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.
