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Bayesian Analysis of a Probit Panel Data Model with Unobserved Individual Heterogeneity and Autocorrelated Errors

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  • Martin Burda
  • Roman Liesenfeld
  • Jean-Francois Richard

Abstract

In this paper, we perform Bayesian analysis of a panel probit model with unobserved individual heterogeneity and serially correlated errors. We augment the data with latent variables and sample the unobserved heterogeneity component as one Gibbs block per individual using a flexible piecewise linear approximation to the marginal posterior density. The latent time effects are simulated as another Gibbs block. For this purpose we develop a new user-friendly form of the Efficient Importance Sampling proposal density for an Acceptance-Rejection Metropolis-Hastings step. We apply our method to the analysis of product innovation activity of a panel of German manufacturing firms in response to imports, foreign direct investment and other control variables. The dataset used here was analyzed under more restrictive assumptions by Bertschek and Lechner (1998) and Greene (2004). Although our results differ to a certain degree from these benchmark studies, we confirm the positive effect of imports and FDI on firms' innovation activity. Moreover, unobserved firm heterogeneity is shown to play a far more significant role in the application than the latent time effects.

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Bibliographic Info

Paper provided by University of Toronto, Department of Economics in its series Working Papers with number tecipa-321.

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Length: 23 pages
Date of creation: 16 Jun 2008
Date of revision:
Handle: RePEc:tor:tecipa:tecipa-321

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Related research

Keywords: Dynamic latent variables; Markov Chain Monte Carlo; importance sampling;

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  1. Franses, Ph.H.B.F., 2002. "On modeling panels of time series," Econometric Institute Research Papers EI 2002-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. Jean-Francois Richard & Roman Liesenfeld, 2007. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Working Papers, University of Pittsburgh, Department of Economics 322, University of Pittsburgh, Department of Economics, revised Jan 2004.
  3. Bertschek, Irene & Lechner, Michael, 1998. "Convenient estimators for the panel probit model," Journal of Econometrics, Elsevier, Elsevier, vol. 87(2), pages 329-371, September.
  4. Richard, Jean-Francois & Zhang, Wei, 2007. "Efficient high-dimensional importance sampling," Journal of Econometrics, Elsevier, Elsevier, vol. 141(2), pages 1385-1411, December.
  5. Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, SUNY-Oswego, Department of Economics, number emetr2, Spring.
  6. Dean R. Hyslop, 1999. "State Dependence, Serial Correlation and Heterogeneity in Intertemporal Labor Force Participation of Married Women," Econometrica, Econometric Society, Econometric Society, vol. 67(6), pages 1255-1294, November.
  7. Joachim Inkmann, 1999. "Misspecified heteroskedasticity in the panel probit model: A small sample comparison of GMM and SML estimators," Finance, EconWPA 9904003, EconWPA.
  8. Axel Borsch-Supan & Vassilis Hajivassiliou & Laurence J. Kotlikoff, 1992. "Health, Children, and Elderly Living Arrangements: A Multiperiod-Multinomial Probit Model with Unobserved Heterogeneity and Autocorrelated Errors," NBER Chapters, in: Topics in the Economics of Aging, pages 79-108 National Bureau of Economic Research, Inc.
  9. William Greene, 2004. "Convenient estimators for the panel probit model: Further results," Empirical Economics, Springer, Springer, vol. 29(1), pages 21-47, January.
  10. Richard Paap, 2002. "What are the advantages of MCMC based inference in latent variable models?," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, Netherlands Society for Statistics and Operations Research, vol. 56(1), pages 2-22.
  11. Bertschek, Irene, 1995. "Product and Process Innovation as a Response to Increasing Import and Foreign Direct Investment," Journal of Industrial Economics, Wiley Blackwell, Wiley Blackwell, vol. 43(4), pages 341-57, December.
  12. Elisabetta Falcetti & Merxe Tudela, 2006. "Modelling Currency Crises in Emerging Markets: A Dynamic Probit Model with Unobserved Heterogeneity and Autocorrelated Errors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(4), pages 445-471, 08.
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