论文标题
游戏理论模型中反事实分析的分解方法
A Decomposition Approach to Counterfactual Analysis in Game-Theoretic Models
论文作者
论文摘要
分解方法通常用于在非战略设置中产生反事实预测。当兴趣的结果源于游戏理论环境中，通过在新政策之后偏离他们的策略，这种预测很难证明是合理的。我们介绍了贝叶斯游戏中的条件，基于分解的预测与基于平衡的预测一致。在许多游戏中，这种巧合遵循了平衡选择规则的不变条件。为了说明我们的信息，我们在Ciliberto和Tamer（2009）中对公司在航空行业的入境决策进行了经验分析。
Decomposition methods are often used for producing counterfactual predictions in non-strategic settings. When the outcome of interest arises from a game-theoretic setting where agents are better off by deviating from their strategies after a new policy, such predictions, despite their practical simplicity, are hard to justify. We present conditions in Bayesian games under which the decomposition-based predictions coincide with the equilibrium-based ones. In many games, such coincidence follows from an invariance condition for equilibrium selection rules. To illustrate our message, we revisit an empirical analysis in Ciliberto and Tamer (2009) on firms' entry decisions in the airline industry.
