William Easterly

Africa's Growth Tragedy: Policies and Ethnic Divisions

Explaining cross-country differences in growth rates requires not only an understanding of the link between growth and public policies, but also an understanding of why countries choose different public policies. This paper shows that ethnic diversity helps explain cross-country differences in public policies and other economic indicators. In the case of Sub-Saharan Africa, economic growth is associated with low schooling, political instability, underdeveloped financial systems, distorted foreign exchange markets, high government deficits, and insufficient infrastructure. Africas high ethnic fragmentation explains a significant part of most of these characteristics.

Fiscal Policy and Economic Growth: An Empirical Investigation

Abstract This paper describes the empirical regularities relating fiscal policy variables, the level of development, and the rate of growth. We employ historical data, recent cross-section data and newly constructed public investment series. Our main findings are: (i) there is a strong association between the development level and the fiscal structure: poor countries rely heavily on international trade taxes, while income taxes are only important in developed economies; (ii) fiscal policy is influenced by the scale of the economy, measured by its population; (iii) investment in transport and communication is consistently correlated with growth; (iv) the effects of taxation are difficult to isolate empirically.

The Middle Class Consensus and Economic Development

A middle class consensus is defined as a high share of income for the middle class and a low degree of ethnic divisons. The paper links a middle class consensus to resource endowments, along the lines of the provocative thesis of Engerman and Sokoloff (1997 and 2000). This paper exploits this association using tropical resource endowments as instruments for inequality. A higher share of income for the middle class and lower ethnic divisions are associated with higher income and higher growth, as well as with more education, better health, better infrastructure, better economic policies, less political instability, less civil war and ethnic minorities at risk, more social “modernization” and more democracy.

Aid, Policies, and Growth: Comment

In an extraordinarily influential paper, Craig Burnside and David Dollar (2000, p. 847) find that “... aid has a positive impact on growth in developing countries with good fiscal, monetary, and trade policies but has little effect in the presence of poor policies.” This finding has enormous policy implications. The Burnside and Dollar (2000, henceforth BD) result provides a role and strategy for foreign aid. If aid stimulates growth only in countries with good policies, this suggests that (1) aid can promote economic growth, and (2) it is crucial that foreign aid be distributed selectively to countries that have adopted sound policies. International aid agencies, public policy makers, and the press quickly recognized the importance of the BD findings. This paper reassesses the links between aid, policy, and growth using more data. The BD data end in 1993. We reconstruct the BD database from original sources and thus (1) add additional countries and observations to the BD data set because new information has become available since they conducted their analyses, and (2) extend the data through 1997. Thus, using the BD methodology, we reexamine whether aid influences growth in the presence of good policies. Given our focus on retesting BD, we do not summarize the vast pre-BD literature on aid and growth. We just note that there was a long and inconclusive literature that was hampered by limited data availability, debates about the mechanisms through which aid would affect growth, and disagreements over econometric specification (see Gustav F. Papanek, 1972; Robert Cassen, 1986; Paul Mosley et al., 1987; Peter Boone, 1994, 1996; and Henrik Hansen and Finn Tarp’s 2000 review). Since BD found that aid boosts growth in good policy environments, there have been a number of other papers reacting to their results, including Paul Collier and Jan Dehn (2001), CarlJohan Dalgaard and Hansen (2001), Patrick Guillaumont and Lisa Chauvet (2001), Hansen and Tarp (2001), Robert Lensink and Howard White (2001), and Collier and Dollar (2002). These papers conduct useful variations and extensions (some of which had already figured in the pre-BD literature), such as introducing additional control variables, using nonlinear specifications, etc. Some of these papers confirm the message that aid only works in a good policy environment, while others drive out the aid policy interaction term with other variables. This literature has the usual limitations of choosing a specification without clear guidance from theory, which often means there are more plausible specifications than there are data points in the sample. We differentiate our paper from these others by NOT deviating from the BD specification. Thus, we do not test the robustness of the results to an unlimited number of variations, but instead maintain the BD methodology. This paper conducts a very simple robustness check by adding new data that were unavailable to BD. Thus, we expand the sample used over their time period and extend the data from 1993 to 1997. * Easterly: Department of Economics, New York University, 269 Mercer Street, New York, NY 10003, Center for Global Development, and National Bureau of Economic Research (e-mail: william.easterly@nyu.edu); Levine: Department of Finance, Carlson School of Management, University of Minnesota, 321 19th Avenue South, Minneapolis, MN 55455, and National Bureau of Economic Research (e-mail: rlevine@csom.umn.edu); Roodman: Center for Global Development, 1776 Massachusetts Avenue NW, Washington, DC 20036 (e-mail: droodman@cgdev.org). We are grateful to Craig Burnside for supplying data and assisting in the reconstruction of previous results, without holding him responsible in any way for the work in this paper. Thanks also to Francis Ng and Prarthna Dayal for generous assistance with updating the Sachs-Warner openness variable, and to three anonymous referees, Craig Burnside, and Henrik Hansen for helpful comments. 1 See, for instance, the World Bank (1994, 2001, 2002), the U.K. Department for International Development (2000), President George W. Bush’s speech (March 16, 2002), the announcement by the White House on creating the Millennium Challenge Corporation (White House, 2002), as well as a Washington Post editorial (February 9, 2002), a Financial Times column by Alan Beattie (March 11, 2002), and The Economist (March 16, 2002).

Good policy or good luck

Abstract Much of the new growth literature stresses country characteristics, such as education levels or political stability, as the dominant determinant of growth. However, growth rates are highly unstable over time, with a correlation across decades of 0.1 to 0.3, while country characteristics are stable, with cross-decade correlations of 0.6 to 0.9. Shocks, especially those to terms of trade, play a large role in explaining variance in growth. These findings suggest either that shocks are important relative to country characteristics in determining long-run growth, or that worldwide technological change determines long-run growth while country characteristics determine relative income levels.

Inflation and the poor

Using polling data for 31,869 households in 38 countries, and allowing for country effects, the authors show that the poor are more likely than the rich to mention inflation as a top national concern. This result survives several robustness checks. Also, direct measures of improvements in well-being for the poor - the change in their share of national income, the percentage decline in poverty, and the percentage change in the real minimum wage - are negatively correlated with inflation in pooled cross-country samples. High inflation tends to lower the share of the bottom quintile and the real minimum wage - and tends to increase poverty.

Social Cohesion, Institutions, and Growth

We present evidence that measures of “social cohesion,” such as income inequality and ethnic fractionalization, endogenously determine institutional quality, which in turn casually determines growth.

Life During Growth

A remarkable diversity of indicators shows quality of life across nations to be positively associated with per capita income. At the same time, the changes in quality of life as income grows are surprisingly uneven. Either in levels or changes, moreover, the effect of exogenous shifts over time is surprisingly strong compared to growth effects. This article reaches this conclusion with a panel dataset of 81 indicators covering up to four time periods (1960, 1970, 1980, and 1990). The indicators cover seven subjects: (1) individual rights and democracy, (2) political instability and war, (3) education, (4) health, (5) transport and communications, (6) inequality across class and gender, and (7) “bads.” With a SUR estimator in levels, income per capita has an impact on the quality of life that is significant, positive, and more important than exogenous shifts for 32 out of 81 indicators. With a fixed-effects estimator, growth has an impact on the quality of life that is significant, positive, and more important than exogenous shifts for 10 out of 81 indicators. With a first-differences IV estimator, growth has a causal impact on the quality of life that is significant, positive, and more important than exogenous shifts for six out of 69 quality of life indicators. The conclusion speculates about such explanations for the pattern of results as (1) the long and variable lags that may come between growth and changes in the quality of life and (2) the possibility that global socioeconomic progress is more important that home-country growth for many quality-of-life indicators.

Where Does the Money Go? Best and Worst Practices in Foreign Aid

Foreign aid from official sources to developing countries (excluding private aid) amounted to

Has Latin America's post-reform growth been disappointing?

103.6 billion in 2006 and has amounted to over