Lesson 6 Poverty, Inequality, and Development PDF

# Lesson 6: Poverty, Inequality, and Development Although our primary focus is on economic poverty and inequalities in the distribution of incomes, human capital, and assets, it is important to remember that this is only part of the broader inequality problem in the developing world. Of equal impor...

# Lesson 6: Poverty, Inequality, and Development Although our primary focus is on economic poverty and inequalities in the distribution of incomes, human capital, and assets, it is important to remember that this is only part of the broader inequality problem in the developing world. Of equal importance are inequalities of power, prestige, status, gender, job satisfaction, conditions of work, degree of participation, freedom of choice, self-esteem, and many other dimensions of capabilities to function. As in most social relationships, we cannot separate the economic from the noneconomic manifestations of inequality. Each reinforces the other in a complex and often interrelated process of cause and effect. After introducing appropriate inequality and poverty measures, we define the nature of the poverty and income distribution problem and consider its quantitative significance in various developing nations. We then examine the ways in which economic analyses can shed light on the problem and explore possible alternative policy approaches directed at the elimination of poverty and the reduction of excessively wide disparities in the distributions of income in developing countries. This also provides the basis for analysis in subsequent chapters of more specific development issues, including population growth, education, health, rural development, and environmental degradation. ## Measuring Inequality In this section, we define the dimensions of income distribution and poverty problems and identify similar elements that characterize the problem in many developing nations. But first, we should be clear about what we measure when discussing income distribution and absolute poverty. Economists usually distinguish between two principal measures of income distribution for both analytical and quantitative purposes: the personal or size distribution of income and the functional or distributive factor share distribution of income. ### Size Distributions The personal or size distribution of income is the measure most used by economists. It simply deals with individual persons or households and the total incomes they receive. How they received that income is not considered. What matters is how much each earns, irrespective of whether the income is derived solely from employment or other sources such as interest, profits, rents, gifts, or inheritance. Moreover, the locational (urban or rural) and occupational sources of income (e.g., agriculture, manufacturing, commerce, services) should be addressed. To define the personal distribution of income (size distribution of income), The distribution of income according to size class of persons—for example, the share of total income accruing to the poorest specific percentage or the richest specific percentage of a population— without regard to the sources of that income. Economists and statisticians, therefore, like to arrange all individuals by ascending personal incomes and then divide the total population into distinct groups or sizes. A common method is to divide the population into successive quintiles (fifths) or deciles (tenths) according to ascending income levels and then determine what proportion of the total national income is received by each income group. A quintile is a 20% proportion of any numerical quantity. A population divided into quintiles would be divided into five groups of equal size. Decile A 10% portion of any numerical quantity; a population divided into deciles would be divided into ten equal numerical groups. | Individuals | Personal Income (money units) | Share of Total Income (%) Quintiles | Share of Total Income (%) Deciles | |---|---|---|---| | 1 | 0.8 | | 1.8 | | 2 | 1.0 | | | | 3 | 1.4 | | | | 4 | 1.8 | 5 | 3.2 | | 5 | 1.9 | | | | 6 | 2.0 | | | | 7 | 2.4 | | | | 8 | 2.7 | 9 | 3.9 | | 9 | 2.8 | | 5.1 | | 10 | 3.0 | | 5.8 | | 11 | 3.4 | | | | 12 | 3.8 | 13 | 7.2 | | 13 | 4.2 | | | | 14 | 4.8 | | 9.0 | | 15 | 5.9 | | | | 16 | 7.1 | 22 | 13.0 | | 17 | 10.5 | | | | 18 | 12.0 | | 22.5 | | 19 | 13.5 | 51 | 28.5 | | 20 | 15.0 | 100 | 100.0 | | Total (national income) | 100.0 | 100 | 100.0 | For example, Table 5.1 shows a hypothetical but typical income distribution for a developing country. In this table, 20 individuals, representing the country's entire population, are arranged in order of ascending annual personal income, ranging from the individual with the lowest income (0.8 units) to the one with the highest (15.0 units). All individuals' total or national income amounts to 100 units and is the sum of all entries in column 2. In column 3, the population is grouped into quintiles of four individuals each. The first quintile represents the income scale's bottom 20% of the population. This group receives only 5% (i.e., 5 money units) of the total national income. The second quintile (individuals 5 to 8) receives 9% of the total income. Alternatively, the bottom 40% of the population (quintiles 1 plus 2) receives only 14% of the income, while the top 20% (the fifth quintile) receives 51% of the total income. A standard measure of income inequality (the disproportionate distribution of total national income among households.) that can be derived from column 3 is the ratio of the incomes received by the top 20% and bottom 40% of the population. This ratio, sometimes called a Kuznets ratio after Nobel laureate Simon Kuznets, has often been used to measure the degree of inequality between high- and low-income groups in a country. In our example, this inequality ratio is equal to 51 divided by 14, or approximately 3. To provide a more detailed breakdown of the size distribution of income, decile (10%) shares are listed in column 4. We see, for example, that the bottom 10% of the population (the two poorest individuals) receives only 1.8% of the total income, while the top 10% (the top two richest individuals) receives 28.5%. Finally, if we wanted to know what the top 5% receives, we would divide the total population into 20 equal groups of individuals (in our example, this would simply be each of the 20 individuals) and calculate the percentage of total income received by the top group. Table 5.1 shows that the top 5% of the population (the twentieth individual) receives 15% of the income, a higher share than the combined shares of the lowest 40%. ### Lorenz Curves Another common way to analyze personal income statistics is to construct what is known as a Lorenz curve. Figure 5.1 shows how it is done. The numbers of income recipients are plotted on the horizontal axis, not in absolute terms but in cumulative percentages. For example, at point 20, we have the lowest (poorest) 20% of the population; at point 60, we have the bottom 60%; and at the end of the axis, all 100% of the population has been accounted for. The vertical axis shows the share of total income received by each percentage of the population. It is also cumulative up to 100%, meaning that both axes are the same length. The entire figure is enclosed in a square, and a diagonal line is drawn from the lower left corner (the origin) of the square to the upper right corner. At every point on that diagonal, the percentage of income received is exactly equal to the percentage of income recipients—for example, the point halfway along the length of the diagonal represents 50% of the income being distributed to exactly 50% of the population. At the three-quarters point on the diagonal, 75% of the income would be distributed to 75% of the population. In other words, the diagonal line in Figure 5.1 is representative of “perfect equality" in size distribution of income. Each percentage group of income recipients is receiving that same percentage of the total income; for example, the bottom 40% receives 40% of the income, while the top 5% receives only 5% of the total income.  The Lorenz curve shows the actual quantitative relationship between the percentage of income recipients and the percentage of the total income they did in fact receive during, say, a given year. In Figure 5.1, we have plotted this Lorenz curve using the decile data contained in Table 5.1. In other words, we have divided both the horizontal and vertical axes into ten equal segments corresponding to each of the ten decile groups. Point A shows that the bottom 10% of the population receives only 1.8% of the total income, point B shows that the bottom 20% is receiving 5% of the total income, and so on for each of the other eight cumulative decile groups. Note that at the halfway point, 50% of the population is in fact receiving only 19.8% of the total income. The more the Lorenz line curves away from the diagonal (line of perfect equality), the greater the degree of inequality represented. The extreme case of perfect inequality (i.e., a situation in which one person receives all the national income while everybody else receives nothing) would be represented by the congruence of the Lorenz curve with the bottom horizontal and right-hand vertical axes. Because no country exhibits either perfect equality or perfect inequality in its distribution of income, the Lorenz curves for different countries will lie somewhere to the right of the diagonal in Figure 5.1. The greater the degree of inequality, the greater the bend and the closer to the bottom horizontal axis the Lorenz curve will be. ### Gini Coefficients and Aggregate Measures of Inequality A final and very convenient shorthand summary measure of the relative degree of income inequality in a country can be obtained by calculating the ratio of the area between the diagonal and the Lorenz curve divided by the total area of the half-square in which the curve lies. In Figure 5.3, this is the ratio of the shaded area A to the total area of the triangle BCD. This ratio is known as the Gini concentration ratio or Gini coefficient, named after the Italian statistician who first formulated it in 1912.  Gini coefficients are aggregate inequality measures that can vary from 0 (perfect equality) to 1 (perfect inequality). As you will soon discover, the Gini coefficient for countries with highly unequal income distributions typically lies between 0.50 and 0.70. In contrast, for countries with relatively equal distributions, it is on the order of 0.20 to 0.35. The coefficient for our hypothetical distribution of Table 5.1 and Figure 5.1 is approximately 0.44—a relatively unequal distribution. Four possible Lorenz curves such as might be found in international data are drawn in Figure 5.4. In the “Lorenz criterion” of income distribution, whenever one Lorenz curve lies above another Lorenz curve, the economy corresponding to the upper Lorenz curve is more equal than that of the lower curve. Thus, economy A may unambiguously be said to be more equal than economy D. Whenever two Lorenz curves cross, such as curves B and C, the Lorenz criterion states that we “need more information” or additional assumptions before we can determine which of the underlying economies is more equal. For example, we might argue on the grounds of the priority of addressing problems of poverty that curve B represents a more equal economy, since the poorest are richer, even though the richest are also richer (and hence the middle class is “squeezed”). But others might start with the assumption that an economy with a stronger middle class is inherently more equal, and those observers might select economy C.  One could also use an aggregate measure such as the Gini coefficient to decide the matter. As it turns out, the Gini coefficient is among a class of measures that satisfy four highly desirable properties: the anonymity, scale independence, population independence, and transfer principles. The anonymity principle simply means that our measure of inequality should not depend on who has the higher income; for example, it should not depend on whether we believe the rich or the poor to be good or bad people. The scale independence principle means that our measure of inequality should not depend on the size of the economy or the way we measure its income; for example, our inequality measure should not depend on whether we measure income in dollars or in cents or in rupees or rupiahs, or for that matter on whether the economy is rich on average or poor on average—because if we are interested in inequality, we want a measure of the dispersion of income, not its magnitude (note that magnitudes are very important in poverty measures). The population independence principle is somewhat similar; it states that the measure of inequality should not be based on the number of income recipients. For example, the economy of China should be considered no more or less equal than the economy of Vietnam simply because China has a larger population than Vietnam. Finally, we have the transfer principle (sometimes called the Pigou-Dalton principle after its creators); it states that, holding all other incomes constant, if we transfer some income from a richer person to a poorer person (but not so much that the poorer person is now richer than the originally rich person), the resulting new income distribution is more equal. If we like these four criteria, we can measure the Gini coefficient in each case and rank the one with the larger Gini as more unequal. However, this is not always a perfect solution. For example, the Gini coefficient can, in theory, be identical for two Lorenz curves that cross; can you see why by looking at curves B and C in Figure 5.4? And sometimes different inequality measures that satisfy our four properties can give different answers as to which of two economies are more unequal. Note that a measure of dispersion common in statistics, the coefficient of variation (CV), which is simply the sample standard deviation divided by the sample mean, is another measure of inequality that also satisfies the four criteria. Although the CV is more commonly used in statistics, the Gini coefficient is often used in studies of income and wealth distribution due to its convenient Lorenz curve interpretation. Note, finally, that we can also use Lorenz curves to study inequality in the distribution of land, in education and health, and in other assets. ## Measuring Absolute Poverty Now let’s switch our attention from relative income shares of various percentile groups within a given population to the fundamentally important question of the extent and magnitude of absolute poverty in developing countries. ### Income Poverty We defined the extent of absolute poverty as the number of people who are unable to command sufficient resources to satisfy basic needs. They are counted as the total number living below a specified minimum level of real income—an international poverty line. That line knows no national boundaries, is independent of the level of national per capita income, and considers differing price levels by measuring poverty as anyone living on less than $1.90 a day (or sometimes other absolute thresholds) in PPP dollars. Absolute poverty is sometimes measured by the number, or “headcount,” of those whose incomes fall below the absolute poverty line. When the headcount is taken as a fraction of the total population, N, we define the headcount index, (also referred to as the “headcount ratio”). The poverty line is set at a level that remains constant in real terms so that we can chart our progress on an absolute level over time. The idea is to set this level at a standard below which we would consider a person to live in “absolute human misery,” such that the person's health is in jeopardy. Certainly, one would unquestionably not accept the international poverty level of $1.90 a day when planning local poverty work. One practical strategy for determining a local absolute poverty line is to start by defining an adequate basket of food, based on nutritional requirements from medical studies of required calories, protein, and micronutrients. Then, using local household survey data, one can identify a typical basket of food purchased by households that just barely meet these nutritional requirements. One then adds other expenditures of this household, such as clothing, shelter, and medical care, to determine the local absolute poverty line. Depending on how these calculations are done, the resulting poverty line may come to more than $1.90 per day at PPP. ## Poverty, Inequality, and Social Welfare What is it About Extreme Inequality That’s So Harmful to Economic Development? Throughout this chapter, we assume that social welfare depends positively on the level of income per capita, but negatively on poverty and negatively on the level of inequality, as these terms have just been defined. The problem of absolute poverty is obvious. No civilized people can feel satisfied with a situation in which their fellow humans exist in conditions of such absolute human misery, which is probably why every major religion has emphasized the importance of working to alleviate poverty and is at least one of the reasons why international development assistance has the nearly universal support of every democratic nation. But it may reasonably be asked if our top priority is the alleviation of absolute poverty, why should relative inequality be a concern? We have seen that inequality among the poor is a critical factor in understanding the severity of poverty and the impact of market and policy changes on the poor, but why should we be concerned with inequality among those above the poverty line? There are three major answers to this question. First, extreme income inequality leads to economic inefficiency. This is partly because at any given average income, the higher the inequality, the smaller the fraction of the population that qualifies for a loan or other credit. Indeed, one definition of relative poverty is the lack of collateral. When low-income individuals (whether they are poor or not) cannot borrow money, they generally cannot adequately educate their children or start and expand a business. Moreover, with high inequality, the overall rate of savings in the economy tends to be lower because the highest rate of marginal savings is usually found among the middle classes. Although the rich may save a larger dollar amount, they typically save a smaller fraction of their incomes and almost always save a smaller fraction of their marginal incomes. Landlords, business leaders, politicians, and other rich elites are known to spend much of their incomes on imported luxury goods, gold, jewelry, expensive houses, and foreign travel or to seek safe havens abroad for their savings in what is known as capital flight. Such savings and investments do not add to the nation's productive resources; in fact, they represent substantial drains on these resources. In short, the rich do not generally save and invest significantly larger proportions of their incomes (in the real economic sense of productive domestic saving and investment) than the middle class or even the poor. Furthermore, inequality may lead to an inefficient allocation of assets. High inequality leads to an overemphasis on higher education at the expense of quality universal primary education, which may not only be inefficient but is also likely to generate more inequality in incomes. Moreover, high inequality of land ownership— characterized by the presence of huge lati - funds (plantations) alongside tiny minifundios that are incapable of supporting even a single family-also leads to inefficiency because the most efficient scales for farming are family and medium-sized farms. These factors can result in a lower average income and a lower economic growth rate when inequality is high. The second reason to be concerned with inequality above the poverty line is that extreme income disparities undermine social stability and solidarity. Also, high inequality strengthens the political power of the rich and, hence, their economic bargaining power. Usually, this power will be used to encourage outcomes that are favorable to them. High inequality facilitates rent- seeking, including excessive lobbying, large political donations, bribery, and cronyism. When resources are allocated to such rent-seeking behaviors, they are diverted from productive purposes that could lead to faster growth. Even worse, high inequality makes it very difficult for poor institutions to improve. The few with money and power are likely to view themselves as worse off from socially efficient reform, so they have the motive and the means to resist it. Of course, high inequality may also lead the poor to support populist policies that can be self- defeating. Countries with extreme inequality, such as El Salvador and Iran, have undergone upheavals or extended civil strife that have cost countless lives and set back development progress by decades. High inequality is also associated with pathologies such as higher violent crime rates. In summary, with high inequality, politics often tends to be on supporting or resisting the redistribution of the existing economic pie rather than on policies to increase its size. Finally, extreme inequality is generally viewed as unfair. The philosopher John Rawls proposed a thought experiment to help clarify why this is so. Suppose that before you were born into this world, you had a chance to select the overall level of inequality among the earth's people but not your own identity. That is, you might be born as Bill Gates, but you might be born as the most wretchedly poor person in rural Ethiopia with equal probability. Rawls calls this uncertainty the “veil of ignorance.” When facing this kind of risk, would you vote for an income distribution that is more equal or less equal than the one you see around you? If the degree of equality had no effect on the level of income or rate of growth, most people would vote for nearly perfect equality. Of course, if everyone had the same income, no matter what, there would be little incentive to work hard, gain skills, or innovate. As a result, most people vote for some inequality of income outcomes to the extent that these correspond to incentives for hard work or innovation. But even so, most vote for less inequality than in the world (or virtually any country) today. This is because much of the inequality we observe in the world is based on luck or extraneous factors, such as the inborn ability to kick a football or the identity of one's great-grandparents. (Although extending uncertainty to before one's birth is a purely mental exercise, experimental evidence has shown that behind the equivalent of a Rawlsian veil, people can overcome the free rider problem, contributing an appropriate amount to pay for public goods.) ### Kuznets's Inverted-U Hypothesis Simon Kuznets suggested that in the early stages of economic growth, the distribution of income will tend to worsen; only at later stages will it improve This observation came to be characterized by the “inverted-U” Kuznets curve because a longitudinal (time-series) plot of changes in the distribution of income—as measured, for example, by the Gini coefficient— seemed, when per capita GNI expanded, to trace out an inverted U- shaped curve in some of the cases Kuznets studied, as illustrated in Figure 5.9. Kuznets curve is a graph reflecting the relationship between a country's income per capita and its inequality of income distribution.  There are numerous explanations as to why inequality might worsen during the early stages of economic growth before eventually improving. They almost always relate to the nature of structural change. In accordance with the Lewis model, early growth may be concentrated in the modern industrial sector, where employment is limited but wages and productivity are are high. As just noted, the Kuznets curve can be generated by a steady process of modern-sector enlargement growth as a country develops from a traditional to a modern economy. Alternatively, returns to education may rise as the emerging modern sector demands skills and then fall as the supply of educated workers increases and the supply of unskilled workers falls. So, while Kuznets did not specify the mechanism by which his inverted-U hypothesis was supposed to occur, it could, in principle, be consistent with a sequential process of economic development. But, as shown earlier, traditional- and modern-sector enrichment would tend to pull inequality in opposing directions, so the net change in inequality is ambiguous, and the validity of the Kuznets curve is an empirical question. Disregarding the the merits of the methodological debate, few development economists would argue that the Kuznets sequence of increasing and declining inequality is inevitable. There are now enough case studies and specific examples of countries such as Taiwan, South Korea, Costa Rica, and Sri Lanka to demonstrate that higher income levels can be accompanied by falling and not rising inequality. It all depends depends on on the nature of the development process. and levels of per capita income, let us look now briefly at the relationship, if any, between economic growth and inequality. During the 1960s and 1990s, per capita growth in East Asia averaged 5.5% while that of Africa declined by 0.2%, yet both Gini coefficients remained unchanged. Once again, it is not just the rate but also the character of economic growth (how it is achieved, who participates, which sectors are given priority, what institutional arrangements are designed and emphasized, etc.) that determines the degree to which that growth is or is not reflected in improved living standards for the poor. Inequality can stay the same for higher growth to be sustained. ## Economic Characteristics of High-Poverty Groups So far, we have painted a broad picture of the income distribution and poverty problem in developing countries. We have argued that the magnitude of absolute poverty results from a combination of low per capita incomes and highly unequal distributions of that income. Clearly, for any given distribution of income, the higher the level of per capita income, the lower the number of the poor. However, higher levels of per capita income are no guarantee of lower poverty levels. An understanding of the nature of the size distribution of income is therefore central to any analysis of the poverty problem in low-income countries. ### Children and Poverty In most countries, the level of poverty is greater among children than among adults. The 2018 MPI was explicitly applied to disaggregate the extent of child poverty, finding that half of all those in MPI poverty are children. This means that more than a third of all children globally are living in multidimensional poverty. UNICEF has found that extreme poverty disproportionately affects children. In a 2016 report, UNICEF estimated that close to 385 million children were living in extremely poor households in 2013, so that they represented about half of the extreme poor, even though children represented only a third of the population. ### Women and Poverty Women make up a substantial majority of the world's poor. If we compared the lives of the inhabitants of the poorest communities throughout the developing world, we would discover that virtually everywhere, women and children experience the harshest deprivation. They are more likely to be poor, malnourished, and less likely to receive medical services, clean water, sanitation, and other benefits. The prevalence of female-headed households, the lower earning capacity of women, and their limited control over their spouses' income all contribute to this disturbing phenomenon. In addition, women have less access to education, formal-sector employment, social security, and government employment programs. These facts combine to ensure that poor women's financial resources are meager and unstable relative to men's. A highly disproportionate number of the ultra-poor live in households headed by women, in which there are generally no male wage earners. Because the earning potential of women is considerably below that of their male counterparts, women are more likely to be among the very poor. In general, women in female-headed households have less education and lower incomes. Furthermore, the larger the household is, the greater the strain on the single parent and the lower the per capita food expenditure. A portion of the income disparity between male- and female-headed households can be explained by the large earnings differentials between men and women. In addition to the fact that women are often paid less for performing similar tasks, in many cases, they are essentially barred from higher-paying occupations. In urban areas, women are much less likely to obtain formal employment in private companies or public agencies and are frequently restricted to illegal, low- productivity jobs. As in the garment industry, the illegality of piecework prevents it from being regulated and renders it exempt from minimum-wage laws or social security benefits. Even when women receive conventional wage payments in factory work, minimum wage, and safety legislation may be flagrantly ignored. Similarly, rural women have less access to the resources necessary to generate stable incomes and are frequently subject to laws that further compromise earning potential. Legislation and social custom often prohibit women from owning property or signing financial contracts without a husband's signature. Although there are a growing number of exceptions, government employment or income-enhancing programs are accessible primarily, if not exclusively, by men, exacerbating existing income disparities between men and women. However, household income alone fails to describe the severity of women's relative deprivation. Because a higher proportion of female-headed households are situated in the poorest areas, which have little or no access to government- sponsored services such as piped water, sanitation, and health care, household members are more likely to fall ill. They are less likely to receive medical attention. In addition, children in female-headed households are less likely to be enrolled in school and more likely to be working to provide additional income. The economic status of women strongly influences the extent of these internal biases. Studies have found that where women's share of income within the home is relatively high, there is less discrimination against girls, and women are better able to meet their own needs as well as those of their children. When household income is marginal, most women's income is contributed toward household nutritional intake. Since this fraction is considerably smaller for men, a rise in male earnings leads to a less than proportionate increase in the funds available for daily needs. It is thus unsurprising that programs designed to increase nutrition and family health are more effective when targeting women than men. Significant increases in total household income do not necessarily translate into improved nutritional status. The persistence of low levels of living among women and children is shared, where the economic status of women remains low. Development policies that increase the productivity differentials between men and women will likely worsen earnings disparities and further erode women's economic status within the household. Since government programs to alleviate poverty frequently work almost exclusively with men, they tend to exacerbate these inequalities. In urban areas, training programs to increase earning potential and formal-sector employment are generally geared toward men. In contrast, agricultural extension programs promote male-dominated crops, frequently at the expense of women's vegetable plots. Studies have shown that development efforts can increase women's workload while at the same time reducing the share of household resources over which they exercise control. Consequently, women and their dependents remain the most economically vulnerable group in developing countries. The fact that the welfare of women and children is strongly influenced by the design of development policy underscores the importance of integrating women into development programs. Women must be drawn into the economic mainstream to improve living conditions for the poorest individuals. This would entail increasing female participation rates in educational and training programs, formal-sector employment, and agricultural extension programs. It is also essential that precautions be taken to ensure that women have equal access to government resources provided through schooling, services, employment, and social security programs. Legalizing informal-sector employment, where most of the female labor force is employed, would also improve the economic status of women. ## Ethnic Minorities, Indigenous Populations, and Poverty A final generalization about the incidence of poverty in the developing world is that it falls especially heavily on minority ethnic groups and indigenous populations. In recent years, domestic conflicts and even civil wars have arisen out of ethnic groups' perceptions that they are losing out in the competition for limited resources and job opportunities, sometimes involving harsh government-sponsored repression and even genocide to crush Indigenous rights movements, such as in Guatemala. The poverty problem is even more severe for Indigenous peoples, whose numbers are estimated at 370 million in over 5,000 different groups in more than 70 countries. ## Rural Poverty Well over two-thirds of the poor are in rural areas, primarily engaged in agricultural and other natural resource-based livelihoods, mainly as small farmers or as low-paid farmworkers. ## Poor Countries Finally, it should be noted that the poor come from poor countries. Although this may seem like a trivial observation, it is a helpful note of optimism. The negative relationship between poverty and per capita income suggests that if higher incomes can be achieved, poverty will be reduced, if only because of the more excellent resources that countries will have available to tackle poverty problems and the growth of civil society and the voluntary sector. Unfortunately, as noted earlier, a high level of absolute poverty can also retard a country's growth prospects. Moreover, many of the poorest countries in sub- Saharan Africa experienced outright declines in per capita income throughout the 1980s and 1990s and, in some cases, during the first decade of this century. Among those that are growing, at current growth rates, it would take decades to reach the levels of income at which poverty tends to be eradicated. After all, Brazil, which has been a solid middle-income for decades, still has citizens living on less than $1.90 daily. Income poverty, malnutrition, low school attendance, and child labor in Brazil finally showed a substantial decline after the turn of this century, when antipoverty and social safety net programs were significantly expanded. We can conclude that higher national incomes greatly facilitate poverty reduction, while at the same time, poverty still needs to be addressed directly. ## Growth and Poverty Are the reduction of poverty and the acceleration of growth in conflict? Or are they complementary? Traditionally, a body of opinion held that more than rapid growth is required for the poor because they would be bypassed and marginalized by the structural changes of modern growth. Beyond this, there had been considerable concern in policy circles that the public expenditures required for reducing poverty would entail a reduction in the growth rate. The concern that concentrated efforts to lower poverty would slow the growth rate paralleled the arguments that countries with lower inequality would experience slower growth. If there was a redistribution of income or assets from rich to poor, even though progressive taxation, the concern was expressed that savings would fall. However, while the middle class generally has the highest savings rates, the marginal savings rates of the poor are not small when viewed holistically. In addition to financial savings, the poor tend to spend additional income on improved nutrition, education for their children, improvements in housing conditions, and other expenditures that, especially at poverty levels, represent investments rather than consumption. There are at least five reasons why policies focused on reducing poverty levels need not lead to a slower growth rate—and indeed could help to accelerate growth. First, widespread poverty creates conditions in which the poor have no access to credit, are unable to finance their children's education, and, in the absence of physical or monetary investment opportunities, have many children as a source of old-age financial security. Moreover, lack of credit denies impoverished people opportunities for entrepreneurship that could help spur growth. Together, these factors cause per capita growth to be less than it would be if there were less poverty. Second, a wealth of empirical data bears witness to the fact that, unlike the historical experience of the now-developed countries, the rich in many contemporary poor countries are generally not noted for their frugality or desire to save and invest substantial proportions of their incomes in the local economy. Third, the low incomes and low levels of living for the poor, manifested in poor health, nutrition, and education, can lower their economic productivity and lead directly and indirectly to a slower-growing economy. Strategies to raise the incomes and levels of living of the poor will, therefore, contribute not only to their material well-being but also to the productivity and income of the economy. Fourth, raising the income levels of the poor will stimulate an overall increase in the demand for locally produced necessities such as food and clothing. In contrast, the rich tend to spend more of their additional incomes on imported luxury goods. Rising demand for local goods provides a more significant stimulus to local production, local employment, and local investment. Such demand thus creates the conditions for rapid economic growth and a broader popular participation in that growth. Fifth, reducing mass poverty can stimulate healthy economic expansion by acting as a robust material and psychological incentive for widespread public participation in development. By contrast, vast income disparities and substantial absolute poverty can be robust material and psychological disincentives to economic progress. They may even create the conditions for the masses' ultimate rejection of progress, impatience at the pace of progress, or its failure to alter their material circumstances. We can conclude, therefore, that promoting rapid economic growth and reducing poverty are not mutually conflicting objectives. Case studies and cross-national data comparisons show that dramatic poverty reduction need not be incompatible with high growth. Countries where poverty has been reduced the most tend to have sustained growth; at the same time, growth does not guarantee poverty reduction. Richer countries strongly tend to have low levels of absolute poverty. Through one means or another—the availability of employment and entrepreneurship opportunities and greater public and NGO assistance-people living in rich countries tend to escape poverty. Among developing countries, there is evidence that countries with faster overall rates of per capita income growth also tend, on average, to have faster rates of per capita income growth among those in the bottom quintile of the income distribution, though the proportions vary widely. While we cannot passively count on even sustainable growth to end absolute poverty, ending poverty can be significantly facilitated through wise and shared stewardship of the various resources' growth provides. Indeed, the relationship between economic growth and progress among the poor does not by itself indicate causality. Some effects probably run from improved incomes, education, and health among the poor to faster overall growth. Moreover, as noted, poverty reduction is possible without rapid growth. However, whatever the causality, growth and poverty reduction are entirely compatible objectives. ## Policy Options on Income Inequality and Poverty: Some Basic Considerations Developing countries that aim to reduce poverty and excessive inequalities in their income distribution need to know how best to achieve their aim. What economic and other policies might governments in developing countries adopt to reduce poverty and inequality while maintaining or accelerating economic growth rates? As we are concerned with moderating the size distribution of incomes in general and raising the income levels of people living in poverty, it is essential to understand the various determinants of income distribution in an economy and see how government intervention can alter or modify their effect. This section's primary focus is the relationship between income inequality and poverty. We can identify four broad areas of possible government policy intervention, which correspond to the following four major elements in determining a developing economy's income distribution. 1