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Robust Dynamic Panel Data Models Usingε-Contamination

In: Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology

Author

Listed:
  • Badi H. Baltagi
  • Georges Bresson
  • Anoop Chaturvedi
  • Guy Lacroix

Abstract

This chapter extends the work of Baltagi, Bresson, Chaturvedi, and Lacroix (2018) to the popular dynamic panel data model. The authors investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach departs from the standard Bayesian framework in two ways. First, the authors consider theε-contamination class of prior distributions for the model parameters as well as for the individual effects. Second, both the base elicited priors and theε-contamination priors use Zellner’s (1986)g-priors for the variance–covariance matrices. The authors propose a general “toolbox” for a wide range of specifications which includes the dynamic panel model with random effects, with cross-correlated effectsà laChamberlain, for the Hausman–Taylor world and for dynamic panel data models with homogeneous/heterogeneous slopes and cross-sectional dependence. Using a Monte Carlo simulation study, the authors compare the finite sample properties of the proposed estimator to those of standard classical estimators. The chapter contributes to the dynamic panel data literature by proposing a general robust Bayesian framework which encompasses the conventional frequentist specifications and their associated estimation methods as special cases.

Suggested Citation

  • Badi H. Baltagi & Georges Bresson & Anoop Chaturvedi & Guy Lacroix, 2022. "Robust Dynamic Panel Data Models Usingε-Contamination," Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Panel Modeling, Micro Applications, and Econometric Methodology, volume 43, pages 307-336, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-90532021000043b013
    DOI: 10.1108/S0731-90532021000043B013

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    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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