Working Paper: CEPR ID: DP10111
Authors: Taisuke Otsu; Martin Pesendorfer; Yuya Takahashi
Abstract: This paper proposes several statistical tests for finite state Markov games to examine the null hypothesis that the data are generated from a single equilibrium. We formulate tests of (i) the conditional choice and state transition probabilities, (ii) the steady-state distribution, and (iii) the conditional state distribution given an initial state. In a Monte Carlo study we find that the test based on the steady-state distribution performs well and has high power even with small numbers of markets and time periods. We apply the tests to the empirical study of Ryan (2012) that analyzes dynamics of the U.S. Portland Cement industry and assess if his assumption of single equilibrium is supported by the data.
Keywords: Dynamic Markov Game; Hypothesis Testing; Multiplicity of Equilibria
JEL Codes: C12; C72; D44
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Assumption of a single equilibrium (D50) | Empirical results derived from the data (C29) |
| Empirical analysis of data from Ryan (2012) (C59) | Rejection of the null hypothesis of a single equilibrium (D59) |
| Rejection of the null hypothesis of a single equilibrium (D59) | Presence of multiple equilibria in the dynamics of the U.S. Portland cement industry (D59) |
| Presence of multiple equilibria (D59) | Inconsistent estimates of policy functions (C51) |
| Inconsistent estimates of policy functions (C51) | Affects validity of conclusions drawn from prior analyses that assumed a single equilibrium (C62) |