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CRiSM Seminar - Roberto Leon-Gonzalez

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Location: A1.01

Roberto Leon-Gonzalez, National Graduate Institute for Policy Studies, Tokyo

Endogeneity and Panel Data in Growth Regressions: A Bayesian Model Averaging Approach

In the empirical growth literature different modeling choices have led to substantially different qualitative results. Even on the basis of similar datasets, such differences can arise because of different set of instruments, exogeneity restrictions or set of controlling regressors. In this paper we develop a Bayesian Model Averaging (BMA) technique to deal with the large number of modeling choices that typically arise in the empirical growth literature. In particular, we present a general framework that not only allows for cross-section regressions with instrumental variables, but also for the commonly used dynamic panel data model with endogenous or predetermined regressors. We apply our technique to the long and inconclusive literature on the effect of international aid on GDP growth. We do not find evidence to support that international aid has an impact on GDP,
or that this impact is positive when conditioning on good macroeconomic policies. Instead we find strong evidence that macroeconomic policies, such as controlled inflation, are important
for GDP growth in developing countries.

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