Estimation of Dynamic Discrete Choice Models in Continuous Time with an Application to Retail Competition

Peter Arcidiacono, Patrick Bayer, Jason R. Blevins, Paul B. Ellickson

NBER Working Paper No. 18449
Issued in October 2012
NBER Program(s):   IO   TWP

This paper provides a method for estimating and solving dynamic discrete choice models in a continuous time framework that is computationally light. The method is particularly useful in dynamic games. In the proposed framework, players face a standard dynamic discrete choice problem at decision times that occur stochastically. The resulting stochastic-sequential structure naturally admits the use of CCP methods for estimation and makes it possible to compute counterfactual simulations for relatively high-dimensional games. We apply our techniques to examine the impact of Walmart’s entry into the retail grocery industry, showing that even the threat of entry by Walmart has a substantial effect on market structure.

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This paper was revised on May 7, 2013

Acknowledgments

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