Nafziger Economic Development (4th ed)

186 Part Two. Poverty Alleviation and Income Distribution

FIGURE 6-9. Ratio of Between-Nation to Within-Nation Income Inequality for 199 Nations, 1820–1992. Theil and MLD are measures of inequality.

Sources: Glenn Firebaugh 2003. The New Geography of Global Income Inequality. Cambridge, Mass.: Harvard University Press, p. 25; and Francois Bourguignon and Christian Morrisson 2002. “Inequality among World Citizens: 1820–1992.” American Economic Review 92(4) (September): 736.

reduced global income inequality, compressing inequality across nations and raising inequality within many nations. During the 19th century, the Industrial Revolution transformed the world from poverty as a norm in 1820 to a richer world with lower poverty rates but much greater inequality near the turn of the 20th century and through the mid-20th century (Figure 6-5; Firebaugh 2003:25). However, during the second half of the 20th century, inequality across nations slowed dramatically, so that the between-nation to within-nation inequality ratio stopped growing and eventually fell (Figure 6-9). During the 1990s, between-nation inequality began declining. Firebaugh expects within-nation inequality to rise or at least not decline, whereas between-nation inequality will fall with the continued modernization and industrialization of poor nations. However, “since between-nation inequality is the larger component, global income inequality will decline” (Firebaugh 2003:27). Findings by Ajit K. Ghose (2003:23–39), a senior economist in the Employment Strategy Department of the International Labor Office, are similar to those by Firebaugh.

Early and Late Stages of Development

The Nobel economist Simon Kuznets hypothesized (1955:1–28) that during industrialization, inequality follows an inverted U-shaped curve, first increasing and then decreasing with economic growth. Initially, growth results in lower income shares for the poor and higher income shares for the rich. Irma Adelman’s and Cynthia

Taft Morris’s explanation (1973) for the Kuznets curve presupposes that LDCs are characterized by a dual economy (Chapter 4) in which the modern sector’s income and productivity are significantly higher than the traditional sector’s. They indicate that when economic growth and migration from the traditional to the modern sector begin in a subsistence agrarian economy (production mostly for the use of the cultivator and his family) through the expansion of a narrow modern sector (primarily manufacturing, mining, and processing), income inequality typically increases. Income inequalities have especially worsened where foreign exploitation of natural resources triggered growth. Data indicate that the income shares of the poorest 60 percent and middle 20 percent decline significantly in such a context while the share of the top 5 percent increases strikingly – particularly in low-income countries with a sharply dualistic economy dominated by traditional or foreign elites.11

Once countries move beyond this early stage, further development generates neither particular increase nor decrease in shares for the top 5 percent. At the very highest income level of a developing country, broad-based social and economic advances usually operate to its relative disadvantage, at least if the government enlarges its role in the economic sphere. However, according to Adelman and Morris, the share of the top 5 percent increases if more natural resources become available for exploitation.

Middle-income groups are the primary beneficiaries of economic development beyond the early, dualistic stage. The first more widely based social and economic advances typically favor the middle sector.

As indicated earlier, the relative position of the poorest 60 percent typically worsens when growth begins. The modern sector competes with the traditional sector for markets and resources, and the result is a decline in the income shares of the poor. Such a decline occurred when peasants became landless workers during the European land consolidation of the 16th through the 19th centuries and when high-yielding varieties of grains were first used on commercial farms in India and Pakistan. Even when economic growth becomes more broadly based, the poorest segments of the population increase their income shares only when the government expands its role, widening opportunities for education and training for lower-income groups (Adelman and Morris 1973:178–183; Adelman and Morris 1978:245–273; Table 6-5).

Do country data over time provide evidence that inequality follows an inverted U-shaped curve as economic development takes place? Time-series data for individual countries are scarce and unreliable, and many LDCs have not yet arrived at a late enough stage of development to test the declining portion of the upsidedown U curve. However, the time-series data available suggest the plausibility of the inverted U-shaped curve for DCs. Income concentration in Britain, Germany, Belgium, the Netherlands, and Denmark increased from preindustrialization to early

11Adelman and Morris (1973) contend that income, not just income shares, falls in early stages of growth, but their evidence does not support this.

188 Part Two. Poverty Alleviation and Income Distribution

TABLE 6-5. Income Shares at Stages of Development

Income Categories

Stages of

Based on Adelman and Morris (1973).

industrialization and decreased from early to late industrialization. Indeed, in late- 19th-century Europe, inequality was very high and was highest in Britain, where the top 10 percent received 50 percent of the income and the bottom 20 percent 4 percent. This distribution is close to that of Brazil and Panama today, where the top 10 percent receive 40–60 percent and the bottom 20 percent no more than 2 percent. Second, the most reliable data for today’s LDCs suggest that since 1970, inequality rose in low-income and lower-middle-income Bangladesh, the Philippines, Colombia, and Thailand and fell in high-income Taiwan, supporting the inverted U, but declined in low-income Pakistan, and middle-income Peru and Costa Rica and increased in upper-middle-income Argentina, Brazil, and Mexico, exceptions to the inverted U (Williamson 1991:10–13; World Bank 1993b:296–297; Sundrum 1992:117–121; Kuznets 1963b: 58–67; Lecaillon, Paukert, Morrisson, and Germidis 1984:42–43; Morris and Adelman 1988; Fields 1980:78–98). Thus, whereas the historical growth of early industrializing Europe followed an inverted U, the evidence for today’s LDCs is too mixed and inconclusive to confirm the Kuznets curve.

Low-, Middle-, and High-Income Countries

Evidence for the Kuznets curve is stronger when we classify a group of countries in a given time period by per capita income levels. The relationship between inequality (as measured by the Gini index) and gross domestic product per capita is an inverted U skewed to the right. Figure 6-10, based on World Bank (2003h:14–16, 64–66) estimates of income distribution in 80 countries (except transitional economies) during the late 1990s, exemplifies the upside-down U relationship. Ahluwalia and his collaborators rank income inequality as high if the income share of the poorest 40 percent is less than 12 percent of GNP; moderate if it is between 12 and 17 percent; and low if 17 percent and above (Ahluwalia, Carter, and Chenery 1979:299–341; Ahluwalia 1974:1–22). Among the 80, 30 percent of low-income countries, 52 percent of middle-income countries, and 0 percent of high-income countries have high income inequality. By contrast, 37 percent of low-income countries,

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systematically; correlations between income inequality and early modern economic growth “are bound to be poor since history has given less developed countries very different starting points.” Indeed, there is much more variation in relative inequality within country income groups than between them. (We discuss factors other than income later.) Income level is an imprecise predictor of a country’s income inequality (Fields 1980:67; Fields 2001).

INCOME INEQUALITY IN DEVELOPED AND DEVELOPING COUNTRIES

The overwhelming majority of developed (high-income) countries have low income inequality (and none have high income inequality), whereas only 27 percent of the developing countries have low inequality (and 41 percent high inequality). The income shares of the poor are higher and their variance lower in DCs than in LDCs. Whereas the conclusion that the poorest 40 percent in high-income countries receive 18 percent compared to 13 percent for low-income countries is not distorted, the indication that poor in middle-income countries receive 12 percent overstates their equality. First, in LDCs personal and household income concentrations are approximately the same, whereas in DCs concentrations for persons is less than for households, as household size increases rapidly from lowerto upper-income classes. Suppose that DCs, whose income distribution is ranked by households, would have followed the approach of the LDCs in having their income distribution data ranked by persons. Then DC distribution data would have been even more egalitarian vis-a`-vis LDC data than what appears in Figure 6-10. Second, in DCs, inequalities measured over a lifetime are markedly lower than those measured over a year, whereas in LDCs inequalities do not vary with the period chosen. Third, LDC life expectancies are highly correlated with average incomes, frequently contributing to interethnic, metropolitan–rural, and skilled–unskilled working life disparities of 10 to 15 years; in DCs these disparities are usually not so great. (In the United States, where these disparities are greater than for DCs generally, a 78-year life expectancy for white Americans compares to an African-American life expectancy of 72 years.) Fourth, progressive income taxes (with higher tax rates for higher incomes) and social welfare programs make income more equal in developed countries than nominal figures indicate. Fifth, however, LDC (especially in a low-income country) urban–rural income discrepancies are overstated, because rural in-kind incomes are undervalued and rural living costs are usually 10–20 percent lower than urban costs. Sixth, retained corporate profits, which accrue disproportionately to upper-income classes, and are a significant fraction of GNP in DCs and many middle-income countries but usually omitted in income distribution estimates, contribute to overstating equality in high-income countries. Thus, overall, the first four distortions are probably balanced by the fifth and sixth distortions, so that the comparison DCs’ and low-income countries’ income distributions is unchanged. However, middle-income countries are affected so little by distortions 5 and 6 that these are outweighed by the first four distortions, which increase the disparity in income concentrations between DCs and middle-income countries (Lecaillon, Paukert, Morrisson, and Germidis 1984:34–52; Kuznets 1976:1–44; U.N. Development Program 1993:18, 26; UN Development

Program 1994:98).13 These distortions make the inverted U even more pronounced than data suggest.

Slow and Fast Growers

As already indicated, countries at earlier and lower levels of development are more likely to experience increases in income inequality. However, higher rates of economic growth, which are only weakly correlated with GNP per capita, are not associated with either greater equality or inequality. Both fast growers, such as Malaysia, Mexico, Chile, Brazil, and Botswana, and slow growers, such as Kenya, Nigeria, Cameroon, Honduras, Nicaragua, Guatemala, Panama, and Peru, have high income inequalities. And slow-growing Uganda, Ghana, Coteˆ d’Ivoire, Rwanda, Burundi, Cuba, and Hungary and fast-growing Taiwan, South Korea, India, Pakistan, Sri Lanka, Indonesia, Israel, Greece, Portugal, and Poland have low income inequalities.

To be sure, Alberto Alesina and Dani Rodrik find that income inequality is negatively correlated with subsequent economic growth among DCs. But when less reliable data from LDCs are included, the coefficient is no longer statistically significant at the 5-percent level. Moreover, the lack of significance holds true for both democracies and nondemocracies (Alesina and Rodrik 1994:465–490).

Women, Poverty, Inequality, and Male Dominance

The major victim of poverty is the female, especially the single head of household responsible for child care but lacking support from males, the state, or informal networks. Narayan et al. (2000:15–28), Voices of the Poor, based on 81 detailed reports from interviews of the poor in 50 LDCs, examines how changing roles of men and women require shifts in internalized norms about and behavior toward women. Male alcoholism and domestic violence get their share of the blame, but the authors also attribute male reaction to the stress from the loss of traditional livelihoods and the unraveling of social safety nets.

Development economics assumes that government policies should be directed to resource allocation among households or families. Partha Dasgupta, however, stresses the allocation of food, education, health care, and work between men and women, young and old, boys and girls, and lowerand higher-birth-order children. Most data are biased, Dasgupta contends, because they fail to show this major source of interpersonal inequality. In many parts of the world, income inequality would be 30–40 percent higher if intrahousehold distribution were included. Gender ideologies commonly support the notion that men have the right to personal spending money (sometimes even when overall income is inadequate), while women’s income is for

13The last two sources give figures on black–white disparities in the United States. In 1992, GDP per capita, in purchasing-power-adjusted dollars, was $22,000 for whites and $17,100 for blacks, while infant mortality rates for whites was 8 per 1,000 and for blacks 19.

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collective purposes. According to Dasgupta, the higher infant mortality and other age-specific death rates for females relative to males in India, China, and the Middle East indicate a substantial antifemale bias in nutrition and health care (Dasgupta 1993:17, 311; Sen 1992:122–125; Dwyer and Bruce 1988:1–11). Indeed, M. R. Rosenzweig and T. P. Schultz (1982:803–815) argue that the lower rates of returns to female relative to male labor explain the low survival rates among girls.

In most precolonial Afro-Asian societies, patriarchal authority severely limited the power of women, who were protected if they were deferential to the patriarchs. Yet some societies gave women clearly defined economic roles, allowing wealth accumulation and limited economic authority.

Most Afro-Asian women lost their limited power under colonialism. Men received land titles, extension assistance, technical training, and education. When men left farms to seek employment, as in South Africa, women remained burdened with responsibility for the family’s food. A few women, especially West African market traders, became wealthy, but the majority worked long hours to survive. In the 1930s through 1950s, colonial authorities colluded with patriarchal indigenous leaders to increase control over women. In some instances, where they had an independent economic base, women used traditional female organizations and methods, not confrontation to male authority, to oppose both European and local authorities. Women played a prominent role in many of the early nationalist struggles, especially when colonialists threatened their economic interests.

After independence low female literacy (two-thirds that for men, now nine-tenths of men’s in LDCs), limited economic opportunity, and domestic burdens relegated women to the lowest economic rungs, even in countries claiming to be socialist, such as Ethiopia, which allocated land to male family heads during land reform in the 1970s. Government agricultural policy favored male heads of households and development plans often ignored women. Moreover, male migration to urban areas or to neighboring countries (as in Yemen, the Sudan, and Botswana) places women at a further disadvantage. Nevertheless, economic or political crises sometimes benefit women, as men seek new alliances between sexes in rebuilding weak economies and polities.

The ILO estimated that women comprised 513 million, or 34 percent of the LDC labor force of 1,510 million, and 766 million, or 36 percent, of the global labor force of 2,129 million in 1990. Although this proportion remained roughly constant from 1950 through 1980, women have increased their share slightly since then. Females receive an average income half that of males in LDCs (three-fourths in Latin America), partly from crowding, the tendency to discriminate against women (and minorities) in well-paying jobs, forcing them to increase the supply of labor for menial or lowpaying jobs. Although women are frequently the backbone of the rural economy, in a modernizing economy, they enjoy few advantages. Although men seek wage employment in cities, women play the dominant role in small-scale farming, often on smaller plots and with lower returns than male-headed households. Women’s workloads are heavy as a result of childbearing (four children in the average rural LDC

family), carrying water (two hours spent daily by many African women), collecting wood, increased weeding from new crop varieties, and other farm tasks caused by growing rural population pressures. Additionally, when technological innovations increase the productivity of cash crops, men frequently divert hectares from women’s food crops. Moreover, women as a rule receive lower returns to training and education (university rates of return are negative for Kenyan women) because of discrimination, withdrawal from the labor force, and having to live in the same place as their husbands. Moreover, in Accra, Ghana female workers shoulder most of the responsibility for cooking, cleaning, laundry, and other housework, although two-thirds of the male workers do not do any housework, a pattern similar to that in many other cultures, such as the United States and Western Europe (World Bank 2003h:45; Parpart 1986:278–292; U.N. Department of International Economic and Social Affairs 1986:12, 70; Lecaillon, Paukert, Morrisson, and Germidis 1984:80– 81; Bloom and Brender 1993:8–9; House and Killick 1983:31–69; Bigsten 1984:134– 147; Date-Bah 1989:59–65; Nafziger 1988:45–46, 124–126; Jazairy, Alamgir, and Panuccio 1992:78–84; Terrell 1992:387–404).

One striking demographic feature of the contemporary world that reflects the unequal treatment of women is the enormous geographic variation in the ratio of females to males. Medical evidence indicates that, given similar care, women have lower death rates than men. Thus, in North America and Europe, although men outnumber women at birth, women have lower mortality rates, outnumbering men by 105 to 100.

In many LDCs, however, the ratio of females to males is lower: 1.02 in sub-Saharan Africa, 0.98 in North Africa, 0.94 in China, Bangladesh, and the Middle East, 0.91 in Pakistan, and 0.93 in India, but 1.04 in Kerala state, known for its progressive policies toward females (Chapter 2). Amartya Sen uses sub-Saharan Africa as a benchmark to estimate “missing” women in female-deficit LDCs. He estimates 44 million missing females in China and 37 million in India.

The missing women reflect the antifemale biases in these cultures. In China, where the state irregularly enforces a “one couple, one child” policy, expectant couples may use sonograms to identify the gender of the fetus, sometimes aborting female children. Also a small fraction of Indian and Chinese couples practice female infanticide. Additionally, Amartya Sen found that in Mumbai, India, women had to be more seriously ill than men to be taken to a hospital. India, China, and some other LDCs with low female-to-male ratios have a bias in nutrition and health care that favors males. Discrimination against women in schools, jobs, and other economic opportunities lies behind the bias against the care of females within the family (Sen 1993:40–47).

The findings about intrafamily distribution suggest the error of merely directing resources to the household as a unit or to the nominal household head. Policy makers interested in inequality cannot stand clear of the issue of internal distribution within a household but may need to examine policies to see whether they discriminate against women or children (Dwyer and Bruce 1988:3).

194 Part Two. Poverty Alleviation and Income Distribution

Accompaniments of Absolute Poverty

The 400 to 1,100 million people living in absolute poverty (no more than $1/day in 1988PPP) suffer the following deprivations:

1.Threeto four-fifths of their income is spent on food; the diet is monotonous, limited to cereals, yams, or cassavas, a few vegetables, and in some regions, a little fish or meat.

2.About 50 percent are undernourished and hundreds of millions are severely malnourished. Energy and motivation are reduced; performance in school and at work is undermined; resistance to illness is low; and the physical and mental development of children is often impaired.

3.One of every ten children born dies within the first year; another dies before the age of 10; and only five reach the age of 45.

4.Beginning in 1975, the World Health Organization (WHO) and UNICEF expanded immunization against the major diseases of the developing world. Immunization rates increased rapidly, and deaths from these diseases fell substantially in LDCs from the 1980s to the 1990s. Still fewer than 60 percent of the children in absolute poverty are vaccinated against measles, diphtheria, and whooping cough, which have been virtually eliminated in rich countries. These diseases are still frequently fatal in developing countries. A case of measles is 35 times more likely to kill a child in a low-income country than in the United States.

5.Two-thirds of the poor lack access to safe and plentiful water and even a larger proportion lack an adequate system for disposing of their feces. Lack of sanitation, a problem of virtually all the poor, contributes to 900 million diarrheal diseases yearly. These diseases cause the death of three million children annually, most preventable with adequate sanitation and clean water.

6.Average life expectancy is about 45 years, compared to 78 years in developed countries.

7.Only about one-third to two-fifths of the adults are literate.

8.Only about 4 of every 10 children complete more than four years of primary school.

9.The poor are more likely to be concentrated in environmentally marginal and vulnerable areas, face higher rates of unemployment and underemployment, and have higher fertility rates than those who are not poor (World Bank 2003h; Mehrotra, Vandemoortele, and Delamonica 2000; World Bank 1993b; World Bank 1992i:5; World Bank 1990i; World Bank 1980i:33; U.N. Development Program 2003; U.N. Development Program 1993; UNICEF 1994).14

You should remember that as we analyze the problems of LDCs in subsequent chapters, the problems of the LDCs’ poor are even more severe than those of LDCs generally.

14UNICEF (1995:24–27) indicates the progress in reducing diarrhea through oral rehydration therapy and lessons for the mothers of infants.

Identifying Poverty Groups

1.Four-sevenths of the world’s absolute poor ($1/day poverty) live in sub-Saharan Africa. Nigeria, Democratic Republic of Congo, Ethiopia, Tanzania, and Kenya and comprise three-fourths of the sub-Sahara’s poor. More than one-sixth live in East Asia (mainly China) and one-sixth in South Asia (primarily India, Bangladesh, Nepal, and Pakistan). The remaining fraction is divided between the Middle East and Latin America (Bhalla 2002:148 for regional, Sala-i-Martin 2002:38–41 for national figures). By 2015, three-fourths of $2/day poverty is expected to be in the sub-Sahara (Bhalla 2002:170).

2.Some indigenous and minority groups are overrepresented among the poor; these include the Indians in Latin America and Dalits (outcastes) in India. An indigenous woman in Asociacin de 10 Agosto, Ecuador remarked:

Because we had not schooling we are almost illiterate. Sometimes we cannot even speak Spanish; we can’t add. Store-owners cheat us, because we don’t know how to count or anything else. They buy at the prices they want and pay less. They cheat us because we are not educated. (World Bank 2001h: 123)

3.Four-fifths of the poor live in rural areas, most of the rest in urban slums – but almost all in crowded conditions. The rural poor are the landless workers, sharecroppers, tenants, and small landowners. The urban poor include the unemployed, irregularly employed, menial workers, some small shopkeepers, artisans, and traders.

4.Compared to the lowest income classes in DCs, a much smaller percentage of the poor in the LDCs are wage laborers, or unemployed and searching for work (see later, on policies). Most of the poor work long hours as farmers, vendors, artisans, or hired workers. A few self-employed may own a small piece of land, some animals, or some tools, but many of the poor own no land and have virtually no assets.

5.Most of the poor are illiterate: They have not completed more than a year or two of school. As a result, their knowledge and understanding of the world are severely circumscribed.

6.Women are poorer than men, especially in one-quarter of the world’s households where women alone head households. Under the weight of poverty, men who “fail” to earn adequate income often have difficulty accepting women as the main breadwinners with the concomitant redistribution of family power. In many instances, men retreat into alcoholism, domestic violence, and other antisocial behavior, contributing to the breakdown of the family. The fact that female-headed households are often desperately poor results not only from this poverty-induced breakdown but also the discrimination against women in the labor market (Narayan et al. 2000:6). The female labor force is small, employed in the lowest paid jobs, and characterized by a far greater unemployment rate than the male labor force. Moreover, in households with an adult male, females