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Panel Growth Regressions With General Predetermined Variables: Likelihood-Based Estimation And Bayesian Averaging

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  • Enrique Moral-Benito

    ()
    (CEMFI, Centro de Estudios Monetarios y Financieros)

Abstract

In this paper I estimate empirical growth models simultaneaously considering endogenous regressors and model uncertainty. In order to apply Bayesian methods such as Bayesian Model Averaging (BMA) to dynamic panel data models with predetermined or endogenous variables and fixed effects, I propose a likelihood function for such models. The resulting maximum likelihood estimator can be interpreted as the LIML counterpart of GMM estimators. Via Monte Carlo simulations, I conclude that the finite-sample performance of the proposed estimator is better than that of the commonly-used standard GMM. In contrast to the previous consensus in the empirical growth literature, empirical results indicate that once endogeneity and model uncertainty are accounted for, the estimated convergence rate is not significantly different from zero. Moreover, there seems to be only one variable, the investment ration, that causes long-run economic growth.

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Bibliographic Info

Paper provided by CEMFI in its series Working Papers with number wp2010_1006.

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Date of creation: Jul 2010
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Handle: RePEc:cmf:wpaper:wp2010_1006

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Related research

Keywords: Dynamic panel estimation; growth regressions; Bayesian Model Averaging; weak instruments; maximum likelihood.;

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  1. Kleibergen, F.R. & Zivot, E., 1998. "Bayesian and classical approaches to instrumental variable regression," Econometric Institute Research Papers EI 9835, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. Theo Eicher & Chris Papageogiou & Adrian E Raftery, 2007. "Default Priors and Predictive Performance in Bayesian Model Averaging, with Application to Growth Determinants," Working Papers UWEC-2007-25-P, University of Washington, Department of Economics.
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Cited by:
  1. Enrique Moral-Benito, 2011. "Model averaging in economics," Banco de Espa�a Working Papers 1123, Banco de Espa�a.

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