IDEAS home Printed from
   My bibliography  Save this paper

A Simulation Estimator for Dynamic Models of Discrete Choice


  • V. Joseph Hotz
  • Robert A. Miller
  • Seth Sanders
  • Jeffrey Smith


This paper extends the recent work of Hotz and Miller (1991) on the use of conditional choice probabilities to represent the valuation functions in the estimation of dynamic, discrete choice models. They derive a N1/2 consistent and asymptotically normal estimator of the structural parameters of agents' optimal decision rules that relies on nonparametric estimates of the conditional choice probabilities of future choices. This paper extends their work by deriving a related estimator that does not require the estimation of the conditional choice probabilities of all future paths associated with a current action, but rather only those associated with a simulated path or paths. This estimator is also shown to be N1/2 consistent and asymptotically normal. The derivation of our estimator's asymptotic properties makes use of recent results in Pakes and Pollard (1989). By reducing the number of conditional choice probabilities that must be estimated, this new estimator allows the consideration of models with large numbers of alternative choices. We report results from a Monte Carlo study comparing several versions of our estimator with the maximum likelihood estimator in the context of Rust's (1989) model of bus engine replacement. We also discuss the implications of the Monte Carlo evidence regarding the actual implementation of the estimator.

Suggested Citation

  • V. Joseph Hotz & Robert A. Miller & Seth Sanders & Jeffrey Smith, 1992. "A Simulation Estimator for Dynamic Models of Discrete Choice," Working Papers 9205, Harris School of Public Policy Studies, University of Chicago.
  • Handle: RePEc:har:wpaper:9205

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:har:wpaper:9205. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Eleanor Cartelli). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.