Identification and Estimation of Continuous Time Dynamic Discrete Choice Games

Jason R. Blevins.
The Ohio State University, Department of Economics
Working Paper.

2x2 Continuous Time Entry Model
2x2 Continuous Time Entry Model


Abstract. This paper considers the theoretical, computational, and econometric properties of a class of continuous time dynamic discrete choice games with stochastically sequential moves, introduced by Arcidiacono, Bayer, Blevins, and Ellickson (2016, Review of Economic Studies). In a generalized version of the model with heterogeneous move arrival rates, we first re-establish conditions for existence of a Markov perfect equilibrium. Then, we consider nonparametric identification of the model primitives with only discrete time data sampled at a fixed time interval. We consider identification not only of the payoff functions, as previous work has done, but also the move arrival rates. Three canonical models are considered: a single agent renewal model, a dynamic model of entry and exit, and a quality ladder model of oligopoly dynamics. These models are foundational for many applications in applied microeconomics. Through these examples we examine the computational properties of the model and statistical properties of estimators via a series of small- and large-scale Monte Carlo experiments. These experiments shed light on how the parameter estimates behave as one moves from continuous time data to discrete time data of decreasing frequency and on the computational feasibility of the model as the number of firms grows.

Keywords: Continuous time, Markov decision processes, dynamic discrete choice, dynamic games, identification.

JEL Classification: C13, C35, C62, C73.