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Limited dependent panel data models: a comparative analysis of classical and Bayesian inference among econometric packages


  • Giuseppe Bruno


Advances in computing power allow the empirical researcher to use intensive computional techniques to solve and estimate nonlinear panel-data models, specifically those arising from nonlinear panel data such as Probit and Tobit models. In these cases, maximum-likelihood estimation can be cumbersome if not analytically intractable, requiring a T-variate multiple integration whose numerical approximation can sometimes be very poor. Different solutions are offered based variously on integral approximation through simulation, some form of Generalized Method of Moments (GMM), or Markov Chain Monte Carlo (MCMC) methods. This paper compares the outcomes of those methods available in standard econometric packages, providing illustrations among prepackaged algorithms and a MCMC Gibbs sampler for nonlinear panel data. Using Chib (1992) and Chib and Carlin (1999), I derive a sampler for Probit/Tobit panel data and provide easy-to-use software for implementing the Gibbs sampler in panel data with discrete/limited dependent variable. I show that, when dealing with a large dataset, MCMC methods may replace the procedures provided in standard econometric packages

Suggested Citation

  • Giuseppe Bruno, 2004. "Limited dependent panel data models: a comparative analysis of classical and Bayesian inference among econometric packages," Computing in Economics and Finance 2004 41, Society for Computational Economics.
  • Handle: RePEc:sce:scecf4:41

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    Cited by:

    1. Li, Hao & Elbakidze, Levan, 2016. "Application of Regression Discontinuity Approach in Experimental Auctions: A Case Study of Gaining Participants’ Trust and Their Willingness to Pay," 2016 Annual Meeting, July 31-August 2, 2016, Boston, Massachusetts 236149, Agricultural and Applied Economics Association.
    2. Bouhlal, Yasser & Capps, Oral, Jr. & Ishdorj, Ariun, 2013. "Estimating the Censored Demand for U.S. Cheese Varieties Using Panel Data: Impact of Economic and Demographic Factors," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151298, Agricultural and Applied Economics Association.

    More about this item


    Gibbs sampler; Econometric software; Panel Tobit model; Random effects;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software


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