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BAYESMIXEDLOGITWTP: Stata module for Bayesian estimation of mixed logit model in willingness-to-pay (WTP) space


  • Matthew Baker

    () (Hunter College)

Programming Language



bayesmixedlogitwtp "fits" mixed logit models using Bayesian methods in willingness-to-pay (WTP) space. bayesmixedlogitwtp functions in the same way as bayesmixedlogit; the command produces draws from the posterior parameter distribution and then presents summary and other statistics describing the results of the drawing. Detailed analysis of the draws is left to the discretion of the user. Implementation of bayesmixedlogitwtp follows the methods described in Train (2009, chap. 12), and mechanics described in Baker (2014).bayesmixedlogitwtp uses the Mata package amcmc() for adaptive Markov chain Monte Carlo sampling from the posterior distribution of individual level coefficients and fixed coefficients. The theory underlying the WTP model in willingness-to-pay space is described in Train and Weeks (2005), Scarpa, Thiene, and Train (2008), and Hole and Kolstad (2012).

Suggested Citation

  • Matthew Baker, 2015. "BAYESMIXEDLOGITWTP: Stata module for Bayesian estimation of mixed logit model in willingness-to-pay (WTP) space," Statistical Software Components S458044, Boston College Department of Economics, revised 19 Mar 2016.
  • Handle: RePEc:boc:bocode:s458044
    Note: This module should be installed from within Stata by typing "ssc install bayesmixedlogitwtp". The module is made available under terms of the GPL v3 ( Windows users should not attempt to download these files with a web browser.

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