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Bayes Estimation of Short-run Coefficients in Dynamic Panel Data Models

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Abstract

This study is concerned with estimating the mean of the coefficients in a dynamic panel data model when the coefficients are assumed to be randomly distributed across cross- sectional units. The authors suggest a Bayes approach to the estimation of such models using Markov chain Monte Carlo methods. They establish the asymptotic equivalence of the Bayes estimator and the mean group estimator proposed by Pesaran and Smith (1995), and show that the Bayes estimator is asymptotically normal for large N (the number of units) and large T (the number of time periods) so long as /N/T60 as both N> and T 64. The performance of the Bayes estimator for the short-run coefficients in dynamic panels is also compared against alternative estimators using both simulated and real data. The Monte Carlo results show that the Bayes estimator has better sampling properties than other estimators for both small and moderate T samples. The analysis of Tobin's q model yields new results.

Suggested Citation

  • Hsiao, C. & Pesaran, M. H. & Tahmiscioglu, A. K., 1998. "Bayes Estimation of Short-run Coefficients in Dynamic Panel Data Models," Cambridge Working Papers in Economics 9804, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:9804
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    Cited by:

    1. Pesaran, H.M., 2003. "Estimation and Inference in Large Heterogeneous Panels with Cross Section Dependence," Cambridge Working Papers in Economics 0305, Faculty of Economics, University of Cambridge.
    2. Giovanni Bella & Carla Massidda & Ivan Etzo, 2013. "A Panel Estimation of the Relationship between Income, Electric Power Consumption and CO2 Emissions," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 59(2), pages 149-166.
    3. Badi H. Baltagi & Georges Bresson & James M. Griffin & Alain Pirotte, 2003. "Homogeneous, heterogeneous or shrinkage estimators? Some empirical evidence from French regional gasoline consumption," Empirical Economics, Springer, vol. 28(4), pages 795-811, November.
    4. Canova, Fabio & Ciccarelli, Matteo, 2004. "Forecasting and turning point predictions in a Bayesian panel VAR model," Journal of Econometrics, Elsevier, vol. 120(2), pages 327-359, June.
    5. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    6. Martín-Mayoral, Fernando, 2008. "¿Existe convergencia entre los países de América Latina?
      [Exist convergence across Latinamerican countries]
      ," MPRA Paper 16039, University Library of Munich, Germany.
    7. Fabio Canova & Matteo Ciccarelli, 2009. "Estimating Multicountry Var Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 929-959, August.
    8. Herbert Brücker & Boriss Siliverstovs, 2006. "On the estimation and forecasting of international migration: how relevant is heterogeneity across countries?," Empirical Economics, Springer, vol. 31(3), pages 735-754, September.
    9. Richard Kneller & Norman Gemmell, 2002. "Fiscal Policy, Growth and Convergence in Europe," European Economy Group Working Papers 14, European Economy Group.
    10. Elena Cefis & Luigi Orsenigo & Matteo Ciccarelli, 2002. "From Gibrat'S Legacy To Gibrat'S Fallacy. A Bayesian Approach To Study The Growth Of Firms," Working Papers. Serie AD 2002-19, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    11. Andrew Hallett & Gert Peersman & Laura Piscitelli, 2004. "Investment Under Monetary Uncertainty: A Panel Data Investigation," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 31(2), pages 137-162, June.
    12. Fabio Canova & Matteo Ciccarelli, 2002. "Panel Index Var Models: Specification, Estimation, Testing And Leading Indicators," Working Papers. Serie AD 2002-21, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    13. repec:eee:juipol:v:45:y:2017:i:c:p:45-60 is not listed on IDEAS
    14. Cheng Hsiao & M. Hashem Pesaran, 2004. "Random Coefficient Panel Data Models," CESifo Working Paper Series 1233, CESifo Group Munich.
    15. Alessandro Rebucci, 2003. "On the Heterogeneity Bias of Pooled Estimators in Stationary VAR Specifications," IMF Working Papers 03/73, International Monetary Fund.
    16. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    17. International Monetary Fund, 1999. "Neglected Heterogeneity and Dynamics in Cross-Country Savings Regressions," IMF Working Papers 99/128, International Monetary Fund.
    18. Marek Jarocinski, 2010. "Responses to monetary policy shocks in the east and the west of Europe: a comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 833-868.
    19. Yongcheol Shin & Ron P Smith & Mohammad Hashem Pesaran, 1998. "Pooled Mean Group Estimation of Dynamic Heterogeneous Panels," ESE Discussion Papers 16, Edinburgh School of Economics, University of Edinburgh.
    20. Matteo Ciccarelli, 2001. "Testing Restrictions In Normal Data Models Using Gibbs Sampling," Working Papers. Serie AD 2001-17, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    21. Elena Cefis & Matteo Ciccarelli, 2005. "Profit differentials and innovation," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(1-2), pages 43-61.

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