Uncertainty and Disagreement in Equilibrium Models
研究了均衡概念中信念与模型真实概率一致的要求，发现检验信念与允许长期分歧之间存在矛盾，并讨论了在资产定价、马尔可夫完美均衡和动态博弈中的应用。
Leading equilibrium concepts require agents' beliefs to coincide with the model's true probabilities and thus be free of systematic errors. This implicitly assumes a criterion that tests beliefs against the observed outcomes generated by the model. We formalize this requirement in stationary environments. We show that there is a tension between requiring that beliefs can be tested against systematic errors and allowing agents to disagree or be uncertain about the long-run fundamentals. We discuss the application of our analysis to asset pricing, Markov perfect equilibria, and dynamic games.