Recent Theory and Applications of DSGE Models

The lectures discussed recent advances in the literature on the econometric analysis of Dynamic Stochastic General Equilibrium (DSGE) models, covering both methods and applications. We began with an introduction to the Bayesian estimation of linearized as well as nonlinear DSGE models and reviewed algorithms to generate draws from the posterior distribution of DSGE model parameters. Once obtained these parameter were used with the DSGE models to provide quantitative answers to a variety of questions, e.g. about the sources of business cycle fluctuations, relative importance of endogenous propagation mechanisms, the effects of monetary and fiscal policy interventions. We presented tools to evaluate the fit of DSGE models, reviewed the forecasting performance of estimated DSGE models, and discussed novel methods of incorporating external information (about the current state of the economy and the long-run outlook) into DSGE model forecasts. Finally, we considered empirical models that relax some of the restrictions imposed by DSGE models. These specifications included VARs with priors derived from DSGE models, DSGE models that were embedded in state-space models, and mixtures of DSGE models.

Frank Schorfheide is Professor of Economics at the University of Pennsylvania.

These lectures are a joint event of the Econometric Institute, Tinbergen Institute and Princeton University Press, and are combined with an international workshop, intended for PhD students, fellows, and qualified external participants.