Person:
Kraay, Aart
Author Name Variants
Fields of Specialization
Macroeconomics,
Debt management,
Economic growth,
Inequality and shared prosperity
Degrees
Departments
Development Research Group, The World Bank
Externally Hosted Work
Contact Information
Last updated
January 31, 2023
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.
Publication Search Results
1 - 3 of 3
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Publication
The Worldwide Governance Indicators : Methodology and Analytical Issues
( 2010-09-01)This paper summarizes the methodology of the Worldwide Governance Indicators (WGI) project, and related analytical issues. The WGI cover over 200 countries and territories, measuring six dimensions of governance starting in 1996: Voice and Accountability, Political Stability and Absence of Violence/Terrorism, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption. The aggregate indicators are based on several hundred individual underlying variables, taken from a wide variety of existing data sources. The data reflect the views on governance of survey respondents and public, private, and NGO sector experts worldwide. The WGI also explicitly report margins of error accompanying each country estimate. These reflect the inherent difficulties in measuring governance using any kind of data. Even after taking these margins of error into account, the WGI permit meaningful cross-country and over-time comparisons. The aggregate indicators, together with the disaggregated underlying source data, are available at www.govindicators.org. -
Publication
Predicting Conflict
(World Bank, Washington, DC, 2017-05)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. -
Publication
Can Disaggregated Indicators Identify Governance Reform Priorities?
( 2010-03-01)Many highly-disaggregated cross-country indicators of institutional quality and the business environment have been developed in recent years. The promise of these indicators is that they can be used to identify specific reform priorities that policymakers and aid donors can target in their efforts to improve institutional and regulatory quality outcomes. Doing so however requires evidence on the partial effects of these many very detailed variables on outcomes of interest, for example, investor perceptions of corruption or the quality of the regulatory environment. In this paper we use Bayesian Model Averaging (BMA) to systematically document the partial correlations between disaggregated indicators and several closely-related outcome variables of interest using two leading datasets: the Global Integrity Index and the Doing Business indicators. We find major instability across outcomes and across levels of disaggregation in the set of indicators identified by BMA as important determinants of outcomes. Disaggregated indicators that are important determinants of one outcome are on average not important determinants of other very similar outcomes. And for a given outcome variable, indicators that are important at one level of disaggregation are on average not important at other levels of disaggregation. These findings illustrate the difficulties in using highly-disaggregated indicators to identify reform priorities.