Four Projects about Macroeconomic Risk and Uncertainty: An Accomplishment Based Renewal

点击翻译按钮获取中文摘要

This project consists of four related lines of research. 1. Model drift and stochastic volatility: The project uses computationally intensive Bayesian methods to organize evidence about the sources of drift in vector autoregressions of post WWII U.S. aggregate time series. It seeks to partition drift into parts due to the systematic or autoregressive part, on the one hand, and the conditional variances of innovations, on the other. There are some influential studies in the literature that purport to affirm drift in the systematic part of vector autoregressions, and other equally influential ones that deny it in favor of drifting volatilities. Insights about continuous time diffusions lead the investigator to suspect that it is much more difficult to detect drift in the systematic part than in the volatilities. Partitioning drift into these two parts is important for quantitatively evaluating monetary and fiscal policy rules and their effects. The project interprets the evidence assembled in the light of recent theoretical formulations of drifting coefficient models that focus on the government's learning process. 2. Self-confirming equilibria and monetary policy: A self-confirming equilibrium is a form of rational expectations that permits agents' models to disagree on events that occur with zero probability in equilibrium. Recent theories of agents' learning deliver this form of rational expectations equilibrium as a limit point. This project extends earlier work with self-confirming equilibria to an empirically more ambitious one based on a version of a 'new synthesis' macro model. It also studies escape routes, a new form of dynamics, and the lessons that they carry for a possible threat to our current low-inflation regime. 3. Robust control and filtering in macroeconomics: This project pursues applications of dynamic models of robust filtering and control. The aim of this work is to provide positive and normative models of decision making where the decision-maker regards his model as an approximation. Robust decision theory provides a model of caution. Robust control theory is applied to asset pricing puzzles and the formulation of monetary and fiscal policies. 4. Macroeconomic history: This project studies in depth two or three important stabilizations of inflation and focuses on the conditions that contributed to high or low output and unemployment costs of stabilization.