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Bayesian Analysis of the Censored Regression Model with an AEPD Error Term

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  • Cheng Gao
  • Hiroki Tsurumi

Abstract

We present the censored regression model with the error term following the asymmetric exponential power distribution. We propose three Markov chain Monte Carlo (MCMC) algorithms: the first one uses the probability integral transformation; the second one uses a combination of the probability integral transformation and random walk draws; while the third one uses random walk draws. Using simulated data we compare the performance of the three MCMC algorithms. Then we compare the posterior means, or Bayes estimates, with maximum likelihood estimates. We estimate the stock option portion of executive compensation as an example of the empirical application.

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  • Cheng Gao & Hiroki Tsurumi, 2015. "Bayesian Analysis of the Censored Regression Model with an AEPD Error Term," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(5), pages 953-971, March.
    • Handle: RePEc:taf:lstaxx:v:44:y:2015:i:5:p:953-971
    DOI: 10.1080/03610926.2012.750358
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