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Bayesian Inference and Model Comparison for Random Choice Structures

Author

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  • William J. McCausland
  • A.A.J. Marley

Abstract

We complete the development of a testing ground for axioms of discrete stochastic choice. Our contribution here is to develop new posterior simulation methods for Bayesian inference, suitable for a class of prior distributions introduced by McCausland and Marley (2013). These prior distributions are joint distributions over various choice distributions over choice sets of different sizes. Since choice distributions over different choice sets can be mutually dependent, previous methods relying on conjugate prior distributions do not apply. We demonstrate by analyzing data from a previously reported experiment and report evidence for and against various axioms.

Suggested Citation

  • William J. McCausland & A.A.J. Marley, 2013. "Bayesian Inference and Model Comparison for Random Choice Structures," Cahiers de recherche 07-2013, Centre interuniversitaire de recherche en ├ęconomie quantitative, CIREQ.
  • Handle: RePEc:mtl:montec:07-2013
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    References listed on IDEAS

    as
    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. Dagsvik, John K, 1994. "Discrete and Continuous Choice, Max-Stable Processes, and Independence from Irrelevant Attributes," Econometrica, Econometric Society, vol. 62(5), pages 1179-1205, September.
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    More about this item

    Keywords

    Random utility; discrete choice; Bayesian inference; MCMC;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles

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