Dynamic panels with predetermined regressors: likelihood-based estimation and Bayesian averaging with an application to cross-country growth
AbstractThis paper discusses likelihood-based estimation of linear panel data models with general predetermined variables and individual-specific effects. The resulting (pseudo) maximum likelihood estimator is asymptotically equivalent to standard GMM but tends to have smaller finite-sample biases as illustrated in simulation experiments. Moreover, the availability of such a likelihood function allows applying the Bayesian apparatus to this class of panel data models. Combining the aforementioned estimator with Bayesian model averaging methods we estimate empirical growth models simultaneously considering endogenous regressors and model uncertainty. Empirical results indicate that only the investment ratio seems to robustly cause long-run economic growth. Moreover, the estimated rate of convergence is not significantly different from zero.
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Bibliographic InfoPaper provided by Banco de Espa�a in its series Banco de Espa�a Working Papers with number 1109.
Length: 55 pages
Date of creation: May 2011
Date of revision:
dynamic panel estimation; maximum likelihood; weak instruments; growth regressions; bayesian model averaging;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- O40 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-06-04 (All new papers)
- NEP-ECM-2011-06-04 (Econometrics)
- NEP-FDG-2011-06-04 (Financial Development & Growth)
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