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Patricia Prüfer

Date of Ph.D. defense: 31 October 2008
Title of thesis: Model Uncertainty in Growth Empirics
ISBN: 978 90 5668 220 0
Promotores: Prof.dr. J.R. Magnus and Prof.dr. J. Boone

Abstract:
Understanding the nature of economic growth, that is why some countries are rich while others stay poor, is one of the oldest and most important research agendas in economics. However, empirical research on the determinants of economic growth lacks theoretical guidance because growth theories are not mutually exclusive, a problem which is commonly referred to as 'open-endedness'. This implies model uncertainty as there does not exist a clearly defined model specification, but a wide set of possible models. One treatment of model uncertainty is model averaging, where the results are derived as a weighted average over all potential models with weights given by the trust one has in each model, based on prior beliefs and data.

This thesis applies so-called Bayesian model averaging (BMA) to three different economic questions substantially exposed to model uncertainty. Chapter 2 addresses a major issue of modern development economics: the analysis of the determinants of pro-poor growth (PPG), which seeks to combine high growth rates with poverty reduction. Vietnam is an interesting example for such an analysis because this country is a showcase for effective policies of PPG. However, it is not clear which factors have contributed to which extent to Vietnam's PPG. Chapter 3 analyzes whether foreign direct investment (FDI) has been beneficial for productivity growth in Latin America (LA). FDI has surged in LA since the mid 1990s. BMA allows accounting for the major shifts in the regional composition of these inflows, for the varying types of and motives for FDI, and for differing local conditions within LA. Finally, Chapter 4 goes a step further and investigates not only the robustness of different types of growth determinants. It also introduces Weighted-Average Least Squares (WALS) as a new model averaging technique, which is theoretically and practically superior to BMA. By comparing the estimation results of WALS and BMA and conducting various robustness checks, we analyze the importance of various 'fundamental' growth determinants such as geography, institutions, fractionalization and culture or religion.

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