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http://hdl.handle.net/2445/122433
Title: | Endogeneity and Panel Data in Growth Regressions: A Bayesian Model Averaging Approach |
Author: | León-González, Roberto Montolio, Daniel |
Keywords: | Estadística bayesiana Anàlisi de dades de panel Anàlisi de regressió Mètode de Montecarlo Processos de Markov Bayesian statistical decision Panel analysis Regression analysis Monte Carlo method Markov processes |
Issue Date: | Dec-2015 |
Publisher: | Elsevier |
Abstract: | Bayesian model averaging (BMA) has been successfully applied in the empirical growth literature as a way to overcome the sensitivity of results to different model specifications. In this paper, we develop a BMA technique to analyze panel data models with fixed effects that differ in the set of instruments, exogeneity restrictions, or the set of explanatory variables in the regression. The large model space that typically arises can be effectively analyzed using a Markov Chain Monte Carlo algorithm. We apply our technique to investigate the effect of foreign aid on per capita GDP growth. We show that BMA is an effective tool for the analysis of panel data growth regressions in cases where the number of models is large and results are sensitive to model assumptions. |
Note: | Versió postprint del document publicat a: https://doi.org/10.1016/j.jmacro.2015.07.003 |
It is part of: | Journal of Macroeconomics, 2015, vol. 46, num. December, p. 23-39 |
URI: | http://hdl.handle.net/2445/122433 |
Related resource: | https://doi.org/10.1016/j.jmacro.2015.07.003 |
ISSN: | 0164-0704 |
Appears in Collections: | Articles publicats en revistes (Economia) |
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