1. 1 Chapter 10 Growth, Poverty, and Income Distribution: Some Basic Facts © Pierre-Richard Agénor The World Bank

2. 2 l A Long-Run Perspective l Some Simple Arithmetic l Some Basic Facts

3. 3 Key Motivation in the Study of Economic Growth: l Observation that average annual growth rates vary substantially across countries. l Conventional neoclassical theory (attributing growth to technological progress) has proved incapable of explaining the wide disparities in per capita output growth rates across countries.

4. 4 A Long-Run Perspective

5. 5 l Highest per capita growth rates since 1820 concentrated in those countries that were already the most prosperous in the early nineteenth century (Maddison, 1995). l Overall pattern suggests convergence in income per capita levels over the very long run among most advanced industrial countries, but significant divergence between rich and poor countries over time. l From 1870 to 1990, the ratio of per capita incomes between the richest and poorest countries increased by a factor of five (Pritchett, 1997). Facts:

6. 6 l Large disparities in growth behavior within the developing world, both across countries and over time. l From 1973-92 average growth rates per annum: è -1.7% in Ethiopia and Peru. è 6.9% in South Korea.

7. 7 Some Simple Arithmetic

8. 8 l Growth and Standards of Living l How Fast Do Economies Catch Up?

9. 9 Growth and Standards of Living l Small differences in output growth between countries result in large differences in standards of livings over long periods. Consider the U.S. and India: è Income per capita in 1992: $21,558 in the U.S., $1,348 in India (measured in 1990 U.S. dollars); è Apply annual growth rate of 1.8% in the U.S. and 1.2% in India for the next two centuries (based on observed growth rates for 1913-92);

10. 10 è By 2100, per capita income will have reached $21,558  (1.018) 108 = $148,036 (U.S), $1,348  (1.012) 108 = $4,889 (India). è India’s income per person, as a percentage of U.S. income per person, will have fallen to 3.3% in 2100 from 6.3% in 1992. U.S. per capita income will have risen by a factor of 7 while India’s level will have risen by only a factor of 3.63..

11. 11 How Fast Do Economies Catch Up? l Question: Using the growth rates from the last example, how long will it take each country to double per capita income? è For India, doubling income in N years requires that y N = 2  1,348 = 1,348  (1.012) N so that, 2 = (1.012) N and, N = ln2/ln(1.012)  58.11.

12. 12 è For the U.S., the same calculation yields, N = ln2/ln(1.018)  38.5. Another question: l India's objective now is to attain a per capita income that is equal to 30% of the level of the United States by 2100. By how much should India grow per year? è Let y 0 US (y 0 IN ) denote per capita income in the United States (India) in the year 1992, and g US = 0.018 and g IN the average growth rate over the period 1913-92 for each country.

13. 13 è Since it takes 108 years to reach 2100 beginning in 1992, the value of g IN that is to be calculated is the solution of, 0.3  y 0 US (1.018) 108 = y 0 IN (1 + g IN ) 108. è Solving for g IN, the target growth rate of output must be about 3.3% per annum---almost three times the level observed during the period 1913- 92. è If India grows by a slightly lower number, 3.0% per annum, in the year 2100 its per capita income will be only about 22% of the U.S. level.

14. 14 Some Basic Facts

15. 15 l Output Growth, Factor Inputs, and Population l Saving, Investment, and Growth l Poverty and Growth l Inequality, Growth and Development l Trade, Inflation, and Financial Deepening

16. 16 Output growth, Factor Inputs and Population l Fact 1. Output per worker (or average labor productivity) tends to grow over time, albeit at widely different rates across countries. l Fact 2. The rate of growth of factor inputs (capital and labor) does not fully account for the rate of growth of output. l Fact 3. The mean growth rate of output is unrelated to the initial level of per capita income across countries (Figure 10.1).

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18. 18 l Fact 4. Population growth rates are negatively related with both the level of income per capita and the rate of growth of income per capita across countries (Figure 10.2).

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21. 21 Saving, Investment, and Growth l Fact 5. Saving rates are positively related to the level and the growth rate of income per capita (Figure 10.3). l Fact 6. Both the rate of growth of investment and the share of investment in output are positively related to the rate of growth of income per capita. See figure 10.4. l Figure 10.5 also displays the role of human capital accumulation in the growth process through two proxies: the gross enrollment ratio and the adult literacy rate.

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28. 28 Poverty and Growth Two indicators typically used to measure poverty: l poverty headcount index: measures the proportion of individuals or households earning less than a given absolute level of income; l poverty gap: average shortfall of the income of the poor with respect to the poverty line, multiplied by the headcount ratio.

29. 29 Ravallion and Chen (1997) used both types of indicators and arrived at the following results (Figure 10.6): l incidence of poverty in developing countries, measured by headcount index, fell between 1987 and 1993, from 31% to 29%; l depth of poverty (average distance below the poverty line), changed little; l rural poor are still poorer than urban poor; l differences across regions; poverty incidence fell in East Asia, South Asia and the MENA region and rose in Eastern and Central Europe, Latin America, and sub-Saharan Africa.

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31. 31 l Fact 7. Durable reductions in poverty rates require maintaining sustained rates of economic growth over time. See Figure 10.7. l Other factors important; Agénor (1999) suggested that inflation has a significant effect on the poor. l Figure 10.8. l Londoño and Székely have suggested that, at least in Latin America, poverty is strongly associated with a skewed distribution of income. l Other important variables are access to education, health services and employment opportunities, and the degree of urbanization.

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36. 36 Inequality, Growth, and Development l Three indicators of income inequality: è Share of the top to the bottom income deciles or quintiles--only attaches weight to the two tails of the income distribution. è Gini Coefficient. è Theil Inequality Index is decomposed into two terms: one that captures inequality due to differences between groups, and another that captures inequality within groups.

37. 37 Gini coefficient: l Derived from the Lorenz curve which displays cumulative share of total income received by cumulative shares of the population. l Measures the area between the Lorenz curve for a population and the line of perfect equality; it varies between 0 (maximum equality) and unity (maximum inequality). See Figure 10.9.

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39. 39 Evidence on Growth and Income Distribution l Data does not show clear pattern between the rate of growth of income per capita in developing countries and two measures of income inequality: the ratio of the share of the richest 20% to the share of the poorest 20%, and the Gini coeficient. See Figure 10.10.

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42. 42 Link between inequality, the pattern of growth, and development: l Kuznets hypothesis: income inequality increases in the early stages of development and then decreases. è Inverted-U shape reflects view that economic development involves a transition from a low- productivity, agrarian economy to a high- productivity, industrial economy. è Industrial incomes, distributed less equally than agricultural incomes, become more important during industrialization, leading to greater inequality.

43. 43 è Industry then takes over, average incomes rise, earnings differentials fall. è Growth is first unequalizing, then equalizing. l Early evidence broadly confirmed inverted-U patter with inequality lowest in low-income and high income countries and highest in middle-income countries. l Recent studies (Bruno, Ravallion, and Squire, 1998 and Fishlow, 1995) have failed to corroborate this result. l Fact 8: The link between income inequality and growth appears to be non-linear, but there remains some controversy about the nature and robustness of this relationship.

44. 44 Education Inequality and Income Distribution l Psacharopoulos et al. (1995) and Londoño and Székely (1997) suggest strong relationship between educational inequality and income inequality. l Lipton and Ravallion suggest that the relationship is nonlinear: è During first phases of growth in education, income inequality actually rises; for example, an increase from 1 to 2 years of education is typically associated with a 3 -point increase in the Gini coefficient.

45. 45 è Turning point arises when work force attains between 5 and 6 years of education. e.g. on passing from 6 to 7 years, Gini falls by.5 point, from 9 to 10 years, Gini falls by 2 points. Other Factors and Income Distribution l Cardoso et al. (1995) identified inflation and unemployment as determinants of income inequality in Brazil during the 1980s. l Relationship between inflation and income inequality as nonlinear (Bulir, 1998); inflation reduction from very high levels reduces income inequality while further reductions towards very low levels bring on negligible improvements.

46. 46 Trade, Inflation, Financial Deepening l Fact 9: export and import volume growth both positively related output growth. evidence on correlation between openness and growth less robust. l Figure 10.11. l Figure 10.12. l Fact 10: inflation-growth relationship; negative and nonlinear, è key for advocating macroeconomic stability; è nonlinear: reductions in inflation from a low (high) base have negligible (significant) impacts on growth. l Figure 10.13.

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51. 51 l Fact 11: financial system development is positively related to the rate of growth of output. l Figure 10.14.

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