Kraay, Aart

Person:
Kraay, Aart

Development Research Group, The World Bank

Fields of Specialization

Macroeconomics, Debt management, Economic growth, Inequality and shared prosperity

Departments

Development Research Group, The World Bank

Last updated: November 7, 2024

Biography

Aart Kraay is Director of Research in the Development Research Group at the World Bank. He joined the World Bank in 1995 after earning a Ph.D. in economics from Harvard University (1995), and a B.Sc. in economics from the University of Toronto (1990). His research interests include international capital movements, growth and inequality, governance, and the Chinese economy. His research on these topics has been published in scholarly journals such as the Quarterly Journal of Economics, the Review of Economics and Statistics, the Economic Journal, the Journal of Monetary Economics, the Journal of International Economics, and the Journal of the European Economic Association. He is an associate editor of the Journal of Development Economics, and co-editor of the World Bank Economic Review. He has also held visiting positions at the International Monetary Fund and the Sloan School of Management at MIT, and has taught at the School of Advanced International Studies at Johns Hopkins University.

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Publication Search Results

Now showing 1 - 8 of 8

The Worldwide Governance Indicators: Methodology and 2024 Update
(Washington, DC: World Bank, 2024-11-07) Kaufmann, Daniel; Kraay, Aart
This paper provides an overview of the data sources and aggregation methodology for the Worldwide Governance Indicators (WGI). The WGI report six aggregate governance indicators measuring Voice and Accountability, Political Stability and Absence of Violence/Terrorism, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption in a sample of 214 economies over the period 1996–2023. The aggregate indicators combine information from 35 different existing data sources, capturing subjective perceptions of the quality of various dimensions of governance reported by experts and survey respondents worldwide. The paper briefly discusses how to use reported margins of error when interpreting cross-country and over-time differences in the aggregate indicators. The paper also updates and extends earlier analysis on three key issues relating to the WGI methodology: (a) the effect of correlated perception errors, (b) the robustness of the aggregate indicators to alternative weighting schemes, and (c) the existence on trends in global averages of governance.
Growth Still Is Good for the Poor
(Elsevier, 2015-06-18) Dollar, David; Kleineberg, Tatjana; Kraay, Aart
Average incomes in the poorest two quintiles on average increase at the same rate as overall average incomes. This is because, in a global data set spanning 121 countries over the past four decades, changes in the share of income of the poorest quintiles are uncorrelated with changes in average income. The variation in changes in quintile shares is also small relative to the variation in growth in average incomes, implying that the latter accounts for most of the variation in income growth in the poorest quintiles. In addition, we find little evidence that changes in the bottom quintile shares are correlated with country-level factors that are typically considered as important determinants for growth in average incomes or for changes in inequality. This evidence confirms the central importance of economic growth for improvements in living standards at the low end of the income distribution. It also illustrates the difficulty of identifying specific macroeconomic policies that are significantly associated with the growth rates of those in the poorest quintiles relative to everyone else.
Predicting Food Crises
(World Bank, Washington, DC, 2020-09) Spencer, Phoebe; Kraay, Aart; Wang, Dieter; Andree, Bo, Pieter Johannes
Globally, more than 130 million people are estimated to be in food crisis. These humanitarian disasters are associated with severe impacts on livelihoods that can reverse years of development gains. The existing outlooks of crisis-affected populations rely on expert assessment of evidence and are limited in their temporal frequency and ability to look beyond several months. This paper presents a statistical forecasting approach to predict the outbreak of food crises with sufficient lead time for preventive action. Different use cases are explored related to possible alternative targeting policies and the levels at which finance is typically unlocked. The results indicate that, particularly at longer forecasting horizons, the statistical predictions compare favorably to expert-based outlooks. The paper concludes that statistical models demonstrate good ability to detect future outbreaks of food crises and that using statistical forecasting approaches may help increase lead time for action.
Toward Successful Development Policies: Insights from Research in Development Economics
(World Bank, Washington, DC, 2020-01) Artuc, Erhan; Cull, Robert; Dasgupta, Susmita; Fattal, Roberto; Filmer, Deon; Gine, Xavier; Jacoby, Hanan; Jolliffe, Dean; Kee, Hiau Looi; Klapper, Leora; Kraay, Aart; Loayza, Norman; Mckenzie, David; Ozler, Berk; Rao, Vijayendra; Rijkers, Bob; Schmukler, Sergio L.; Toman, Michael; Wagstaff, Adam; Woolcock, Michael
What major insights have emerged from development economics in the past decade, and how do they matter for the World Bank? This challenging question was recently posed by World Bank Group President David Malpass to the staff of the Development Research Group. This paper assembles a set of 13 short, nontechnical briefing notes prepared in response to this request, summarizing a selection of major insights in development economics in the past decade. The notes synthesize evidence from recent research on how policies should be designed, implemented, and evaluated, and provide illustrations of what works and what does not in selected policy areas.
Good Countries or Good Projects?: Comparing Macro and Micro Correlates of World Bank and Asian Development Bank Project Performance
(World Bank, Washington, DC, 2015-04) Bulman, David; Kolkma, Walter; Kraay, Aart
This paper examines the micro and macro correlates of aid project outcomes in a sample of 3,821 World Bank projects and 1,342 Asian Development Bank projects. Project outcomes vary much more within countries than between countries: country-level characteristics explain only 10–25 percent of project outcomes. Among macro variables, country growth and the policy environment are significantly positively correlated with project outcomes. Among micro variables, shorter project duration and the presence of additional financing are significantly correlated with better project outcomes. In addition, the track record of the project manager in delivering successful projects is highly significantly correlated with project outcomes. There are few significant differences between the two institutions in the relationship between these variables and project outcomes.
Predicting Conflict
(World Bank, Washington, DC, 2017-05) Celiku, Bledi; Kraay, Aart
This paper studies the performance of alternative prediction models for conflict. The analysis contrasts the performance of conventional approaches based on predicted probabilities generated by binary response regressions and random forests with two unconventional classification algorithms. The unconventional algorithms are calibrated specifically to minimize a prediction loss function penalizing Type 1 and Type 2 errors: (1) an algorithm that selects linear combinations of correlates of conflict to minimize the prediction loss function, and (2) an algorithm that chooses a set of thresholds for the same variables, together with the number of breaches of thresholds that constitute a prediction of conflict, that minimize the prediction loss function. The paper evaluates the predictive power of these approaches in a set of conflict and non-conflict episodes constructed from a large country-year panel of developing countries since 1977, and finds substantial differences in the in-sample and out-of-sample predictive performance of these alternative algorithms. The threshold classifier has the best overall predictive performance, and moreover has advantages in simplicity and transparency that make it well suited for policy-making purposes. The paper explores the implications of these findings for the World Bank's classification of fragile and conflict-affected states.
Weak Instruments in Growth Regressions: Implications for Recent Cross-Country Evidence on Inequality and Growth
(World Health Organization, 2015-11) Kraay, Aart
This paper revisits four recent cross-country empirical studies on the effects of inequality on growth. All four studies report strongly significant negative effects, using the popular system generalized method of moments estimator that is frequently used in cross-country growth empirics. This paper shows that the internal instruments relied on by this estimator in these inequality-and-growth regressions are weak, and that weak instrument-consistent confidence sets for the effect of inequality on growth include a wide range of positive and negative values. This suggests that strong conclusions about the effect of inequality on growth— in either direction—cannot be drawn from these studies. This paper also systematically explores a wide range of alternative sets of internal instruments, and finds that problems of weak instruments are pervasive across these alternatives. More generally, the paper illustrates the importance of documenting instrument strength, basing inferences on procedures that are robust to weak instruments, and considering alternative instrument sets when using the system generalized method of moments estimator for cross-country growth empirics.
Approximating Income Distribution Dynamics Using Aggregate Data
(World Bank, Washington, DC, 2017-06) Kraay, Aart; Van der Weide, Roy
This paper proposes a methodology to approximate individual income distribution dynamics using only time series data on aggregate moments of the income distribution. Under the assumption that individual incomes follow a lognormal autoregressive process, this paper shows that the evolution over time of the mean and standard deviation of log income across individuals provides sufficient information to place upper and lower bounds on the degree of mobility in the income distribution. The paper demonstrates that these bounds are reasonably informative, using the U.S. Panel Study of Income Dynamics where the panel structure of the data allows us to compare measures of mobility directly estimated from the micro data with approximations based only on aggregate data. Bounds on mobility are estimated for a large cross-section of countries, using data on aggregate moments of the income distribution available in the World Wealth and Income Database and the World Bank's PovcalNet database. The estimated bounds on mobility imply that conventional anonymous growth rates of the bottom 40 percent (top 10 percent) that do not account for mobility substantially understate (overstate) the expected growth performance of those initially in the bottom 40 percent (top 10 percent).