Intercountry inequalities in income and basic- needs indicators: A recent perspective

World Development, Vol. 20, No. 6, pp. 899-905,1992. 0305-750X/92 $5.00 + 0.00 Printed in Great Britain. 0 1992 Pergamon Press Ltd

Intercountry Inequalities in Income and Basic- Needs Indicators: A Recent Perspective

RAT1 RAM* Illinois State University, Normal

Summary. - Large crosscountry samples are used to compute intercountry inequalities in income and three indicators of basic-needs fulfillment. First, the familiar picture of high intercountry inequality in income coexisting with low inequality in basic-needs indicators is reaffirmed for the 1980s. Second, income inequality seems to have continued its increasing trend. Third, however, while the pace of increase in inequality in conventional GDP per capita has accelerated, accentuation of inequality in “real” GDP per capita has slowed. Fourth, inequality in basic-needs indicators continues to decline. Last, caution is urged in interpreting the very low values observed for some indices of inequality in basic-needs fulfillment during the 1980s.

1. INTRODUCTION

Along with the desirability of increased income, the importance of basic-needs fulfillment received a new recognition in the development literature of the 1970s and the 1980s. In addition to several other scholars who dealt with the various conceptual, empirical and policy aspects, Hicks (1979), Hicks and Streeten (1979), Leipzi- ger (1981), Sheehan and Hopkins (1979), Stewart (1985), Streeten (1980, 1981), Wheeler (1980) and World Bank (1980a) have made notable contributions on the subject.

The primary purpose of this study is to provide a perspective on crosscountry inequalities in income per capita and three major basic-needs indicators over the last three decades, and, in particular, to show their position for the 1980s.’ The work proceeds by reporting indices of intercountry inequality in income and basic- needs indicators for 1960, 1988 (or thereabout) and at least one intervening year. Although the primary inequality index adopted in the paper is Bourguignon’s (1979) L, a brief comparison is made with one more index for income inequality and with three other indices for judging inequality in basic-needs fulfillment. The broad situation can be summarized by saying that income inequality continues to be high while inequality in basic-needs indicators is low. Income inequality appears to have continued its upward trend, although increase in inequality in terms of “real” GDP per capita has slowed and may even have

stopped. Inequality in basic-needs indicators continued to decline, and some indicators did so at an even faster pace than others. The inequality in most basic-needs indicators may now seem to be at such extremely low levels as to be almost nonexistent. Care is, however, needed in the interpretation of these low inequality indices. It seems desirable to consider several indices of inequality and to supplement these with other measures of basic-needs fulfillment in the less developed world.

2. DATA, INEQUALITY MEASURES,

AND THE MAIN RESULTS

It is perhaps obvious that an intertemporal perspective on crosscountry inequality in major economic and social indicators is a useful step toward judging the economic progress made by less developed countries (LDCs), the status of fulfillment of basic needs of human populations, and the extent of amelioration of poverty. As noted in Section 1, this study reports indices of intercountry inequality in income and three

*Two anonymous referees of this journal gave many useful comments on an earlier version. Cynthia Yuchang, Koby Bailey and Terry Harvill provided research help. The author alone is, however, respon- sible for all errors and deficiencies.

Final revision accepted: September 6, 1991.

899

900 WORLD DEVELOPMENT

important measures of basic-needs fulfillment for 1960, a recent year around 1988 and at least one intervening year.2 Although the broad picture for the 1960s and the 1970s is fairly well known, the reported comparisons should reveal both the directions of change and the present levels of inequality after taking into account the situation for most of the 1980~.~

One income variable for which crosscountry inequality is computed is the familiar GDP per capita in US dollars. In view of the well-known bias in that measure, however, which shows poor countries to be relatively poorer and rich countries to be relatively richer, shortcut estimates of GDP per capita in “international” dollars have been used to compute another index of crosscountry inequality in real income.

The three indicators of basic-needs fulfillment are calorie supply, life expectancy, and literacy rate. These are obviously prime indicators of the extent to which basic needs relating to nutrition, health and education are being met.

The data are taken largely from World Bank (1980b, 1989), United Nations (1986), Summers and Heston (1988), and United Nations Develop- ment Programme (1990). Appendix A provides additional details about the variables and the data sources.

A well-recommended measure of inequality is used. Besides its usage in several other studies, Bourguignon (1979) has shown that this measure provides the only population-weighted additively decomposable inequality index which satisfies the Pigou-Dalton condition and has the property of zero-homogeneity. For intercountry inequality, the index (L) may be defined as4

where pi is the ith country’s share in total (“world”) population, yi is the ith country’s share in total “income,” In denotes natural logarithm, and there are II countries.’

Table 1 contains the main results. Based on fairly large intercountry cross-sections, it reports indices of income inequality for 1960, 1970, 1978 and 1985, and inequality indices for three basic- needs measures for the years 1960,1978 and 1988 (or thereabout). Country coverage for income is identical in all years, and the indices are directly comparable. Samples for the basic-needs indicators are somewhat different for various years, but are fairly close in most cases6

Table 1 reaffirms the observation that income inequality is high and increasing. Considering

Table 1. Indices of intercountry inequality in GDP per capita and some indicators of basic-needs fulfillment*

GDP per capita 1960 1970 1978 1985

In conventional dollars 0.910 1.006 1.098 1.160 (N = 112)(N = 112)(N = 112)(N = 112)

In “international” dollars 0.540 0.607 0.644 0.653 (N = 112)(N = 112)(N = 112)(N = 112)

Basic-needs indicators 1960 1978 1985-88

Calorie supply 0.012 0.010 0.013 (N = 119) (N = 101) (N = 106)

Life expectancy 0.028 0.016 0.010 (N = 125) (N = 101) (A’ = 157)

Adult literacy 0.240 0.145 0.071 (N = 89) (N = 90) (N = 89)

*The inequality index is Bourguignon’s (1979) L and is defined in equation (1) of the text. The samples exclude almost all socialist countries. The sample countries are listed in Appendix B. Data on GDP per capita are based largely on Summers and Heston (1988). Information on life expectancy and adult literacy for 1985-88 comes primarily from World Bank (1989), while that on calorie supply is taken from UNDP (1990). Inequality indices for basic-needs measures for 1978 are taken directly from Ram (1982, p. 115); those for 1960 are computed largely from data reported in World Bank (1980b) and United Nations (1986).

INTERCOUNTRY

conventional GDP per capita in US dollars, the inequality index shows a continuous increase from 1960 to the mid-1980s. Perhaps more significantly, the rate of increase seems to have been accelerating, especially over the 1970s.’ Inequality in real GDP per capita (in international dollars) is also seen to be increasing, but the rate of increase has probably slowed, and the accentuation of inequality may even have stopped.8

A few words about the country coverage are in order. Appendix B contains the list of 112 countries for which income inequality is reported. As stated in Table 1, most state-socialist countries are excluded. Strictly speaking, therefore, the numbers reflect the position in the nonsocialist world. In particular, the absence of China may merit some reflection. Given the very large size of that country, and its relatively rapid income growth, it is reasonable to think that inclusion of China would show the increase in income inequality to be smaller. Data deficiencies, however, make a clear inference difficult. It is true that if Summers-Weston data on real GDP per capita are used, inclusion of China would show little increase in inequality over the period. On the other hand, it seems unlikely that inclusion of China would show a smaller increase in inequality during the period in terms of conventional GNP per capita.’

By way of a methodological point, some observations on the inequality index L may be useful here. As already noted, the index has some very appealing properties. In fact, Bour- guignon (1979, p. 913) stated “That the inequality measure L has seldom been used in applied works on income distribution is somewhat sur- prising because it has very much to commend it.” It may, however, be interesting to check the position with reference to at least one more index. lo Table 2 provides a comparison of in-

INEQUALITIES 901

come inequality for 1960 and 1985 on the basis of two inequality indices. One of these is, of course, L. The other is the well-known entropy index (E) which is obtained by interchanging the positions of income-share and population-share in equation (1); this is also Theil’s income-weighted index, as Bourguignon (1979, p. 915) noted. It is evident from the comparison that while E shows the inequality to be smaller, as is usually observed, the broad picture indicated by L and E

concerning the level, direction, and pace of change of inequality is very similar.

In addition to an assessment of the magnitude of change in intercountry inequality, it is useful to take advantage of the property of decompo- sability of the index, and decompose the observed increase in income inequality into the components attributable to relative changes in income per capita and population. Following the methodology suggested by Theil and Sorooshian (1979) for states in the United States, decomposition of the increase in inequality in real GDP per capita from 1960 to 1985 indicates that practically the entire increase is due to changes in relative income per capita, and very little can be attri- buted to relative changes in population.”

In regard to basic-needs indicators, Table 1 reaffirms for the 1980s the familiar scenario of a low level of inequality. Perhaps more important, crosscountry inequality in these indicators continued not merely to decline, but the pace of decline accelerated for literacy and life expectancy. The inequality indices for literacy, which are based on fairly similar samples, show that the relative (percentage) decline during 197845 was larger than that during 196&78. The position for life expectancy is similar. Despite the sample variability, the decline during 197&88 is impressive. l2 The situation in regard to calorie supply is also very good; there is no decline in inequality, and there might even have been a

Table 2. Comparison of inlercountry income inequality on the basis of two different measures*

1960 1985

L E L E GDP per capita in conventional dollars 0.910 0.756 1.160 0.843

(N = 112)(/v = 112)(N = 112)(N = 112)

GDP per capita in international dollars 0.540 0.481 0.653 0.543 (N = 112)(N = 112)(N = 112)(N = 112)

*The index L is Bourguignon’s (1979) measure, while E is the entropy index which is obtained by interchanging the positions of income share and population share. The latter is also known as Theil’s income-weighted inequality index.


small increase from 1960 to 1985, but the level has been very low throughout.

The continuation through the 1980s of the declining trend in intercountry inequality in basic-needs fulfillment is welcome. The large declines in the inequalities in literacy and life expectancy are gratifying. The observed low values of intercountry inequality in these indicators, however, need to be interpreted with some caution. It may be tempting to treat these extremely small values as suggesting that the serious problems of international inequalities in basic-needs fulfillment have been largely resolved. Such an interpretation may be inappro- priate. Casual observation indicates that there are large differences across countries (and within countries) in the fulfillment of basic needs relating to health, nutrition and education.

It may be useful to consider whether some other measures of inequality would reflect the position better in regard to crosscountry inequalities in basic-needs indicators. A definite answer to that question is not possible within the limits of this short paper. Table 3, however, provides a comparison of the position for 1960 and 198548 on the basis of four different measures of inequality, which include L, E, standard deviation, and absolute mean deviation.” In general, the situation suggested by the four indices is broadly similar. All of them show large declines in inequalities for both life expectancy and adult literacy. Standard deviation and absolute mean deviation, however, seem to give a better indication of both the decline and the current inequality levels. Therefore, use of several different inequality measures could provide a richer perspective on intercountry inequalities in basic- needs fulfillment. Moreover, it might be possible to supplement such measures by other information so as to get a better feel for the status of basic-needs fulfillment in the developing world and the extent of progress made in that regard.14 Of course, income inequality also has to be taken into account along with that in basic-needs fulfillment.‘5

3. CONCLUDING REMARKS

This study is an update on the status of intercountry inequalities in income and basic- needs indicators. The increasing tendency for the inequality in conventional GDP per capita (in US dollars) appears to have continued in the 1970s and the 1980s. The increase in the inequality

Table 3. Comparison of intercountry inequality in basic- needs fulfillment in terms of four different inequality

measures

1960 1985-88

Calorie supply Bourguignon’s L

Entropy (E)

Standard deviation

Absolute mean deviation

Life expectancy Bourguignon’s L

Entropy (E)

Standard deviation


Adult literacy Bourguignon’s f.

Entropy (E)

Standard deviation


0.012 0.013 (N = 119)(N = 106)

0.012 0.013 (N = 119)(N = 106)

15.9 17.7 (N = 119)(N = 106)

13.7 15.3 (N = 119)(N = 106)

0.028 0.010 (N = 125)(N = 157)

0.027 0.010 (N = 125)($’ = 157)

12.5 8.9 (N = 125)(N = 157)

11.4 7.5 (N = 125)(N = 157)

0.240 0.071 (N = 89) (N = 89)

0.196 0.068 (N = 89) (N = 89)

31.5 21.1 (N = 89) (N = 89)

28.8 19.1 (N = 89) (N = 89)

index for real GDP per capita in international dollars may, however, have slowed and might even have stopped. In regard to basic-needs fulfillment, the decline in crosscountry inequalities seems to have accelerated in the 1970s and the 1980s for such important indicators as life expectancy and literacy, and the inequality indices for recent years are very low. While the observed decline is welcome, some caution seems appropriate in interpreting measures of inequality in basic-needs indicators. In particular, the very low values of some of these indices may not be interpreted to imply that problems of international inequalities in the fulfillment of basic needs have been resolved. It appears useful to consider several different measures of inequality, and to supplement these with other information to obtain a reasonable indication of the status of basic-needs fulfillment in the developing world.

INTERCOUNTRY INEQUALITIES 903

NOTES

1. Although there is some literature on the subject, there is apparently no research that includes the 1980s. Ram (1982) compared the position for 1960 with that for 1978. To some extent, this study updates Ram (1982) after including one more decade.

2. The last year reported is determined by data availability. Conventional dollar income and real income in international dollars are for 1985; calorie supply is for 1985 (1984-86); life expectancy relates to 1988; and the literacy rate is for 1985. Appendix A has additional details about the variables and the data sources.

3. Ram (1982) and other researchers have brought out the situation for the 1960s and most of the 1970s.

4. Bourguignon (1979) defines L as ln(AIG) where A and G are respectively the (population-weighted) arithmetic and geometric means. It is, however, mathe- matically equivalent to equation (1) which also defines Theil’s population-weighted index of inequality.

5. Note that all such indices are defined for income inequality, but can be adapted to the measurement of inequality in other indicators of well-being. Therefore, the terms “income” and “population” need to be interpreted separately for each variable. The different meanings of “income” are obvious; the variable would be measured in calories (or percent) for calorie intake, in years for life expectancy, and number of literates for literacy. Item 6 of Appendix A clarifies the “population weights” that are appropriate for each variable.

6. Variation in the number of sample countries is caused by data limitations. An attempt was made to achieve comparability across the years for each variable while keeping the samples as large as possible. Appen- dix B lists the sample countries.

7. This observation is based on the 112-country sample derived from Summers-Heston (1988) data. A larger sample of 129 countries for 1988, based on World Bank (1989), shows the inequality index to be even higher at 1.383. In addition, later discussion in the text and Table 2 provide a comparison of the position for two different measures of inequality.

8. This possibility was also brought out by Ram (1989).

9. World Bank (1989) data on conventional GNP per capita for 1988 show that the index of inequality without China (N = 129) is 1.383, and increases to 1.435 if China is included. Moreover, there is some- thing puzzling about the information on China reported by the World Bank. For example, the World Develop- ment Report 1990 (World Bank, 1990, p. 178) shows China’s GNP per capita in 1988 as US $330, and also reports an annual growth rate of 5.4% during 1965-88. Taken literally, the growth rate implies that China’s GNP per capita for 1965 in 1988 dollars was less than

$100, which would correspond to about $30 in 1965 prices at an average inflation rate of 5% per year. In addition, issues of World Devlopment Report for 1982- 89 show China’s GNP per capita in currerzf dollars as $290 (1980), $300 (1981), $310 (1982), $300 (1983), $310 (1984), $310 (1985), $300 (1986) and $290 (1987). These numbers imply a zero or negative growth rate even in current prices, although these very documents show a high real growth rate for China during the period. Therefore, while it may seem reasonable to believe that inclusion of China would show a better picture regarding intercountry inequality in income, it is not easy to document such a picture, at least for conventional GDP per capita. In regard to basic-needs fulfillment, the inequality picture is so good that inclusion of China is not likely to make a significant difference despite China’s large size and high position in basic-needs indicators.

10. For example, Berry, Bourguignon and Morrisson (1983) have indicated that the picture depends to some extent on the inequality measure used.

11. Additional details concerning the decomposition are available from the author. Theil and Sorooshian (1979) have explained the procedure. Note that while decomposition by income- and population-change is reported here, Theil (1989) presented a regional decomposition for 1960-85.

12. For a sample of 137, which is more comparable to the 1960 sample, the inequality index is even smaller at 0.008.

13. Standard deviation is a well-known measure, and may be defined here as

where pi is the relevant “population” size in country i, X, is the value of the relevant basic-needs indicator for country i, x is the (weighted) sample mean of X,. Absolute mean deviation may similarly be defined as

1 ,gl PZ ABS@; - ml / [ ,9 piI

where ABS denotes the absolute value of the number in parenthesis.

14. Even simple descriptive measures, such as country and regional minima and maxima, can constitute useful supplements in such studies.

15. A perceptive referee raised the question concerning the relation between income and basic-needs fulfillment. That is obviously an important area, but its treatment lies outside the scope of this work. Ram (1985) and many other researchers have dealt with that aspect. In general, it could be stated that income level is positively correlated with basic-needs fulfillment, but


the correlation is imperfect. Therefore, crosscountry author suggests that a quadratic income function does inequalities in income and basic-needs indicators are well in explaining the levels of basic-needs indicators very different, and have been moving in opposite across countries. directions. Some additional ongoing work by the

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Bourguignon, F., “Decomposable income inequality national comparisons of real product and price measures,” Econometrica, Vol. 47 (1979), pp. 901- levels, estimates for 130 countries, 1950-1985,” 920. Review of Income and Wealth, Vol. 34 (1988), pp.

Hicks, N. L., “Growth vs basic needs: Is there a trade- l-25. off?” World Development, Vol. 7, No. 1102 (1979), pp. 985-994.

Hicks, N. L., and P. Streeten, “Indicators of development: The search for a basic needs yardstick,” World Development, Vol. 7, No. 6 (1979), pp. 567- 580.

Leipziger, D. M. (Ed.), Basic Needs and Development (Cambridge, MA: Oelgeschlager, Gunn and Hain, 1981).

Ram, R., “Level of development and income inequality: An extension of Kuznets-hypothesis to the world economy,” Kyklos, Vol. 42 (1989), pp. 7s-88.

Ram, R., “The role of real income level and income distribution in fulfillment of basic needs,” World Development, Vol. 13, No. 5 (1985), pp. 589-594.

Ram, R., “International inequality in the basic needs indicators,” Journal of Development Economics, Vol. 10 (1982) pp. 113-117.

Sheehan, G., and M. Hopkins, Basic Needs Perfor- mance (Geneva: International Labour Office, 1979).

Stewart, F., Basic Needs in Developing Countries (Baltimore, MD: Johns Hopkins University Press, 1985).

Streeten, P., First Things First (New York: Oxford University Press, 1981).

Theil, H., “The development of international inequality 1960-85,” Journal of Econometrics, Vol. 42 (1989) pp. 145-155.

Theil, H., and C. Sorooshian, “Components of the change in regional inequality,” Economics Letters, Vol. 4 (1979), pp. 191-193.

United Nations, World Population Prospects, Estimates and Projections as Assessed in 1984 (New York: United Nations, 1986).

United Nations Development Programme (UNDP), Human Development Report 1990 (New York: Oxford University Press, ‘1990).

Wheeler. D.. “Basic needs fulfillment and economic growth: A simultaneous model,” Journal of Develop- ment Economics, Vol. 7 (1980), pp. 435-451.

World Bank, World Development Report (New York: Oxford University Press,* various years).

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World Bank, Poverty and Basic Needs (Washington, DC: World Bank, September 1980a).

World Bank, World Tables, second edition (Baltimore, MD: Johns Hopkins University Press, 1980b).

APPENDIX A: DATA SOURCES

1. GDPper capita in USdollars Derived from data table of Summers and Heston (1988) by multiplying real GDP per capita in international dollars (RGDPl) with the price level for real GDP. The years are 1960,1970,1978, and 1985, the last being the most recent available.

2. GDPper capita in international dollars The numbers are taken from data table of Summers and Heston (1988).

3. Calorie supply 1960: taken from World Bank (1980b, pp. 449, 451, 453). The variable is calorie supply per capita as percentage of calorie requirements. 1984-86 (most recent year): taken from UNDP (1990, pp. 134-135.)

4. Life expectancy (at birth) 1960: taken from World Bank (1980b, pp. 442, 444, 446). 1988 (most recent year): taken from World Bank (1989,

PP. 6-9).

5. Literacy rate 1960: taken from World Bank (1980b, pp. 455, 457, 459). 1985 (most recent year): derived from World Bank (1989, pp. 6-9) as 100 minus the illiteracy rate.

6. Population “weights” GDP per capita in dollars: The proper weight is the total population size, and the data are taken from Summers and Heston (1988). GDP per capita in international dollars: Total popula-

INTERCOUNTRY INEQUALITIES 90.5

tion is the proper weight, and all numbers are taken from Summers and Heston (1988). Calorie supply: Since calorie supply is “per capita” in both cases-,-population size is the proper weight. For 1960. it is taken from United Nations (1986). For 1985, Summers and Heston (1988) population data are used. Life expectancy: Since this may be treated as roughly the average (mean) life of the population, total

population is taken as the weight, and the sources are United Nations (1986) for 1960 and World Bank (1989) for 1988. Literacy rate: Adult population is the proper weight. For both 1960 and 1985, population aged 15+, derived from United Nations (1986, pp. 159-330), is taken as the relevant measure.

APPENDIX B: LIST OF SAMPLE COUNTRIES

Income inequality, all years (N = 112)

Algeria, Angola, Argentina, Australia, Austria, Bangladesh, Barbados, Belgium, Benin, Bolivia, Bots- wana, Brazil, Burundi, Cameroon, Canada, Central African Republic, Chad, Chile, Colombia, Congo, Costa Rica, C&e d’Ivoire, Cyprus, Denmark, Domini- can Republic, Ecuador, Egypt, El Salvador, Ethiopia, Fiii. Finland. France, Gabon. Gambia, Germanv < (F.R.G.), Greece, Guatemala, Guinea, Guyana, Haiti, Honduras, Hong Kong, Iceland, India, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kenya, South Korea, Kuwait, Lesotho, Liberia, Luxembourg, Madagascar, Malawi, Malaysia, Mali, Malta, Mauri- tania, Mauritius, Mexico, Morocco, Mozambique, Myanmar (Burma), Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria. Norwav, Pakistan. Panama, Papua-New Guinea, Paraguay: Peru, Philippines, Portugal, Rwanda, Saudi Arabia, Senegal, Sierra Leone, Singapore, Somalia, South Africa, Spain, Sri Lanka, Sudan, Suriname, Swaziland, Sweden, Switzer- land, Syria, Tanzania, Thailand, Togo, Trinidad and Tobago, Tunisia, Turkey, Uganda, United Kingdom, United States, Uruguay, Venezeula, Zaire, Zambia, Zimbabwe.

Calorie supply

1960 (N = 119): Income sample with the following additions and exclusions: Additions (8): Afghanistan, Burkina Faso, Ghana, Guinea-Bissau, Indonesia, Lao PDR, Lebanon, and Yemen Arab Republic. Exclusion (1): Swaziland.

198&86 (N = 106): Income sample with the following changes: Additions (5): Afghanistan, Burkina Faso, Ghana, Indonesia and Yemen Arab Republic. Exclu- sions (11): Barbados, Cvprus, Fiii. Gambia, Guvana, Iceland, ‘Kuwait, Luxembourg, Malta, Suriname; and Swaziland.

changes: Additions (14): Afghanistan, Albania, Burkina Faso, Comoros, Equatorial Guinea, Ghana, Guinea-Bissau, Indonesia, Lao PDR, Lebanon, Libya, Mongolia, Oman, and Yemen Arab Republic. Exclu- sion (1): Gambia.

1988 (N = 157): Income sample with the following 45 additions: Albania, Antigua and Barbuda, Bahamas, Belize, Bhutan, Brunei, Burkina Faso, Cape Verde, Channel Islands, Comoros, Dominica, Equatorial Guinea, French Polynesia, Ghana, Grenada, Guade- loupe, Guam, Guinea-Bissau, Indonesia, Kiribati, Lao PDR, Libya, Macao, Maldives, Martinique, Mongolia, Namibia, N. Antilles, New Caldonia, Oman, Puerto Rico, Qatar, Reunion, St. Kitts and Nevis, St. Lucia, St. Vincent, SBo Tome and Principe, Seychelles, Solomon Islands, Tonga, United Arab Emirates, Vanuatu, US Virgin Islands, Western Samoa, Yemen Arab Republic.

Adult literacy

1960 (N = 89): Income sample with the following changes: Additions (8): Afghanistan, Burkina Faso, Ghana, Guinea-Bissau, Indonesia, Lao PDR, Libya, Yemen Arab Republic. Exclusions (31): Angola, Australia, Austria, Belgium, Canada, Chad, Costa Rica, Denmark, Ethiopia, Fiji, France, Germany (F.R.G.), Guyana, Ireland, Israel, Lesotho, Luxem- bourg, Madagascar, Malawi, Netherlands, New Zealand, Nicaragua, Norway, Singapore, Suriname, Swaziland, Sweden, Switzerland, United Kingdom, Uruguav, and Zimbabwe.

1% (k = 89): 1960 sample for literacy with the -- following changes: Additions (1.5): Cape Verde, Chad, Costa Rica, Equatorial Guinea, Ethiopia, Fiji, Guyana, Lesotho, Madagascar, Malawi, Nicaragua, Singapore, Suriname, Swaziland, and Zimbabwe. Exclusions (15): Afghanistan, Barbados, Cyprus, Fin- land, Iceland, Italy, Jamaica, Japan, South Korea, Mauritania, Myanmar (Burma), South Africa, Sudan, Tanzania, and United States.

Life expectancy

1960 (N = 125): Income sample with the following

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Intercountry inequalities in income and basic- needs indicators: A recent perspective