Public Disclosure Authorized Estimating Internationally Comparable Per Capita

Income Numbers Public Disclosure Authorized Public Disclosure Authorized

International Economics Department

June 24, 1994 Public Disclosure Authorized Table of Contents

I. Introduction ...... 1 IT. Issues in measurement of income in national currencies ...... 2 ill Issues in choice of a common numeraire ...... 5

IV. Country comparisons by composite indicators ...... 11 V. The Bank's approach to country comparisons ...... 13 VI. Conclusion ...... 17

Annexes

I: Production Approach to Purchasing Power Parities ...... 19 IT: GNP Estimates and ICP Aggregation Procedures ...... 21 Til: The Standard Atlas Method of Estimating GNP in U. S. Dollars ...... 24 IV: Consistent use of SDR Deflator in the Bank's GNP Comparisons ...... 27

References ...... 29 Estimating Internationally Comparable Per Capita Income Numbers

I. Introduction

1. This paper reviews the methodological and data issues in estimation of per capita income on an internationally comparable basis, and sets out the Bank's current and prospective practices in generating such numbers for operational uses. 1 Compilation of these estimates requires measurement of income in national currencies, which raises various national accounting issues. The national currency estimates of income must then be denominated in a common currency for inter-country comparability, which raises issues in the choice between exchange rates and purchasing power adjusted conversion factors. Also, it is generally recognized that no single indicator can be an adequate basis for comparing countries. Per capita income, for instance, only relates to one aspect of the development process, which requires a broader comparison of a plurality of indicators for a more comprehensive assessment. In considering these numerous issues, the Bank's main priority has been to find a simple, transparent and readily available basis to compare economies for such operational purposes as determination of country eligibility to preferential categories of lending. It has at the same time been recognized that for most analytical purposes per capita income measures have to be supplemented by broader socio-economic indicators.

2. Section ll reviews the various issues in estit~ation of gross national product (GNP) per capita in national currencies. Section ill discusses issues concerning the conversion factor with focus on the relative merits and practicality of the purchasing power adjusted income comparisons under the United Nations International Comparison Programme (ICP). Section IV notes limitations of single indicator comparisons and assesses the case for composite indicators such as the (HDI) of the United Nations Development Programme (UNDP). Section V outlines Bank practices in per capita GNP comparisons that essentially reflect national estimates of GNP converted at official exchange rates with modifications made as needed on an exceptional basis. The concluding Section VI notes prospective modifications of these practices in Bank comparisons of per capita GNP.

Earlier staff reports on this subject Methodological Problems and Proposals Relating to the Estimation of Internationally Comparable Per Capita GNP Figures (SecM83-1120, December, 1983) and Per Capita Income: Estimating Internationally Comparable Numbers (SecM89-73, January 17, 1989) -- referred to hereafter as Board Papers-- were discussed by the Executive Directors on January 5, 1984, and February 10, 1989, respectively. 2

D. Issues in measurement of income in national currencies

3. GNP as the aggregate of domestic and net foreign incomes of a nation 1 s residents is the generally preferred conceptual basis for country income comparisons. The results are, however, little affected for most countries if one uses instead the concept of (GDP), which excludes net factor income from abroad.2 GNP comparisons on a per capita basis adjust for differences in population size, but not for other demographic factors such as differences in age-sex compositions of the national populations. Also, GNP per capita does not reflect the evolution of the country 1 s natural resources and nor does it distinguish between the ultimate uses of products generated during the period. Supplementary indicators thus have to be considered to assess relative levels of national welfare or development.

4. GNP comparison is substantially affected by coverage and quality differences as well as variations in institutional practices and capabilities implicit in the various data. In measuring GNP, market economies in principle follow the System of National Accounts (SNA) rule of including all marketable goods and services. However, actual practices differ widely in coverage and valuation especially of output from subsistence and informal economic activities. There are also systemic differences between countries that have long experience with SNA practices and those in transition from the alternative Material Products System (MPS) that only includes goods and the so-called material services. For instance, differing treatment of services and depreciation of capital assets is reflected in a substantial difference between SNA­ based GDP and MPS-based Net Material Product (NMP), the latter being generally between 15 to 30 percent lower for most Historically Planned Economies (HPEs). 3 These intrinsic disparities in national currency estimates of GNP together imply that country income comparisons can only be tentative so that relatively small differences in the national levels of per capita GNP have to be interpreted with caution.

2 The relative merits of various national accounting categories as alternative basis for international comparisons were extensively discussed in the 1989 Board Paper (op. cit., Annex 1, pp. 14-25).

3 World Bank, "Measuring and Inflation in Transition Economies", Summary Report: Accounting for Economies in Transition (International Economics Department (IEC), RPO 676-18, 1993). 3

Subsistence and informal activities

5. The disparate coverage and quality of national accounts data are especially pronounced for many of the lower income countries with a weak national capability for gathering even the most basic economic statistics. Data gathering in these countries is frequently limited to the formal monetized economy although informal and subsistence activities account for a relatively high proportion of their total incomes. The non­ monetized subsistence sector, which produces for own consumption rather· than marketing, is generally incorporated in the GNP estimates of most countries, but by various procedures. Coverage is more disparate for the monetized but unrecorded activities that are referred to as the informal sector; this sector comprises a wide variety of occupations that mostly engage the self-employed, including those in the underground economy operating at the margin of the law by evading taxes and regulatory frameworks.

6. Indications are that a more realistic assessment of the production in subsistence and informal activities will have a considerable impact on income comparisons across countries. However, measurement of such activities has been difficult for even the higher income industrialized economies where economic statistics are more plentiful. For instance, depending on the method of imputation, the estimated GNP share of informal activities has varied from 5 to 12 percent for Sweden and 7 to 15 percent for the U.K. for the same year. 4 Since monetization and market-orientation rise with the level of development, the problem of GNP comparability posed by disparities in the coverage of subsistence and informal activities is as a rule greater for lower income countries where the difficulties of measurement are also much greater.

7. For lower income countries, one study of a selection of countries places the relative share of unrecorded informal activities at well above 25 percent of GNP for most of Africa. 5 The seriousness of the gaps in coverage is illustrated in the periodic efforts to improve national accounts that have led to major revisions of the national currency estimates of GNP. Even an ordinal ranking of country incomes is made

4 See, J. J. Thomas, Informal Sector Activity (London, 1992).

5 See, World Bank, "The Measurement of Traditional Activities in the National Accounts". Paper prepared for Economic Commission for Africa Seminar on the Revision of the SNA, Addis Ababa, 29 September - 3 October, 1986. 4 difficult when the available data are subject to such drastic changes as the recent upward revisions of the GNP series by over 25 percent for Madagascar and over 30 percent for Argentina. 6 While the problem is likely to persist in view of the generally weak national statistical capabilities of many lower income countries, the International Labour Office (ILO) has reported plans by a large number of these countries to collect data on the informal sector and related topics such as small enterprises, cottage industries and household economic activities. 7

Historically Planned Economies (HPEs)

8. The long-standing problem of international comparability because of differences between the MPS and SNA estimates has lately eased with the transition of the states of the former (FSU) and other HPEs toward market-oriented economic systems. However, the pace of the transition has varied and the GNP data have been mostly derived from MPS estimates through mechanical bridge methods. These economies in transition thus are still affected by systemic differences that limit international comparability. Moreover, with the start of transition, traditional data reporting systems in HPEs are breaking down while the newly introduced procedures are yet to be fully effective. Comparability of economic aggregates has thus been reduced by persistent discontinuities in definitions, classifications and methods for collecting basic data and compiling statistical indicators. As output becomes more diverse and better suited to the consumer preferences during the transition process, the changes typically fail to be adequately reflected in the aggregated production data due to weak national statistical capabilities. The problems of GNP coverage are substantial also because the informal sector is believed to be extensive and growing in most HPEs as a result of persistent price controls as well as a legal framework for private business that is still at an early stage of development.

Accounting for the environment

9. Concerns over the environmental sustainability of economic development have renewed interest in an environmentally adjusted concept of income. This has added

6 See World Bank, Madagascar: Beyond Stabilization to Sustainable Growth (Report No. 9101, June, 1991) and Central Bank of Argentina, Estimacione Aonuales de Ia Oferta y Demanda Globales, 1980-92, (Buenos Aires, April, 1993).

7 ILO, Measuring Employment in the Informal Sector Through Labor Force Surveys: Conceptual Issues (International Labour Office, Geneva, September, 1990). 5 another potential source of incomparability to GNP estimates because of differing national practices in environmental accounting. The Bank has worked closely with the U.N. and other agencies acting on development of a System of Integrated Environmental and Economic Accounts and work is also proceeding on estimation of GNP and other national accounting categories on an environmentally adjusted basis. 8 However, standard guidelines are yet to be developed for such adjustments and the 1993 revised SNA has recommended independent treatment for now of the environmental impact in a satellite account. 9

Ill. Issues in choice of a common numeraire

10. Denomination of national currency GNP estimates in a common currency such as the U.S. dollar for international comparability raises intractable index number issues analogous to those in comparisons of prices and quantity aggregates for a single economy over time. While research continues on the methodological foundations for international comparisons, the results are so far mostly illustrative with little near-term prospect of a practicable option. 10 Meanwhile, exchange rates and the ICP approach to purchasing power adjusted comparisons of income offer the only workable alternatives for denominating national currency estimates of GNP in a common unit such as the U.S. dollar. While ICP-based comparisons ~e extensively used in various analytical works, exchange rates being readily available for most countries have remained the only practical basis of comparing economies for operational purposes.

8 Kirk Hamilton, "Green Alternatives to GDP," Paper presented to the London Group on National Accounts and the Environment, London, March 16-18, 1994 (World Bank, Environment Department, 1994); World Bank, Progress Towards Environmentally Sustainable Development (Environment Department, forthcoming, 1994).

9 United Nations et al, "Satellite Analysis and Accounts", Chapter XXI of System of National Accounts: 1993 (United Nations et al, New York, 1993).

10 See, World Bank, Purchasing Power of Currencies: Comparing National Incomes Using ICP Data (World Bank, IEC, 1993); Y. Kurabayashi and I. Sakuma, Studies in International Comparisons of Real Product and Prices (Hitotsubashi University and Kinokuniya Co., Tokyo, 1990); Francis Seton, The Economics of Cost. Use and Value: The Evaluation of Performance, Structure and Prices Across Time, Space, and Economic System (Oxford, 1992); A.E. Steenge and E. Bramer, "International Economic Comparisons Using Seton Eigenprices with Case Studies of Germany, Indonesia, Latvia and the Netherlands," (World Bank, IEC, 1993); and K. Velupillai and S. Zambelli, "The Economics of Purchasing Power and Production Based Approaches to International Comparison of Output, Expenditure and Income," (World Bank, IEC, 1994). 6

Exchange rates

11. The exchange rate is ·often used as basis for conversion factors since tt ts observable in the market and available universally. If free trade, competitive domestic markets and stable exchange rates prevail and transport costs are relatively small, then international comparisons of GNPs converted at prevailing exchange rates would be conceptually equivalent to GNP comparisons between regions within an economy. Under such conditions, national currency data converted at exchange rates would be comparable across countries, as a U.S. dollar's worth of U.S. products would be equivalent to what a U.S. dollar converted at the exchange rate of any other country would fetch in products of that country. International comparability would only suffer to the extent that the actual country situation departs from the above free market conditions.

12. Since market imperfections are extensive, it is generally recognized that conversions at exchange rates can be misleading in practice. Moreover, fluctuations in exchange rates are affected by capital flows, speculation and currency market interventions of monetary authorities that are unrelated to actual changes in the relationship between domestic and foreign prices. Also, exchange rates reflect at most relative prices of tradeables and even that correspondence cannot be expected in so far as there are taxes, subsidies, quantitative controls and other restrictive practices impeding free trade. Thus, the volume of goods and services that a U.S. dollar buys in the U.S. may lack any close correspondence to what a U.S. dollar converted to another country's currency at the official exchange rate would buy in that country. In the FSU, for instance, trade and service transactions often took place by administrative fiat with no reference to either domestic prices or official exchange rates so that the relation of purchasing power to exchange rates was especially remote.

Purchasing Power Parities (PPPs)

13. The alternative approach is to convert national currency estimates of GNP to a common currency by using conversion factors that reflect ICP-based Purchasing Power Parities (PPPs) 11 rather than exchange rates. The basic ICP approach is to subdivide

11 PPP is the commonly used term for these computed currency parities, which are unrelated to the PPP theory of exchange rate determination (Kravis, "Comparative Studies of National Incomes and Prices", Journal of Economic Literature, March 1984, p. 2) and are more appropriately labeled relative Purchasing Power of Currencies (World Bank, 1993, ibid.); computed in principle for a product basket comprising items of comparable quality, PPPs at the GDP (or GNP) level denote the national currency units required to purchase in the respective countries the same as what a U. S. dollar would purchase in the U. S. 7

GDP into a large number of basic item headings for which detailed price and expenditure data are collected. The implicit real quantities obtained from these price and expenditure data are then revalued at a uniform set of average international prices which are denominated in a standard currency. These values, which parallel constant price estimates in time-to-time comparisons, are deemed to provide an improved basis for international comparison of national accounting categories at various levels of aggregations up to the level of GDP (or GNP). Similar estimates can be obtained by converting local currency values to the numeraire currency by PPPs, which are computed by obtaining price ratios of matched items and aggregating them by GDP expenditure weights. PPPs as conversion factors provide estimates of GNP aggregates and their various components on a purchasing power adjusted basis for income levels to be compared according to their relative command over goods and services. PPP-based estimates are more stable over time as rankings are affected by relative performance of the economies free from effects of changes in exchange rates. In general, GNPs converted at PPPs are higher than the corresponding values at exchange rates, the difference being larger for lower income countries. ICP-based GNP levels and rankings can thus differ from those based on exchange rate conversions.

14. ICP-based purchasing power adjusted GNP comparisons are extensively used in analytical work12 as exchange rates at most equalize actual market prices of tradeables whereas PPPs are designed to represent a notional equalization of the prices of all goods and services in the comparison across countries. Operational use, however, has been limited as there are concerns about methodological issues and serious gaps in the quality, timeliness and geographic coverage of th~ available survey data.

15. The uniform valuation of national accounts at international prices for ICP comparisons effectively ignores the systematic differences in the price structures of economies at different stages of development, thereby effectively narrowing the income distances between richer and poorer countries .13 The estimated international prices typically reflect the price structures of the richer countries as country shares in global GDP are commonly used as weights in the averaging of national prices. The international prices are th.us relatively high for the services although most service

12 See Summers, "Analytical Uses of ICP-based International Comparisons," paper presented at the World Bank seminar on Bank Uses of ICP, Washington, D.C., June 8, 1989 and Heston et al, "Issues in Comparing Prices and Real Output Among Countries" (World Bank, IEC, 1994).

13 Paul Isenman, "Inter-Country Comparisons of "Real" (PPP) Incomes: Revised Estimates and Unresolved Questions," World Development, 1980, 8(1); World Bank (1993), ibid. 8 activities command relatively low prices in the poorer countries. Uniform use of the generally higher service prices of the richer industrial countries to reprice the estimated service quantities of all countries in effect inflates the relative size of the service outputs of poorer countries, thereby leading to a systematic upward shift in the ICP­ based estimates of poorer country GNPs.I4

16. The difficulties of matching the quality of products in international comparisons of prices is another major factor in the upward shift in PPP-based GNPs of poorer countries. Although PPPs are in principle computed for comparable items, observed prices are often included without adjustments for the large differences in product quality among countries. Typically, the prices of personal, medical, educational and most other services in low-income countries are thus recorded as a small fraction of the prices in the higher income industrialized countries with little or no adjustment for the substantial differences in quality. The extent of the resulting upward shift in PPP-based GNP estimates rises inversely with the level of country income as the quality of products is in general lowest in the poorest countries. PPP-based U.S. dollar GNPs of poorer countries are thus generally higher than they would be under price comparisons adjusted for differences in product quality. To minimize this tendency, ICP is now organized on a regional basis in which quality differences between neighbors is less severe than between countries across continents.

17. The available PPP estimates are for the most part based on comparisons of expenditures on GDP and use of one of several available alternative procedures for computation of aggregate PPPs from the basic data. PPPs can in principle be computed from either of the expenditure, production and income approaches to national accounting and all of these should yield comparable estimates of purchasing power adjusted GNPs. While a methodology is yet to be developed for the income approach, preliminary results for a limited group of countries suggest that GNP estimates based on production-based PPPs can be lower than those estimated from expenditure-based PPPs for lower income countries [Annex 1]. Also, the ICP-based GNP levels and relativities are sensitive to the choice of aggregation procedures from among several alternatives, the income differences among the PPP-adjusted GNPs of poorer and richer countries being much wider under some of the available but less used approaches

14 These tendencies are, however, absent in the official PPP estimates of the Organization for Economic Cooperation and Development (OECD), which are based on a method comparing two countries at a time and avoiding the use of a single set of international prices; OECD also publishes unofficial PPP estimates based on international prices. The dependence of ICP comparisons on various aggregation procedures is illustrated in Annex II. 9

[Annex m. These variations have persisted as aggregation procedures are suitable for one purpose or another and there is no single aggregation procedure that can satisfy all requirements.

18. Methodological considerations aside, operational use of the available PPPs has been limited by serious gaps in the coverage, quality and timeliness of the basic survey data. In particular, geographic coverage of ICP surveys, while regular and more or less complete in the industrialized economies, is irregular and uncertain for the developing economies. For about 70 percent of the non-OECD countries accounting for more than half of the total non-OECD GNP, ICP surveys are either yet to be undertaken or were carried out in 1980 or earlier. The latest surveys of Latin American countries were for 1980, and among countries yet to be surveyed are China and all countries in the Middle East. Also, some national authorities see ICP data as responding mainly to the analytical and operational needs of outside agencies and international organizations, including the United Nations Statistical Office (UNSTAT), the Statistical Office of the European Communities (EUROSTAT), the Economic and Social Commission for Asia and the Pacific (ESCAP), the International Monetary Fund (IMF), the World Bank and the OECD. Since collecting ICP data is also a resource intensive task, many countries have found it hard to assign it a high enough priority in their efforts at statistical development.

19. The prospect for ICP surveys to expand and continue has generally worsened since the Executive Board last discussed these issues in 1989. In the six ICP surveys completed so far, the country coverage increased from 10 in 1970 to 64 in 1985, but in 1990 only the OECD countries participated. About 60 non-OECD countries, again excluding countries in Latin America but including a limited participation by China, have signed up for the 1993 surveys. However, the surveys have progressed as scheduled in only the OECD countries and a number of HPEs receiving assistance for the purpose from OECD and the Bank. Data problems have also been aggravated by continued delays in dissemination of survey results. For instance, ICP's 1985 global comparison results were published in 1994.

20. In the absence of survey data for especially the non-OECD countries, the ICP comparisons have come to depend increasingly on extrapolations and regression-based estimates. The extrapolated results differ, depending on the choice of the base year or 10 years from which the extrapolations are made.1s Also, the extrapolations of data depend on average rates of inflation and output growth that in effect abstract from various structural changes affecting the composition of output and prices in these economies. These abstractions become more unrealistic as the period of extrapolation increases. For countries without any ICP survey, the practice has been to make inferences from regressions that differ among various ICP comparisons, adding one more element to the susceptibility of ICP results to methodological choices. 16

21. Despite these limitations, ICP data offer a valuable basis for some country comparisons. The 1989 Board Paper stressed ICP's advantages as a unique basis for inter-country analysis of prices and quantities for economies at a comparable stage of development. ICP data also permit such comparisons to be conducted at the level of any national accounting aggregate such as food, housing and medical services that can be further subdivided as rural-urban and formal-informal sectors data. The data thus facilitate international comparisons of, for instance, poverty levels and costs of health services. Moreover, PPPs have been helpful in inferring exchange rates in non-market economies (see Section V below).

22. Since ICP's inception in 1968, the Bank has been strongly supportive of work on PPPs as basis for country comparisons. 17 Bank work since 1989 in this regard has focused on integration of ICP surveys into national statistical routines and background support for UNST AT, which is responsible for coordination of global ICP comparisons. The Bank has also supported research on ICP methodology and uses of ICP data, promoted improved corrections of ICP comparisons for product quality differences and improved dissemination of ICP information. It has also funded meetings of experts, provided technical assistance, collaborated with EUROSTAT on a software to facilitate processing of ICP data, and stimulated further work on ICP in contacts with national and international statistical authorities.

15 Sultan Ahmad, "Intertemporal and Interspatial Comparisons of Income: The Meaning of Relative Prices," Policy Research Working Paper 1157, (World Bank, July, 1993); World Bank, "Table 30 and Technical Note" in World Development Report: 1994. (Washington, D.C., 1994).

16 Sultan Ahmad, "Regression Estimates of Per Capita GDP Based on Purchasing Power Parities," Policy Research Working Paper 956 (World Bank, August 1992); Heston et al (1994), op. cit.; World Bank (1994), ibid.

17 United Nations, Report of the Statistical Commission: Price Statistics (Twenty-Seventh Session, 22 February-3 March, 1993, E/1993/26; EKN.3/1993/27). 11

IV. Country comparisons by composite indicators

23. It is generally recognized that human development is a multi-faceted process that cannot adequately be reflected by any single indicator such as per capita GNP, which is only indicative of an economy's productivity or standard of living without any direct reflection of the level achieved in, for instance, literacy and longevity. Even as an income measure, per capita GNP is wanting in its lack of any reference to such pressing aspects of a country's development as poverty levels, distributional equity and sustainability of income from the standpoint of economic, environmental and broader sociological considerations. For a comparison of national welfare levels or quality of life, the income measure thus needs to be supplemented by indicators representing broader aspects of human development.

24. One response to the limitations of the income level as a single measure of welfare has been to develop composite indicators. Attempts in that direction have ranged from a search for holistic measures of development to design of narrower indicators for identifying achievement in specific areas of human needs. 18 Early efforts in this regard include the UN Research Institute of Social Development (UNRISD) work in the 1960s on a II development index II that combined a selection of indicators representative of economic and social development. 19 More recently, UNDP has introduced the Human Development Index (HDI) from indicators of income, health and knowledge. The index ranks countries by their estimated relative positions vis-a-vis the best and the worst performers among the countries in the comparison on average real income, longevity and literacy. 2o

18 Leo Goldstone, "The Use of Composite Indicators for Ranking Countries by their Level of Development," (World Bank, IEC, 1993); Sulekha Patel, "Composite Indicators: Review and Assessment with Emphasis on the Human Development Index (HOI)," (World Bank, IEC, 1994); T.N. Srinivasan, "Human Development: A New Approach or Reinvention of the Wheel?" (American Economic Association, Papers and Proceedings, May 1994, pp. 238-243).

19 UNRISD, Contents and Measurement of Socio-economic Development (New York, 1972). See also, David Morris, Measuring the Condition ofthe World's Poor (New York, 1979).

20 For each indicator, a country's deprivation index is computed as the deviation of its own performance from that of the best performer, expressed as a ratio of the widest such deviation recorded (i.e., the difference between the performances of the best and the worst performers) in the comparison; the HOI for each country is then the simple average of the computed deprivation indices for longevity (life expectancy at birth), literacy (literacy and average years of schooling) and income (logarithm of purchasing power adjusted GOP). See, UNDP, Human Development Report (New York, 1993). 12

25. While using HDI for general presentations of the country record on human development, the UNDP has continued to use the single per capita GNP indicator for operational purposes (see para. 33 below). Also, there is no consensus yet on the feasibility and desirability of combining income with other indicators to form a composite index. The HDI has so far lacked a conceptual justification for its methodology of selecting and combining the various indicators. It is thus difficult to interpret what aspect of development is portrayed in the particular combination of indicators in the HDI. Moreover, the observed differences in country rankings between HDI and per capita GNP largely disappear if the comparison is with the logarithm of the latter to adjust for the diminishing marginal utility of income.21 Also, the annual changes in HDI country rankings are difficult to interpret since they reflect comparisons with the best and worst performing countries, which vary from year to year.

26. The conceptual issues apart, data problems are as a rule more acute for composite indicators. In the case of HDI, for instance, the income component has the measurement problems and coverage limitations of GNP comparisons as both are drawn from the same national accounting sources. Also, the life expectancy data are heavily dependent on mathematical models rather than on actual observations. For a substantial proportion of the lower income countries, actual health and literacy statistics either do not exist or are highly dated. Further, the data are often difficult to compare internationally. For instance, school enrollment data cannot be compared across countries without adjustment for differences in, for instance, quality of schools and drop out rates for students attending school. 22

27. Data availability has a decisive influence on composite indicators as the choice of indicators has to be limited to the few on which data can be found. Furthermore, the computed country rankings are highly sensitive to the various methodological and statistical options in the selection, scaling and weighting of indicators. For instance, a switch from the sketchy and generally unreliable indicators of literacy to the more readily available and relatively robust data on educational expenditure as indicators for education would shift country ranks by 15 or more positions for 20 percent, and by 10

21 Allen C. Kelley, "The Human Development Index: Handle with Care", Population Development Review (June, 1991).

22 Srinivasan, op. cit. 13 to 14 positions for 15 percent of the included countries. 23 Similarly, assignment of a higher weight for the health indicator leads to major shifts in HDI country relativities.

28. While there is a general recognition that no single indicator such as per capita GNP can serve as a comprehensive basis for assessment of a country's relative stage of development, opinion is thus far from unanimous that the purposes of such a comparison can be served by merely shifting to any one of the many possible pluralities of indicators. The selection of a particular set of indicators is intrinsically difficult as what constitutes welfare can differ from country to country and time to time. For the same consideration of national differences, the difficulties are particularly great in the matter of weighting the various indicators. Thus, whether the choice is to be of any single indicator or of a particular group of indicators depends on the purposes of the comparison at hand. The Bank practice accordingly has been to compile and disseminate a wide variety of economic, social, demographic, environmental and other indicators to be used as needed in various international comparisons.

V. The Bank's approach to country comparisons

29. The Bank's practice has been to use per capita GNP numbers in U.S. dollars as a transparent and readily available single indicator for such operational purposes as determination of country eligibility for preferential credit. The Bank also generates a wide range of country-level economic and social indicators to supplement per capita GNP in international comparisons for broader analytical purposes. These various economic, demographic, educational and other indicators are regularly included in reports to the Executive Board24 and disseminated to the general public through various Bank publications.25 Besides a regular core of basic socio-economic indicators, the selection focuses on areas of Bank policy priority such as poverty alleviation and environmentally sustainable development. Since 1991, the Bank has also published ICP­ based purchasing power adjusted estimates of GNP.

23 Patel, op cit.

24 See, World Bank Operational Directives on "Country Economic Memoranda" (OD 2.0), "Social Indicators of Development" (OD 2.10, Annex A) and "Poverty Reduction" (OD 4.15).

25 See Atlas 1994 (Washington, D.C.); Social Indicators of Development: 1994 (Washington, D.C., 1994); "World Development Indicators" in Word Development Report, op cit. 14

30. The Bank's Atlas methodology [Annex III] provides procedures for computing conversion factors as well as a practical framework to review the available national accounts, population and exchange rate data for estimating the per capita GNP numbers. The conversion factor for expressing the national currency estimates in U. S. dollars is based ordinarily on official exchange rates. The estimates are made once a year and disseminated internally as part of the Bank's Operational Guidelines. 16 Revisions are made as needed for operational purposes in view of newly available information and presented in subsequent issues of the World Bank Atlas.

Assessment of income estimates in national currencies

31. Typically, the International Economics Department (IEC) first evaluates the national currency estimates of GNP and population in collaboration respectively with the responsible country departments, and the Population, Health and Nutrition Department (PHN). The dialogue on the national GNP estimates can lead to either adjustments to the national estimates or technical assistance as needed to arrive at figures acceptable to the Bank and the national authorities. In cases where an estimation is impractical for lack of reliable statistics, the Bank's practice has been to leave the country out of the comparisons pending availability of additional information. For instance, no per capita GNP was indicated for 21 of the 143 countries reported in the Bank's FY94 Operational Guidelines.

32. It is generally recognized that an improved basis for comparing economies would require above all a sustained effort by the national authorities to achieve greater consistency and coverage of national accounts statistics within the SNA framework. For many lower income countries, a significant improvement in national accounts statistics would only be possible with technical assistance from bilateral sources and from the Bank and other interested international organizations. Given resource constraints, IEC provides such technical assistance on a selective basis in consultation with the Bank country operations staff. The Bank also actively participates in efforts with the UN and other international agencies to facilitate a fuller implementation of the SNA in lower income countries and the HPEs.

26 World Bank, Per Capita Income Guidelines for Operational Purposes (SecM93-942, September 9, 1993). 15

Choice of conversion factors for market economies

33. In normal conditions of market economies, the Atlas conversion factor is the simple arithmetic average of the exchange rates for the current and the two preceding years adjusted for the country's inflation rates relative to the US inflation. While ICP­ based income estimates are widely used for various analytical purposes, conversion factors based on exchange rates are routinely applied for operational purposes by the Bank, other international organizations and national authorities. For instance, the IMF, while using ICP-based GNP weights for analytical purposes,27 has retained GNP estimates converted at exchange rates for operational purposes such as quota calculations. Similarly, the UNDP, while proposing HDI as an indicator of development, has continued to use the Bank's Atlas per capita income for allocation of technical assistance funds. The Bank's per capita GNP estimates are also used for the operational purposes of OECD's Development Assistance Committee (DAC).

34. The Atlas methodology incorporates a number of procedures to mitigate the limitations of GNP comparisons based on exchange rates. Use of a three year average of the annual exchange rates28 lessens the effects of fluctuations and abrupt changes in the rates. For countries with a multiple exchange rate system, a weighted average of the rates has been used, the weights being the shares of foreign exchange transactions subject to the different exchange rates.29 Besides tracking various parallel or black market exchange rates, the staff monitors changes in national trade and foreign exchange policies as part of the regular process of collecting country statistics on key indicators. The staff also reviews the real exchange rate trends by comparing nominal exchange rate movements with domestic and external rates of inflation. The objective is to identify egregious cases of exchange rate distortions resulting from, for instance, severe trade and foreign exchange restrictions and domestic price controls.

35. For determining alternative conversion factors, the staff practice has been to first identify the exchange rate of an earlier year or a recent month as normal in the absence of specific information indicating otherwise. The exchange rate in that year is then extrapolated forward or backward with adjustments for relative rates of inflation

27 IMF, World Economic Outlook, "Annex IV" (IMF, Washington, D.C., May, 1993).

28 Une rf in the IMF monthly publication International Financial Statistics (Washington, D.C., various issues).

29 Michael Hee, "Conversion Factors: A Discussion of Alternative Rates and Corresponding Weight," PRE Working Paper WPS 479 (W~rld Bank, IEC, August, 1990). 16 between the country and the U.S. during the period. However, such computations as a rule involve a large element of judgment and have therefore been limited in practice to cases of operational significance to the Bank. This has also meant that computation of alternative conversion factors has been effectively limited to distortionary cases of exchange rate appreciation typical of lower income countries. Such computations have thus been made for a total of only 27 countries since 1989, including the 15 countries of the FSU.

Choice of conversion factors for HPEs

36. The standard Atlas approach, which has been developed for open market economies, was inapplicable to the HPEs where resources were allocated administratively so that market forces played little role in determining prices and exchange rates. To meet the case especially of the FSU economies, Bank staff have developed the Synthetic Atlas-type Conversion Factors (SACF), which blends the Atlas and PPP approaches. The method yields an alternative set of national currency to U.S. dollar conversion factors for individual FSU economies, based on the observed PPP links between FSU economies and market economies, and the links between PPPs and average exchange rates for the latter. 30

37. Given the varying pace of adjusting domestic prices to world market levels, supply rigidities, remaining price distortions and thin foreign exchange markets, the so­ called market-determined exchange rates in the HPEs are still far from linking the domestic and foreign prices of tradeables. In particular, the highly porous newly drawn borders of FSU economies pose especially complex problems as prices for traded products differ widely between inter-Republic transactions among the FSU countries themselves and their trade with the rest of the world. Also, the estimation of foreign trade prices for inter-republic trade is beset by problems of assessing comparability of the quality of products traded among the FSU Republics as distinct from those traded with partner countries outside the FSU. Conversion factors for the economies in transition thus continue to require further modifications including possible revisions of SACFs as well as a more extensive use of PPPs.

30 The procedure is detailed in Estimating Dollar Per Capita Income for the States of the Former Soviet Union (World Bank, SecM93-589, June 15, 1993) and in Annex ill below. 17

VI. Conclusion

38. Developments since the 1989 Executive Board seminar31 have borne out the view expressed at the time that it would be "very unlikely that we would be able to discover a spectacular new methodology which will replace the present system of comparing economies, ... " The basis for comparing economies has in fact weakened as inadequacies of the available data have become more acute and pervasive, thereby worsening the inherent lack of comparability in the national currency estimates of GNP. The likely persistence of widely divergent national accounting practices, varying statistical capabilities and general resource constraints across countries suggest that the disparate quality and availability of national currency estimates will continue to be by far the most important limitation on country comparisons by levels of per capita GNP. The issue is of particular concern for a large proportion of lower income countries that have experienced a deterioration in national statistical capabilities. For the HPEs, the record is one of mixed progress as erstwhile statistical routines for collecting data destined for central planning exercises are being discontinued with new organizations yet to be firmly in place for the more indirect collection of data generated in market economies.

39. The staff will continue the review work for improving the available statistics and to extend technical assistance as resources permit in support of the Bank's country operations. Given resource limitations, the effort will be focused on an improved coverage of informal activities in especially the lower income countries. The 1989 Executive Board seminar on GNP comparisons suggested greater attention particularly to uniform coverage of informal and subsistence economic activities in national statistics. The Bank has been actively involved in the 1993 revision of the SNA, which recognizes the problem and outlines an approach to the issues. The work program includes effort to assemble information on country practices on national accounting coverage of these activities as a first step to assess the scope of the problem.

40. On conversion of national GNP estimates into U.S. dollars, earlier expectations of a possible greater reliance on ICP's purchasing power adjusted GNP comparisons have receded largely because of a deterioration in data availability. While work toward an improved availability of reliable PPP estimates is continuing, exchange rates are still the only practical option for denominating GNP estimates in a common numeraire to compare income levels on a current basis for lower as well as higher income countries.

31 February 10, 1989 seminar of Executive Directors to discuss the 1989 Board Paper (SecM89-73). 18

Building on the recent experience with the FSU economies, the staff will explore a more extensive use of PPPs in inferring conversion factors in exceptional cases. Where possible, PPPs will also be considered to infer alternative conversion factors for all countries undergoing drastic adjustments of exchange rates. Limited in the past to egregious cases of exchange rate appreciation, estimation of alternative conversion factors will be applied henceforth symmetrically to cases of exchange rate depreciation.

41. In view of the deteriorating prospects for ICP surveys in non-OECD countries, the Bank is now exploring a new initiative to be launched for expanding country coverage and improving timeliness of data by using simplified survey procedures in collaboration with other users of purchasing power adjusted estimates of GNP. While the primary aim is to compensate for major gaps in the global coverage of regular ICP surveys, the initiative is expected to be the starting point of an improved basis for international comparisons of price and expenditure structures. Preliminary contacts have been established in this regard with the European Bank for Reconstruction and Development (EBRD), the Inter-American Development Bank (IADB), the IMF and the UNDP.

42. Finally, the current inconsistency will be eliminated in making inflation adjustments to the Atlas conversion factors for estimating country GNP per capita and to the income thresholds for qualifying countries to various categories of Bank preferential lending. In adjusting the exchange rates for a country's relative inflation rate, the U.S. GNP deflator is at present used to represent external inflation. However, in making the corresponding adjustment to the income thresholds, the external inflatien indicator is taken to be the SDR deflator in US dollar terms. Henceforth, the SDR deflator will be applied consistently for both purposes. This technical correction is not expected to result in significant changes in per capita income estimates, but it will serve to eliminate the asymmetry in current practice and to ensure that the updating of country GNP per capita figures reflects a wider measure of external inflation than U.S. domestic price increases for all countries including the United States [Annex IV]. 19

Annex I

Production Approach to Purchasing Power Parities

Computation of PPP based on the production side of GDP has a long history, dating back to early postwar years and accounting for over two dozen studies. 32 These studies compare pairs of countries at a time and are typically confined to commodity producing sectors, most frequently manufactures, and rarely covering total GDP. About two dozen countries have been covered this way, some for several years, with the reference years ranging from 1935 to 1987. The most recent and by far also the most successful effort in this direction is by the International Comparison of Output and Productivity (ICOP) team at the University of Groningen led by Professor Angus Maddison.

Using data from censuses of industries, unit value ratios are computed for matched outputs, which typically account for a fifth to a third of the industry. The ratios are then aggregated by alternatively weighting them by the quantities of the two countries being compared. These computations for a pair of countries yield two alternative estimates of average unit values ratios, or PPPs. A geometric mean of these is then presented as a summary measure of PPP. Estimates for entire industries are finally made on the assumption that the unit value ratios observed in the matched outputs would be applicable to the rest of the industry. For the service sectors, ICOP sometimes uses ICP estimates and otherwise makes own estimates as census data are generally unavailable.

!COP's PPPs computed from gross outputs in effect ignore quality differences between products of different countries. Also, the computation of these ratios solely from gross outputs assumes that price relatives for inputs are the same as those for outputs. Subject to these limitations, purchasing power adjusted income estimates based on !COP's PPPs are generally lower than those from the expenditure comparisons, and thus closer to the Atlas as shown below:

32 Bart van Ark, International Comparisons of Output and Productivity: Manufacturing Productivity Performance ofTen Countries for 1950 to 1990 (Growth and Development Centre Monograph Series No. 1, Ch. 2, Groningen, 1993). 20

Table 1 : Comparison of Atlas, !COP and ICP estimates of GDP at factor cost, 1975 (US = 100)

Atlas ICOP ICP Brazil 7 12 15 Mexico 5 7 12 Korea 1 2 4 Japan 32 36 39 USA 100 100 100

The difference between ICP and !COP estimates mainly relate to the service sectors as the two would be virtually the same if the comparison were confined to the sectors for which census data were used by ICOP, i.e., agriculture, mining, and manufacturing. The !COP's country coverage is, however, too limited to draw any general conclusions. Thus, coverage at the overall GDP level is limited to five countries for the single year 1975. Besides, the ICOP method can be applied only to countries that have censuses of industries giving values and quantities of detailed outputs at least for the reference year. When such data are available, the approach has been applied to studies of output and productivity of particular industries. 33 Given the limitations of data on the especially lower income countries, the ICOP approach is yet to be developed for a worldwide comparison of all components of GDP in the expenditure comparisons of ICP.

33 Angus Maddison and Bart van Ark, "The International Comparison of Real Product and Productivity", (World Bank, IEC, 1994). 21

Annex II

GNP Estimates and ICP Aggregation Procedures

Various methods are available for aggregating price relatives of individual products to compute GDP (or GNP) in international prices (1$) for different countries.34 There is no universal agreement on any particular formula as none meets all of the criteria considered desirable in index number comparisons. Moreover, the relative importance of these desirable characteristics of index numbers varies with the purpose of comparisons. For instance, a formula has to ensure additivity if the comparison is of the structure rather than the aggregate level of GNP. In other words, national accounting quantities obtained through applying an aggregation method should be such that, for each country, the computed GNP components will add up to the independently computed aggregate GNP.

Several aggregation methods have thus been used, resulting in various 1$ estimates of GNP from the same basic price relatives. Among these, Geary-Khamis (G-K) and Elteto-Koves-Szulc (E-K-S) are widely used, and a third, Ikle, 35 Is a more recent application to the ICP field (see below):

The G-K method gives unequal weights to individual country price relatives, the weight for each country's price relative being the country's share in global expenditures for each product. The method thus yields a vector of international prices that mainly reflects the price patterns of countries with large aggregate expenditures, mainly including the major industrialized economies.

The E-K-S method provides PPPs directly without explicitly introducing a set of international prices. Each country's PPP is instead derived as the geometric average of its direct and indirect Fisher price indexes. The resulting PPPs are transitive across countries and can be used to convert the national currency estimates of GDP into 1$.36

34 Yuri Dikhanov, "Sensitivity of PPP-Based Income Estimates to Choice of Aggregation Procedures," (World Bank, IEC, 1994).

35 Doris M. Ikle, 11 A New Approach to the Index Number Problem, 11 Quarterly Journal of Economics, Vol. 86, May, 1972, pp. 188-211; Velupillai, et al, op. cit.

36 Irving Kravis, et al, World Product and Income (Baltimore and London, 1982, pp. 74-79). 22

Table 1. PPP-Based Per Capita GDP Estimates by Alternative Methods, 1985

EKS G-K Ikte EKS G-K Ikte

(In/$) (Rank shifts)*

USA 16,559 16,559 16,559 1 Canada 15,180 15,403 15,100 2 Gennany 12,078 12,275 11,316 7 1 1 France 11,621 12,133 10,978 9 1 Netherlands 11,494 11,533 10,667 10 2 1 U.K. 10,808 11,152 9,859 12 3 3 Japan 10,768 11,584 10,365 13 -2 -1 Italy 10,757 11,474 10,216 14 -1 -1 Spain 6,715 7,064 6,274 20 -1 5,625 6,196 5,468 21 Yugoslavia 5,148 5,536 4,929 23 -1 Iran 4,366 5,418 4,429 25 -1 -1 4,164 4,497 4,264 26 2 -1 South Korea 3,899 4,532 3,960 27 Turkey 2,984 3,536 3,147 29 1 Thailand 2,034 2,968 2,172 33 -1 -2 Egypt 1,732 2,683 1,829 34 Philippines 1,459 2,007 1,578 38 -1 Pakistan 1,070 1,442 1,013 42 Nigeria 834 1,149 780 44 3 1 India 640 779 653 48 4 1 Bangladesh 557 1,125 673 51 -3 -3 Ethiopia 210 324 208 57

Source: Dikhanov (1994)

* The rank shifts are relative to the E-K-S ranks for a selection of 57 countries of which 23 are shown here. 23

The lkle method, like G-K, derives international prices. However, the country weights for individual products are the shares of the products in the country's total expenditures, expressed in international prices.

The country expenditures data in international prices derived through the G-K procedure are additive. Thus, the GNP components separately computed in international prices add up to the independently computed GNP in international prices. Such additivity is important in comparing economic structures across nations, as in comparisons of, for instance, poverty incidence and burden of medical care. However, as the G-K international prices tend to be closer to the price patterns of high-income countries, the income of the poorer countries as expressed in I$ becomes considerably high. This overstatement--the so-called Gerschenkron effect37 --narrows the distance between the income levels for the rich and the poor.

The E-K-S method is now used in OECD's official estimates of purchasing power adjusted GDPs. Being geometric averages of binary comparisons with equal country weights, these estimates are virtually free from the Gerschenkron effect. They are thus well suited for cross-country comparisons of GDP, although lack of additivity limits their usefulness for comparing the structure of GDP.

The Ikle method derives the international prices needed for comparison of GNP and its details so that the results remain additive and thus well suited like the G-K estimates for detailed comparisons of GNP components and sub-aggregates. At the same time, the Ikle method allows each country to exercise an equal influence on the structure of international prices, thus minimizing the Gerschenkron effect.

Given these differing advantages and disadvantages, some international organizations such as EUROSTAT tailor comparisons to specific purposes through use as needed of either G-K or E-K-S. As can be seen from the Table below, G-K results are substantially different from the E-K-S and Ikle results for many lower income countries, and the differences are not uniform across countries, resulting in changes in country ranking. Thus, the Bangladesh GNP differs by over 100 percent, switching the country's relative ranking vis-a-vis India.

37 The Gerschenkron effect means that the valuation of a country's quantities tends to be high when a price structure much different from its own is the basis of the valuation. (See Kravis et al, A System of International Comparisons of Gross Product and Purchasing Power, Baltimore and London, 1975, p. 74). 24

Annex III

The Standard Atlas Method of Estimating GNP in US Dollars

The standard Atlas method of deriving GNP per capita estimates in U.S. dollars applies a conversion factor based on official exchange rates to per capita GNP figures in national currencies that have been reviewed by operational and IEC staff. The conversion factor used for any given year is the simple arithmetic average of a country's official exchange rate for that year and its exchange rates for the two preceding years, after adjusting these rates for differences in relative inflation between the country and the United States. In countries with multiple exchange rates, a weighted average of the officially recognized rates is first calculated for each year before application of the standard Atlas method, the weights being the respective shares of the various rates in total international transactions. 38 The three-year averaging process smoothes the effects of fluctuating prices and exchange rates in each country. For any given year t, the Atlas GNP per capita is thus derived as follows:

where . (e 1-21)

y$ t Atlas GNP per capita in U.S. dollar; yt national currency estimate of current GNP; Nt mid-year population; e *t-2,t Atlas conversion factor: national currency/U.S. dollar; et average annual exchange rate: national currency/U.S. dollar; pt GNP deflator; and p$t U.S. GNP deflator.

The Bank uses the official exchange rate, shown on line if in the IMF, International Financial Statistics, to derive the standard Atlas conversion factor. Exceptions are made to the standard case in two cases. For market economies,

38 The incidence of multiple exchange rates in various countries is shown in the IMF's Annual Report on Exchange Arrangements and Exchange Restrictions, (IMF, Washington, D.C.; various issues). 25 alternative conversion factors are computed when Bank operations and central staff determine that the official exchange rate is egregiously out of line as a link between average world prices and the average domestic prices included in the national accounts. Typically, this reflects distortions of markets by policy interventions. In the case of the FSU economies where comparable price and national accounts information has not been available, special procedures using PPPs have been employed to generate an alternative conversion factor that is still compatible with the Atlas methodology generated results for the other countries.

For computation of alternative conversion factors in market economies, the staff practice has been to monitor the evolution of effective real exchange rates to identify countries where the official exchange rate is not linking domestic prices to the corresponding world prices because of major market distortions from policy interventions such as import tariffs, quantitative restrictions, export taxes and domestic price controls. Although a number of economies are identified as requiring alternative conversion factors, the actual cases of alternative conversion factor computations have been kept to a minimum in view of the large element of judgment in making these determinations (see table below). Typically, in the absence of information to the contrary, the practice has been to adopt a recent period as one in which market conditions were normal. The exchange rate for that year is then extrapolated to the current period by the changes in the country's domestic GOP deflator, relative to that of the US during the period. This alternative conversion factor is then used to convert the non-trade portion of GNP into U.S. dollars, the official exchange rate being used to convert the data on external transactions. The overall alternative conversion factor in such cases is thus a weighted sum of official and estimated exchange rates.

For the transition economies of the FSU, alternative procedures had to be devised because of the lack of reliable indicators of market prices. 39 The available exchange rate data could not be used to convert GNP into U.S. dollars because until recently trade was at exchange rates vastly different from the market rate. The alternative approach used in market economies of selecting a past exchange rate as basis for forward extrapolations was also not feasible, given the erstwhile managed price and exchange rate regimes of the FSU economies. An alternative methodology was

39 A detailed description of the derivation and use of SACF in estimating GNP per capita in US dollars for the FSU is found in World Bank, "Measuring the Incomes of the Economies of the Former Soviet Union", Policy Research Working Paper 1057 (World Bank, December, 1992) and World Bank, "Estimating Dollar Per Capita Income for the States of the Former Soviet Union" (SecM93-589, June 15, 1993). 26 accordingly devised. The approach constructs a conversion factor -- the Synthetic Atlas Type Conversion Factor (SACF) -- relying first on a comparison of (a) PPPs of an individual FSU currency against currencies of a group of broadly comparable economies at a similar stage of development and (b) the PPP-to-exchange rate relationship for the latter group of economies. Available data on a 39-commodity basket for each of the FSU Republics allow for country-specific PPP estimates for each individual Republic. The SACFs for each FSU economy are averaged over three years as in the standard Atlas methodology.

Countries With Alternative Atlas Conversion Factors, FY90- FY94 /1 FY90 FY91 FY92 FY93 FY94 ------ Bulgaria El Salvador El Salvador El Salvador El Salvador .El Salvador Ghana Ghana Ghana Ghana Ghana Guinea-Bissau ------Peru Peru Peru Peru Peru ------ Somalia Somalia Somalia Somalia Somalia ------FSU economies21 FSU economies21

/1 A country is listed when at least one year's exchange rate is an alternative conversion factor in ·the Atlas 3-year exchange rate averaging process.

/2 FSU Economies: , Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine and Uzbekistan. 27

Annex IV

Consistent use of SDR Deflator in the Bank's GNP Comparisons

The Bank's Operational Guidelines GNP thresholds for determining lending categories have been updated annually by the international inflation rate as measured by the SDR deflator in US$ terms since FY83. However, the US GNP deflator is applied as a measure of international inflation to the traditional Atlas formula for updating the GNP per capita of individual countries. There is thus some divergence between the change in thresholds in nominal US$ and the country level nominal GNP per capita in US$. The staff will, therefore, use the SDR deflator in US$ terms also in the Atlas formula to be consistent with the inflation measure used to update the Operational Guidelines thresholds. The proposed formula for the Atlas method conversion factor presented below would differ from the formula presented in Annex III above. Thus, for any given year t, the proposed Atlas conversion factor is:

ss s •s P P e

e., = .!l' (-p~s 1-p-~ J+ 3 2 L t- Pt-2 Pt-2 where e * t = Atlas conversion factor (national currency to the U.S. dollar); e*S = Relative inflation adjusted US$/SDR exchange rate; est = Official US$/SDR exchange rate;

~ = The country's exchange rate (national currency to the U.S. dollar); Pt - The country's GNP deflator; pS$t = SDR deflator in U.S. dollar tenns; p$ t - U.S. GNP deflator; and P5 t = SDR deflator in SDR tenns. 28

Annual changes in the SDR deflator in US$ differ from those in the US GNP deflator since the SDR deflator covers not only inflation of the US, but also of France, Germany, Japan, and the U.K. Further, the US$/SDR exchange rate has shown large changes, particularly during the 1980s. For instance, the US$ weakened relative to the SDR by about 16 percent in 1986 and a further 10 percent in 1987. Below is a comparison of annual percentage increases in the US GNP deflator and the SDR deflator in US$ terms since FY90:

Table 1: Comparison of Changes in Alternative Deflators (Annual changes in percent)

FY90 FY91 FY92 FY93 FY94

US GNP deflator 3.8 4.5 4.3 3.9 2.9 SDR deflator in US$ terms 1.1 -1.1 9.7 4.4 5.5

Since the Atlas method uses a three year average of prices and exchange rates, the switch to the SDR deflator would have a less pronounced effect on year to year estimates of GNP than that indicated by the varying measures of annual inflation in Table 1. For instance, substitution of the US GNP deflator by the SDR deflator in US$ terms in the Atlas formula would have changed the Bank member countries' GNP per capita levels in US$ by less than 2 percent in FY92 when changes in the two deflators deviated by over 5 percentage points. Indications are that for FY95 the technical corrections for consistent use of SDR deflators will have no impact on the Bank's classification of countries into the various operational lending categories as the switch to consistent use of the SDR deflator in US$ terms will result in an estimated upward adjustment of less than one half of one percent in the Atlas GNP per capita estimates. 29

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