 2,011 2,559 2,775 New Zealand 2,687 2,695 1,633 1,252 1,241 1,221 1,146 1,073 1,038 Nicaragua ... ... ... ... ... ... ... ... ... Niger ... ... ... ... ... ... ... ... ... Nigeria ... ... 212 185 ... ... ... ... ... Niue ... ... ... ... ... ... ... ... ... Norway ... 784 888 756 770 755 751 730 739 42 1970 1980 1990 1995 1996 1997 1998 1999 2000 Oman ... ... ... ... ... ... ... ... ... Pakistan 643 714 486 530 564 621 629 614 635 Palau ... ... ... ... ... ... ... ... ... Panama ... ... ... ... ... ... ... ... ... Poland 3,039 3,420 3,222 3,145 3,074 2,961 2,939 2,743 2,473 Portugal 1,440 1,835 2,116 2,078 2,059 2,071 2,053 2,071 2,036 PuertoRico ... ... ... ... ... ... ... ... ... Qatar ... ... ... ... ... ... ... ... ... Romania ... ... ... 1,663 1,726 1,563 ... ... ... Russian Federation ... ... ... ... 1,916 2,081 2,385 2,598 2,691 Rwanda ... ... ... ... ... ... ... ... ... Saint Kitts and Nevis ... ... ... ... ... ... ... ... ... Saint Lucia ... ... ... ... ... ... ... ... ... Saint Vincent and the Grenadines ... ... ... ... ... ... ... ... ... Samoa ... ... ... ... ... ... ... ... ... San Marino ... ... ... ... ... ... ... ... ... Sao Tome and Principe ... ... ... ... ... ... ... ... ... Saudi Arabia ... ... ... ... ... ... ... ... ... Senegal ... 995 ... 351 371 330 ... ... ... Seychelles ... ... ... ... ... ... ... ... ... Sierra Leone ... ... ... ... ... ... ... ... ... Singapore 2,658 2,440 ... ... ... ... ... ... ... Slovakia ... ... ... 2,006 2,166 2,293 2,363 2,119 2,039 Slovenia ... ... ... ... 2,979 2,944 2,872 2,786 2,742 Solomon Islands 257 253 147 611 694 643 638 620 ... Somalia ... ... ... ... ... ... ... ... ... South Africa 1,220 1,528 1,664 1,345 1,264 1,182 1,091 1,011 941 Spain 2,278 ... 2,520 2,496 2,469 2,572 2,669 2,810 2,826 Sri Lanka 415 536 446 414 397 395 380 369 344 Sudan ... ... ... ... ... ... ... ... ... Suriname 1,186 2,155 1,943 2,088 2,285 ... ... ... ... Swaziland ... ... ... ... ... ... ... ... ... Sweden 1,644 1,874 1,668 1,280 1,148 1,060 991 1,036 1,085 Switzerland 3,377 2,997 3,021 2,916 2,851 2,871 2,892 2,917 2,880 Syrian Arab Republic 854 1,834 1,062 1,357 1,313 1,255 1,249 1,224 1,223 Tajikistan ... ... ... ... ... ... ... ... ... Tanzania, United Republic of 373 333 254 218 204 194 ... ... ... Thailand 774 1,087 1,043 1,128 1,099 1,014 889 805 798 Timor Leste ... ... ... ... ... ... ... ... ... Togo ... ... ... ... ... ... ... ... ... Tokelau ... ... ... ... ... ... ... ... ... Tonga ... ... ... ... ... ... ... ... ... Trinidad and Tobago 1,452 1,388 939 890 1,104 1,362 1,271 1,019 673 Tunisia ... 1,594 1,637 1,562 1,574 1,551 1,644 1,746 1,775 Turkey 1,914 2,006 2,101 2,164 2,084 2,068 2,118 ... ... Turkmenistan ... ... ... ... ... ... ... ... ... Tuvalu ... ... ... ... ... ... ... ... ... Uganda 304 ... ... 152 156 163 159 157 ... Ukraine ... ... ... ... 1,268 1,358 1,405 1,329 1,225 United Arab Emirates ... ... ... ... ... ... ... ... ... United Kingdom 2,920 2,586 2,094 2,174 1,935 1,893 1,790 1,627 1,553 United States 3,618 3,572 2,692 2,464 2,434 2,354 2,246 2,150 2,092 Uruguay 1,551 ... ... 1,185 1,177 1,167 1,362 1,407 1,425 Uzbekistan ... ... ... 507 579 554 594 512 501 Vanuatu ... ... ... ... ... ... ... ... ... Venezuela, Bolivarian Republic of ... ... 1,310 1,221 ... ... ... ... ... Viet Nam ... ... ... 1,317 1,290 1,183 1,085 1,084 ... Yemen ... ... 991 765 797 794 ... ... ... Yugoslavia ... ... ... ... 876 1,148 1,345 1,722 1,736 Zambia 489 392 ... ... ... ... ... ... ... 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