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