Collaborative Research - Incomplete Information in Dynamic Economies: Analytics and Applications

自理性预期革命以来，求解动态宏观经济模型中的均衡依赖于施加限制，即模型动态是随机变量预期的函数。根据庇古（1929）的直觉--经济的结构特征加上不完全信息可能导致悲观主义和乐观主义的浪潮--不完全信息在早期宏观经济理性预期文献中发挥了重要作用[见卢卡斯（1972）和基德兰和普雷斯科特（1982）]。尽管有可能产生一组有趣的结果，但信息摩擦很快就从文献中消失了，主要是由于在解决不完整信息的动态模型时出现的技术挑战。PI的研究将回到早期文献的范式，并研究不完全信息如何影响均衡结果。1.智力的优点-拟议的研究的智力优点是充分说明和描述动态经济中的“信息均衡”。本研究将（1）建立资讯均衡的概念，提供不完全资讯动态模型的存在唯一性条件。初步结果表明，PI的平衡概念推翻了不存在的结果，一旦被认为是普遍的模型与非平凡的信息动态。(2)动态理性预期模型的信息均衡空间的解析刻画。所提出的方法克服了求解平衡的技术挑战，并通过在解析函数空间中求解模型来实现平衡的封闭形式表征。(3)刻画了赋予非对称信息的均衡中存在的一类信息均衡的动态性质。PI特征高阶的信念动力学在封闭的形式，并表现出重要的传播效果，由于不完全信息。(4)通过推导非基本移动平均表示和动态信号提取问题之间的等价性，提供移动平均表示的新信息解释。(5)研究不完全信息如何改变各种环境中的均衡动态。初步结果表明，不完全信息可以发挥至关重要的作用，在评估商业周期动态的来源，确定最佳的信息披露和稳定政策，调和资产定价理论与数据，并提高宏观DSGE模型的实证拟合;仅举几例应用。2.通过关注非常一般的设置中的动态不确定性，PI相信这些贡献可以在动态经济学的许多领域产生广泛的影响。虽然PI的研究主要集中在宏观和金融方面，但不完全信息及其解决方法可以应用得更广泛。拟议的研究将作出协调一致的努力，通过提供拟议的研究和现有的方法，更熟悉的专业概念之间的明确联系，明确所采用的技术的优势。

COLLABORATIVE RESEARCH INCOMPLETE INFORMATION IN DYNAMIC ECONOMIES:ANALYTICS AND APPLICATIONS Since the rational expectations revolution, solving for equilibria in dynamic macroeconomic models relies on imposing the restriction that model dynamics are a function of expectations of stochastic variables. Following the intuition of Pigou (1929) - that structural features of the economy coupled with incomplete information may lead to waves of pessimism and optimism -incomplete information played a prominent role in the early macroeconomic rational expectations literature [see Lucas (1972) and Kydland and Prescott (1982)]. Despite the potential for generating an interesting set of results, informational frictions soon disappeared from the literature, primarily due to the technical challenges that emerge when solving for dynamic models with incomplete information. The PI's research will return to paradigm of the early literature and examine how incomplete information affects equilibrium outcomes. 1. Intellectual Merit The intellectual merit of the proposed research is to fully specify and characterize "information equilibria" in dynamic economies. The proposed research will (1) Establish an information equilibrium concept that provides existence and uniqueness conditions for dynamic models with incomplete information. Preliminary results suggest that the PIs' equilibrium concept overturns non-existence results once thought to be pervasive in models with non-trivial informational dynamics. (2) Analytically characterize the space of information equilibria for dynamic rational expectations models. The proposed approach overcomes the technical challenges of solving for equilibrium and achieves a closed-form characterization of the equilibria by solving the model in the space of analytic functions. (3) Characterize the dynamic properties of the class of information equilibria for which endowed asymmetric information survives in equilibrium. The PIs characterize higher-order belief dynamics in closed form and demonstrate an important propagation effect due to incomplete information. (4) Provide a novel informational interpretation of moving average representations by deriving an equivalence between non-fundamental moving average representations and dynamic signal extraction problems. (5) Examine how incomplete information alters equilibrium dynamics in a variety of settings. Preliminary results suggest that incomplete information can play a vital role in assessing the sources of business cycle dynamics, determining optimal information disclosure and stabilization policies, reconciling asset pricing theory with data, and improving the empirical fit of macro DSGE models; to name a few applications. 2. Broader Impact By focusing on dynamic uncertainty in very general setups, the PI's believe the contributions can have a broad impact in many areas of dynamic economics. While the PIs research focuses on macro and finance, incomplete information and the solution techniques can be applied more broadly. The proposed research will make a concerted effort to make clear the advantages of the employed techniques by providing an explicit connection between the concepts of the proposed research and existing methodologies that are more familiar to the profession.