This project develops and applies tools for estimation, forecasting, and policy analysis in dynamic stochastic general equilibrium macroeconomic models. These methods are fully structural and fully Bayesian, shrinking vector autoregressions in the direction of the prior mean. These methods are unique in that although the model is estimated over all frequencies, the shrinkage occurs only at frequencies selected by the user, such as business cycle frequencies. Although superficially resembling the band-spectral methods of several decades ago, they are fundamentally different and facilitate a tight integration of macroeconomics and econometrics in estimation, forecasting, and policy analysis - using the same model, and acknowledging misspecification, throughout.
The intellectual merit of the work is high, as the problems addressed - acknowledging misspecification while finding a workable middle ground between the unappealing extremes of pure calibration and classical maximum-likelihood estimation - have eluded solution for decades and are widely acknowledged to be both highly challenging and crucially important for compelling empirical application of modern macroeconomic models.
The broader impacts of the project are substantial and several-fold. First, it will contribute directly to teaching and learning via mentoring and collaborating with graduate students. Second, it will reach out to underrepresented groups via broad web-based dissemination of all research results. Third, it will enhance infrastructure for research and education by establishing a variety of collaborations: between disciplines (by deepening our understanding of the econometrics / macroeconomics interface), between researchers and nations (by utilizing national and international coauthorships and joint projects), and between academia and other communities including government and policy organizations (by facilitating and accelerating knowledge transfer from academia). This knowledge transfer is crucially important, because the problems on which the proposed research focuses are precisely those that have hindered widespread application of modern macroeconomic models in government and policy organizations. Hence if the intellectual merit of the research is high, its value is nevertheless much greater than that associated purely with its intellectual merit. Indeed, the research will significantly push modern macroeconomic modeling, forecasting, and policy analysis toward routine application, producing improved policy, and ultimately improved general performance of the macroeconomy.
