APPENDIX I: The Data

The data sources for this study are the World Bank, the United Nations, the Stockholm International Peace Research Institute (SIPRI), the US Arms Control and Disarmament Agency (ACDA), and the U.S. Central Intelligence Agency, in addition to external Fund publications. In a number of cases, published national accounts were used as a supplement. The military expenditure figures are derived primarily from SIPRI. The SIPRI estimates are useful because they are provided in local currency. Furthermore they are more reliable because their coverage is clearly defined, comprehensive, and consistently applied to each country. Two types of modification to the SIPRI data are applied. First, a number of countries are omitted from the SIPRI data. Most of these countries are small enough that their exclusion is unlikely to materially affect the findings. However, SIPRI does not provide estimates of military expenditures of the U.S.S.R. and China, two extremely important military powers.

The data base uses ACDA estimates for China military expenditures, the only known time series source. In the case of the U.S.S.R., estimates of military expenditures are based on Steinberg (1990). The main advantage of Steinberg’s estimates is that they are provided in current rubles, whereas the ACDA data are in U.S. dollars. Furthermore, Steinberg’s definition is comprehensive and compatible with SIPRI’s definition. Steinberg’s methodology starts with published U.S.S.R. military expenditures and adds unpublished military expenditures, estimated by attributing unaccounted expenditures in the U.S.S.R. national accounts to the military. Since this methodology produces upper-limit estimates of military expenditures, an adjustment is made. On the basis of alternative annual estimates of U.S.S.R. military expenditures -- see Deger and Sen (1990), SIPRI Yearbooks, ACDA -- a reasonable figure for 1989 military expenditures is 105 to 110 billion rubles. Since Steinberg’s figure for that year is 120 billion rubles, this implies a 10 percent overestimation. ^1/ Therefore, on the basis of this comparison, a 10 percent downward adjustment was applied to the entire Steinberg time series of U.S.S.R. military expenditures. The reader is cautioned that the military expenditure figures of both the U.S.S.R. and China are not as reliable as the other figures. However, it seems likely that they provide a credible estimate of the trend.

The second major modification to the SIPRI data concerns the coverage or definition of military expenditures. As explained in ^{Section II}, the SIPRI figures do not include foreign aid financed expenditures in the military expenditures of the recipient nations. The reasons for this are probably practical; many nations do not include foreign-financed military expenditures in their government budget and, therefore, accurate estimates would be difficult to compile. The SIPRI figures therefore are meant to indicate the domestic opportunity cost of government appropriations to the military. Foreign aid-financed military expenditures are deemed to have no domestic opportunity cost.

There are a number of inherent weaknesses in the SIPRI definition that lead to potentially serious underestimates of even the domestic cost of the military in the long run. One problem stems from the fact that a certain portion of military aid is given in the form of loans to be repaid in the future and therefore carry an interest cost. For the SIPRI definition to be fully consistent, the costs of military loan repayments and interest payments must be added. However, such adjustments are inherently difficult to make because foreign-interest payments and loan repayments tend to be lumped together in government accounts. In most countries, it is impossible to follow the progress of individual loans.

There are two additional problems with the SIPRI figures. It is likely that a large portion, if not all, of foreign-financed acquisitions of military equipment and supplies are not covered in the SIPRI definition of military expenditure because many governments treat all foreign-financed military expenditures as off-budget items. Thus, in developing countries it is likely that military purchases financed by commercial foreign credit as well as military aid are not contained in the government accounts and are therefore missed in the SIPRI figures. An additional problem is that, in a macroeconomic sense, it is very likely that there is an indirect domestic opportunity cost for military expenditures financed through military aid. Military aid is to some degree fungible. A nation that receives military aid can divert funds formerly intended for the military to other uses simply by lowering domestic military expenditures below originally planned levels. Furthermore, the exact distinction between economic assistance and military assistance is at times murky.

For these reasons, it is preferable to define the military expenditures of a nation as consisting of all military expenditures, regardless of the means of financing, consistent with Fund accounting methods. Ideally, this can be accomplished by adding the off-budget military expenditures to the SIPRI figures. There are reasonably reliable figures from ACDA on the level of foreign military purchases. Furthermore, in a number of cases the foreign purchases exceed the SIPRI military expenditures. It is quite clear in these cases that they have been excluded and that an adjustment to the SIPRI military expenditure figures is warranted. However, there is no sure way of knowing to what extent foreign purchases are off-budget items for individual countries. Therefore, one is faced with the dilemma of using SIPRI military expenditure figures that are known to systematically underestimate military expenditure or of relying on imperfect means of adjusting the data to offset the error.

To correct for the measurement error, an alternative set of military expenditure figures has been constructed on a formula basis. The resulting estimates, the Adjusted SIPRI figures, must therefore be viewed as simulations rather than as concrete estimates. They are not meant to be interpreted as actual military expenditure figures in individual cases but are an estimate of the total funds made available to the military, provided the assumptions delineated below are reasonably accurate.

The Adjusted SIPRI military expenditures are constructed from arms imports data provided by ACDA, supplemented with U.S. foreign military aid figures. A three-year moving average is used to diffuse any problems associated with the timing of deliveries. The following assumptions are then applied.

1. Net creditor nations that purchased military goods from industrial countries are assumed to have paid for the equipment and to have reported these purchases within their military budgets, therefore no adjustment is needed. The same assumption is applied to purchases by industrial countries. ^1/

2. For other developing nations that acquired military goods from industrial countries, it was assumed that 80 percent of the arms purchases are unrecorded in the SIPRI figures, due to grant and credit financing. Brzoska (1990) estimates that 50 percent of arms sales by the U.S. are funded either through grants or credits. Since these figures include sales to other industrial nations and net creditor nations as well as developing nations, they are consistent with the 80 percent assumption used herein.

3. Owing to the way SIPRI military expenditures are estimated, as outlined in the text, the larger figure of aid versus arms imports was used for major U. S. military aid recipients.

4. The valuation of Eastern European military equipment presented a problem because most transactions are not subject to market influences. In order to avoid too much reliance on politically sensitive information sources, it is assumed that the total value of unrecorded arms transfers from Eastern Europe to developing nations equaled the total unrecorded arms transfers from the industrial countries to developing nations in 1972-88. This assumption relies on the notion that the military balance of power between the Eastern bloc and the Western bloc has on average been at parity with respect to supplying arms to the third world on a concessional basis. Applying this assumption leads to an average yearly transfer of $5.9 billion from 1972 to 1988 to developing nations from both sides. The implied weight on the ACDA valuation of Eastern European arms transfers to developing nations is 52.5 percent. Compared with the 80 percent factor used for industrial countries, this is an effective discount of 35 percent on the ACDA valuations of Eastern European military arms. See Brzoska (1990) for a discussion of the valuation problems associated with arms transfers from Eastern European countries.

5. An adjustment was also made for transfers between the U.S.S.R. and other Eastern European nations based on the same formula (52.5 percent).

One of the primary conclusions that is derived from the analysis of the SIPRI data as opposed to the Adjusted SIPRI data is that the seemingly major adjustment has only a minor impact on the results. To the extent that the adjustment for foreign acquisitions of military equipment does not change the findings, the adjustment confirms that the SIPRI estimates are a workable basis for assessing the level of military expenditures. In the few cases where there is a large impact, the reader is cautioned to confirm the accuracy of the Adjusted SIPRI estimates for the country before drawing any policy conclusions. One desirable outcome of this research would be the generation of studies that check the accuracy of the estimates of military expenditures in a variety of countries.

All the share figures in the text are based on official exchange rates. Official exchange rates do not always provide a reliable means of comparison for a number of reasons. Serious differences exist between the price structures in different countries. The official rates of exchange are often administered prices rather than market clearing prices. Finally, the market clearing exchange rate does not necessarily reflect real purchasing power of incomes within each country. An alternative measure, purchasing power parity (PPP), designed to indicate real purchasing power of currencies, has been developed over the years. Table 7 shows four alternative comparisons of the share of world military expenditure in 1980 based on PPP estimates from Summers and Heston (1988), using real growth rates to update their figure for 1986, 1987, and 1988. Column 1 shows SIPRI military expenditure shares based on official exchange rates, column 2 Heston’s (1990) data based on official exchange rates, column 3 the converted SIPRI military expenditure shares based on PPP exchange rates, and column 4 Heston’s data based on PPP. ^1/

The PPP conversion leads to a substantial share decrease for industrial countries (by one fourth) and a tripling or doubling of the share for the Asian developing countries. The relative shares of the other groups are reasonably invariant between the two methods. These results indicate that the real GDP of Southeast Asian countries is under-represented by official exchange rates. However, the degree of correction is questionable. For instance, behind the Column 3 shares, the PPP valuations of U.S.S.R., U.S. and Chinese military spending in 1980 are virtually equal, a most unlikely coincidence. Thus, although PPP conversions indicate the direction of error that the official exchange rates engender, they clearly exaggerate the extent of the error with respect to military expenditure. There may be a problem with cost versus value.

APPENDIX II: Economic Theory of Defense and Military Expenditure

This appendix provides a review of the public finance theory of defense, along the lines of Stiglitz (1988). First, the relationship between military expenditures and defense needs clarification. Economists generally consider military expenditures to be an input or a cost of providing defense. Defense is therefore an output, ideally measured by the level of security from external attack provided by alternative levels of military expenditures, given the external political environment. However, much like the notion of utility, the notion of defense is somewhat fictitious and cardinal numerical scales of the level of security probably have little meaning. Furthermore, the level of defense is a monotonic function of military expenditures and military expenditure is a suitable proxy for the level of defense, provided the efficiency factor remains constant.

Traditional public finance theory offers an extensive analysis of the optimal level of government expenditures on public goods. Since defense is a textbook example of a pure public good that exhibits the characteristics of nonrival consumption and nonexcludability, it appears to be an ideal case for the application of this theory. ^1/ However, defense combines a series of separate market failures and therefore does not lend itself to traditional public finance treatment. In essence, the optimal level of military expenditure is a political, normative, and moral issue and is not amenable to economic analysis. These factors lead to the conclusion that the role of economics in analyzing military expenditures is somewhat different from other areas of public policy. Economic analysis is well suited to measuring the economic costs of the military; for instance, the types of economic trade-offs that exist and the impact of military expenditures on economic growth. Economic and statistical techniques can be used to analyze the political and economic factors that appear to influence the demand for military spending and thus provide a better understanding of the motivations involved in choosing a given level of defense. The area where economics is quite limited is in determining the proper level of military expenditure.

One can see the difficulty in applying the traditional theory of public goods to military expenditures by examining some of the details of the theory. The optimal expenditure on a public good is the level that equates total marginal willingness to pay with marginal cost of supply. This implies that the mix and size of the budget should be based upon aggregate demand for military expenditures and other government goods, in conjunction with technical cost data. Whether or not the government chooses to follow policies that reflect the wishes of the population will depend upon the efficacy of the political choice mechanism. Furthermore, the social demand for government goods is meaningful only when consumer preferences are reasonably exogenous to the political process and consumers are sufficiently well informed to form meaningful demand functions for the various potential items of public expenditure.

One of the most serious problems in applying the above theory to defense arises from the difficulty of making assessments of the personal utility impact of military expenditures. There is little agreement among experts regarding the link between military expenditures and defense benefits. The major points of disagreement are on the dangers of invasion, the impact of military expenditures in preventing invasion, the defense value of alternative weapons systems, and the extent to which military expenditures promote other national goals. Furthermore, the public at large is notoriously poorly informed about the level and composition of military spending. ^1/ Given these severe informational problems, it is not clear whether popular perceptions, as indicated by public demand, are relevant to the optimal level of military expenditures -- summing the individual demand for defense does not carry the same kind of compelling interpretation as with park expenditures or roads.

Another complicating factor is that demand for military expenditures is to a large extent endogenous in the political system. The stance and actions of a nation’s political leaders influence perceived demand for military expenditures. Furthermore, the level of military expenditure and the political stance of neighboring states can also have an effect. Explicit endogeneity of demand and interdependence violates a major premise behind the economic analysis of the optimal level of government expenditure.

A further complication results from uncertainties regarding the eventual use of military power. Since defensive capabilities can be used for internal control, military expenditures can be beneficial to certain groups in a country while being detrimental to other sectors of the population. When the military functions primarily to influence domestic political events, defense loses its justification as a public good and the standard analysis of optimal supply has no relevance. Instead, there is likely to be a zero-sum game or an overall decrease in social welfare (a negative-sum game).

Finally, the global perspective on military expenditures is almost the polar opposite of the domestic perspective. Internationally, defense expenditures are welfare diminishing. In a simple two-state world, military expenditures of one nation have negative utility consequences for the other nation. In this manner, just like trade barriers, noncooperating states will spend too much on the military. There is a prisoner’s dilemma -- a simultaneous decrease in military expenditures that does not alter the strategic balance will increase the welfare of both nations. This conclusion can easily be extended to more complicated settings where competing alliances exist in the context of many nations. Although allies will benefit from military expenditures, the welfare losses of rivals will on average outweigh these gains. This international aspect of defense means that defense is indeed an unusual public good. While infrastructure and human capital expenditures increase the world productive capacity and therefore unambiguously improve global welfare, the domestic benefits of military expenditures are generally offset by the disutility they impose on those living outside the security zone.

To understand the implications of the international negative externality, consider a new nation that is contemplating the guidelines for its new government. Domestically, defense is both a public good and a merit good. If the nation chooses to rely on individual initiative to support defense, the projected support from voluntary private contributions would be relatively low. Government technocrats could increase social welfare by funding defense with tax revenue and increasing total expenditures. However, an even greater welfare-improving solution would be for the technocrats to negotiate with technocrats in other nations to agree on a mutually beneficial low level of military expenditures in each country. Ironically, the international cooperative solution could conceivably result in lower levels of defense expenditure than would have arisen from voluntary contributions. However, the international cooperative solution is very difficult to obtain. It is similar to a cartel arrangement and carries all the difficulties involved as such, including natural incentive to cheat (or, equivalently, remaining outside the cartel can be welfare improving for any single country).

In the absence of a cooperative solution, economic theory suggests a hypothetical correction for the negative externality. A global international agency with the proper authority could improve global welfare by imposing a military fine on each nation. The agency could then simply return the money to national governments on a formula basis. Under fairly reasonable assumptions, national defense budget decreases would be sufficient to pay the national fines, even if the revenue were not returned. ^1/ Therefore, each and every country would be better off.

APPENDIX III: Military Expenditures and Economic Growth

The controversial issue of how military expenditures affect the economic growth of a nation has given rise to numerous theoretical and empirical studies. Appendix Table 13 reproduces the results of four cross-section empirical studies of the relationship between defense spending and economic growth. Benoit is credited with first proposing the thesis that military expenditures are not necessarily detrimental to national growth. For instance in Benoit (1978), the dependent variable is the average annual growth rate between 1950 and 1965 (Table 13.B). The independent variables -- private investment as a proportion of GDP, net economic assistance, and defense spending -- all have a positive impact on growth; however, defense spending is significant only at the 80 percent level of confidence. From this latter result, one can conclude with a 90 percent level of confidence that the effect of defense spending is non-negative. This disproves Benoit’s maintained hypothesis that defense expenditures have a negative impact on growth. Frederiksen and Looney (1982) derive virtually identical results in a retest of Benoit’s hypothesis using data from 1960-78 (Table 13.C). Investment and military expenditures are positively associated with growth, but the t-ratio for military expenditure is marginally insignificant.

The econometric formulation of these two studies has been widely criticized. In a simple OLS model, there is no attempt to analyze the transmission mechanism between military expenditure and growth. Deger and Smith (1983) carried out a much more sophisticated analysis of growth in a well-formulated simultaneous equations model (Table 13.D). The three dependent variables in the system are GDP growth, the ratio of savings to GDP, and the ratio of military expenditures to GDP. In summary, their findings show that the direct impact of military expenditures on growth is indeed positive and significant. However, the effect of military expenditures on the savings ratio is negative and significant, and the latter’s impact on growth is positive and significant. Therefore, in total, military expenditures have a negative effect on growth because the negative indirect effect is of a higher order of magnitude than the positive direct effect.

On the basis of these three studies, statisticians would tend to support the finding that the correlation between growth and the military is negative since the simultaneous equations model is more sophisticated. However, the causes of growth are still an unsolved mystery to economists and in all likelihood, the simultaneous equations model is also misspecified -- as indicated by the R-square of 23 percent in the growth equation, which is much lower than that associated with their other equations. An alternative specification could reverse the results again. Until it is possible to adequately explain growth, it is impossible to provide definitive empirical conclusions as to the impact of military expenditures on growth.

An alternative method of investigating the growth implications of military expenditures is a micro approach, which involves a disaggregated examination of the composition of military expenditures. The object is to determine which elements of the military budget might have growth-enhancing effects and which elements exclusively provide defense benefits. Such an approach, explained in more detail below, is more compelling than the macro approach because it focuses on the resource allocation issue in a long-run context -- how military expenditure will affect growth in a long-run context when sustained high or low levels of military expenditure are maintained.

The methodology is relatively straightforward, though tedious, and involves measuring how or to what extent expenditures increase civilian productivity. In this manner, a certain percentage of military expenditure can be identified as investment expenditure and the remaining portion is definitionally regarded as consumption expenditure. The first-round growth-enhancing expenditures of the military are as follows. The military can increase civilian productivity by providing public infrastructure, such as roads or port facilities that are used by private businesses or consumers. ^1/ These infrastructure expenditures should be discounted to the extent that they are not available for private use or to the extent that they are not useful to the public (such as an isolated border road). The next channel through which the military can enhance civilian output is through training. The discounted value of the human capital of demobilized soldiers enhances civilian productivity. Finally, research and development activities of the military can enhance civilian productivity provided they have civilian applications.

The extent to which military expenditure is equivalent to government provision of economic services depends upon the composition of military expenditure. The decomposition process will undoubtedly find that in most countries military expenditures are more productive than government consumption expenditures (e.g., government administrative costs and transfer programs), but less productive than government provision of economic services (e.g., support of development projects). There are numerous secondary considerations that might shift the weighting factor in one direction or the other. For instance, to some extent the military has preferential access to scarce resources. There may also be some more remote ways in which military expenditure enhances civilian productivity that would become apparent in conducting the analysis.

The final impact of military expenditures on growth will then depend upon the alternative use of military funds. All growth benefits attributed to the military can be achieved more efficiently and at a lower cost with a program that directly sets out to achieve that purpose -- for instance, education and health expenditures are more efficient means of enhancing human capital; public works programs are more efficient means of providing rural infrastructure. Therefore, defense spending can promote growth if it crowds out (or replaces) private consumption or government consumptive expenditures; however, its impact on growth will be negative if the alternative use of funds is either private investment or reasonably efficient government infrastructure. ^1/ Furthermore, the impact of military expenditures on growth will vary in time and place. Inconsistent empirical findings, as in fact exist, are predicted.

In line with the micro approach, Aschauer (1989) conducted an empirical test of the productivity of military expenditure (Table 13.A). These results indicate that in the United States, government expenditure on infrastructure is found to have a positive and significant effect on growth while defense capital expenditures have virtually no impact. Thus, these initial findings indicate that the positive impact of military spending on civilian production is insignificant. However, these results are subject to verification in other countries and in other time periods.

Finally, a major distinction must be made between countries that are net importers of military goods and those that are net exporters of military goods. In net exporting countries, the military increases the level of available foreign exchange for alternative uses. From the perspective of the economy, profit-making arms for export industries are an effective means of increasing the country’s productive capacity. However, governments tend to subsidize the arms industry, in which case, as with any other subsidized industry, such actions represent an inefficient use of resources, and the contribution of such businesses to the economy is likely to be negative.

Table 6.

Categories of Countries

^1/Heavily indebted countries are nations with an external debt to exports ratio in excess of 3 and an external debt to GDP ratio in excess of 0.8. Nations that met these criteria that are not in the WEO list were Congo, Costa Rica, Egypt, and Nicaragua. The countries that were deleted from the WEO list were Colombia, Uruguay, and Yugoslavia.

^2/Small low-income economies: This category consists of nations with a per capita income of less than USS400 in 1980 and a population less than 50 million. Bangladesh and Pakistan were eliminated from the WEO list of small low-income economies group since they rank eighth and ninth in population among the world nations.

^3/Industrial nations: Singapore was added to the WEO list.

^4/ Eastern Europe: This is another category that was created to replace “other Europe.” It includes Yugos Lavia in addition to the Warsaw treaty organization members.

^5/North Africa and sub-Saharan Africa replace the WEO category of Africa.

^6/These two countries are now united.

^*Countries included in the GFS data, ^{Table 5}.

Note: The term “country” used in this report does not in all cases refer to a territorial entity that is a state as understood by international Law and practice. The term also covers some territorial entities that are not states but for which statistical data are maintained and provided internationally on a separate and independent basis.

Table 6.

Categories of Countries

Net Creditor		Heavily Indebted Middle-Income 1/	Small Low-income Economies 2/		Industrialized 3/		Sub-Saharan Africa 5/		North Africa 5/		Latin America and The Caribbean		Eastern Europe 4/		Asian Developing		Middle East
Iran		Argentina	Benin		Australia		Angola		Algeria		Argentina		Bulgaria		Bangladesh*		Bahrain*
Kuwait		Bolivia	Burkina Faso*		Austria		Benin		Egypt*		Bolivia		Czechoslovakia		China		Cyprus*
Libya		Brazil	Burundi		Belgium		Botswana*		Libya		Brazil		German Democratic		Fiji*		Iran*
Oman		Chile*	Cameroon*		Canada		Burkina Faso*		Morocco*		Chile*			Republic	India*		Iraq
Saudi Arabia		Congo	Central African Denmark				Burundi			Tunisia*	Colombia		Hungary		Indonesia*		Israel*
Taiwan		Costa Rica*		Rebublic	Finland		Cameroon*				Costa Rica*		Poland		Korea*		Jordan*
	Province of	Côte d’ Ivoire	Chad		France		Central African				Cuba		Romania		Malaysia		Kuwait*
	China	Ecuador*	Ethiopia*		Federal Rebublic			Republic	Dominican		USSRs Lavia		Myanmar*		Lebanon
United Arab		Egypt*	Ghana*			of Germany	Chad					Republic*	Yugos Lavia		Nepal*		Oman*
Emirates		Mexico*	Guinea-Bissau		Greece		Congo				Ecuador*				Pakistan*		Saudi Arabia
		Morocco*	Guyana		Ireland		Cote d’lvoire				El Salvador*				Philippines*		Syrian AR
		Nicaragua	Haiti		Italy		Ethiopia*				Guatemala*				Sri Lanka*		Turkey*
		Nigeria*	Kenya*		Japan		Gabon				Guyana				Taiwan		United Arab
		Peru*	Liberia*		Luxembourg		Ghana*				Haiti					Province of		Emirates
		Philippines*	Madagascar		Netherlands		Guinea-Bissau				Honduras					China	Yemen Ar 6/*
		Venezuela*	Malawi*		Norway		Kenya*				Jamaica				Thailand		Yemen PDR
			Mali*		Portugal		Liberia*				Mexico*
			Mauritania		Singapore		Madagascar				Nicaragua
			Mozambique		Spain		Malawi*				Panama*
			Myanmar*		Sweden		Mali*				Paraguay*
			Nepal*		Switzerland		Mauritania				Peru*
			Niger		United Kingdom		Mauritus*				Trinidad &
			Rwanda		United States		Mozambique					Tobago
			Senegal				Niger				Uruguay*
			Sierra Leone				Nigeria*				Venezuela*
			Somalia				Rwanda
			Sri Lanka				Senegal
			Sudan				Sierra Leone
			Tanzania				Somalia
			Togo*				South Africa
			Uganda*				Sudan
			Zaire				Swaziland*
			Zambia*				Tanzania
							Togo*
							Uganda*
							Zaire
							Zambia*
							Zimbabwe*

^1/Heavily indebted countries are nations with an external debt to exports ratio in excess of 3 and an external debt to GDP ratio in excess of 0.8. Nations that met these criteria that are not in the WEO list were Congo, Costa Rica, Egypt, and Nicaragua. The countries that were deleted from the WEO list were Colombia, Uruguay, and Yugoslavia.

^2/Small low-income economies: This category consists of nations with a per capita income of less than USS400 in 1980 and a population less than 50 million. Bangladesh and Pakistan were eliminated from the WEO list of small low-income economies group since they rank eighth and ninth in population among the world nations.

^3/Industrial nations: Singapore was added to the WEO list.

^4/ Eastern Europe: This is another category that was created to replace “other Europe.” It includes Yugos Lavia in addition to the Warsaw treaty organization members.

^5/North Africa and sub-Saharan Africa replace the WEO category of Africa.

^6/These two countries are now united.

^*Countries included in the GFS data, ^{Table 5}.

Note: The term “country” used in this report does not in all cases refer to a territorial entity that is a state as understood by international Law and practice. The term also covers some territorial entities that are not states but for which statistical data are maintained and provided internationally on a separate and independent basis.

View Table

Table 6.

Categories of Countries

Net Creditor		Heavily Indebted Middle-Income 1/	Small Low-income Economies 2/		Industrialized 3/		Sub-Saharan Africa 5/		North Africa 5/		Latin America and The Caribbean		Eastern Europe 4/		Asian Developing		Middle East
Iran		Argentina	Benin		Australia		Angola		Algeria		Argentina		Bulgaria		Bangladesh*		Bahrain*
Kuwait		Bolivia	Burkina Faso*		Austria		Benin		Egypt*		Bolivia		Czechoslovakia		China		Cyprus*
Libya		Brazil	Burundi		Belgium		Botswana*		Libya		Brazil		German Democratic		Fiji*		Iran*
Oman		Chile*	Cameroon*		Canada		Burkina Faso*		Morocco*		Chile*			Republic	India*		Iraq
Saudi Arabia		Congo	Central African Denmark				Burundi			Tunisia*	Colombia		Hungary		Indonesia*		Israel*
Taiwan		Costa Rica*		Rebublic	Finland		Cameroon*				Costa Rica*		Poland		Korea*		Jordan*
	Province of	Côte d’ Ivoire	Chad		France		Central African				Cuba		Romania		Malaysia		Kuwait*
	China	Ecuador*	Ethiopia*		Federal Rebublic			Republic	Dominican		USSRs Lavia		Myanmar*		Lebanon
United Arab		Egypt*	Ghana*			of Germany	Chad					Republic*	Yugos Lavia		Nepal*		Oman*
Emirates		Mexico*	Guinea-Bissau		Greece		Congo				Ecuador*				Pakistan*		Saudi Arabia
		Morocco*	Guyana		Ireland		Cote d’lvoire				El Salvador*				Philippines*		Syrian AR
		Nicaragua	Haiti		Italy		Ethiopia*				Guatemala*				Sri Lanka*		Turkey*
		Nigeria*	Kenya*		Japan		Gabon				Guyana				Taiwan		United Arab
		Peru*	Liberia*		Luxembourg		Ghana*				Haiti					Province of		Emirates
		Philippines*	Madagascar		Netherlands		Guinea-Bissau				Honduras					China	Yemen Ar 6/*
		Venezuela*	Malawi*		Norway		Kenya*				Jamaica				Thailand		Yemen PDR
			Mali*		Portugal		Liberia*				Mexico*
			Mauritania		Singapore		Madagascar				Nicaragua
			Mozambique		Spain		Malawi*				Panama*
			Myanmar*		Sweden		Mali*				Paraguay*
			Nepal*		Switzerland		Mauritania				Peru*
			Niger		United Kingdom		Mauritus*				Trinidad &
			Rwanda		United States		Mozambique					Tobago
			Senegal				Niger				Uruguay*
			Sierra Leone				Nigeria*				Venezuela*
			Somalia				Rwanda
			Sri Lanka				Senegal
			Sudan				Sierra Leone
			Tanzania				Somalia
			Togo*				South Africa
			Uganda*				Sudan
			Zaire				Swaziland*
			Zambia*				Tanzania
							Togo*
							Uganda*
							Zaire
							Zambia*
							Zimbabwe*

^1/Heavily indebted countries are nations with an external debt to exports ratio in excess of 3 and an external debt to GDP ratio in excess of 0.8. Nations that met these criteria that are not in the WEO list were Congo, Costa Rica, Egypt, and Nicaragua. The countries that were deleted from the WEO list were Colombia, Uruguay, and Yugoslavia.

^2/Small low-income economies: This category consists of nations with a per capita income of less than USS400 in 1980 and a population less than 50 million. Bangladesh and Pakistan were eliminated from the WEO list of small low-income economies group since they rank eighth and ninth in population among the world nations.

^3/Industrial nations: Singapore was added to the WEO list.

^4/ Eastern Europe: This is another category that was created to replace “other Europe.” It includes Yugos Lavia in addition to the Warsaw treaty organization members.

^5/North Africa and sub-Saharan Africa replace the WEO category of Africa.

^6/These two countries are now united.

^*Countries included in the GFS data, ^{Table 5}.

Note: The term “country” used in this report does not in all cases refer to a territorial entity that is a state as understood by international Law and practice. The term also covers some territorial entities that are not states but for which statistical data are maintained and provided internationally on a separate and independent basis.