Inference of Signs of Interaction Effects in Simultaneous Games With Incomplete Information
提出一个易于实施的检验方法，用于推断不完全信息离散同时博弈中玩家行动对彼此收益的交互效应方向，无需参数设定，并应用于夫妻联合退休决策数据。
This paper studies the inference of interaction effects, i.e. the impacts of players' actions on each other's payoffs, in discrete simultaneous games with incomplete information. We propose an easily implementable test for the signs of state-dependent interaction effects which does not require parametric specifications of players' payoffs, the distributions of their private signals or the equilibrium selection mechanism. The test relies on the commonly invoked assumption that players' private signals are independent conditional on observed states. The procedure is valid in the presence of multiple equilibria and as a by-product we propose a formal test for multiple equilibria in the data-generating process. We provide Monte Carlo evidence of the test's good performance in finite samples. We also implement it to infer the direction of interaction effects in couples' joint retirement decisions using data from the Health and Retirement Study.