Bayesian Macroeconometrics (BMAE)

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This course will introduce students to the foundations of Bayesian estimation in the context of macroeconomics. A rigorous treatment of the principles of Bayesian estimation and contrast with frequentist techniques will form the foundations to application to reduced-form and structural models of the macroeconomy. Topics such as linear regression, VAR, and DSGE models will be examined through the Bayesian perspective.

Textbooks: Introduction to Bayesian Econometrics 2nd Edition, Cambridge University Press, 2012 By Edward Greenberg

Bayesian Econometric Methods Cambridge University Press, 2007 By Gary Koop, Dale J. Poirier, and Justin L. Tobias

Bayesian Estimation of DSGE Models Princeton University Press, 2016 By Edward P. Herbst and Frank Schorfheide

Methods for Applied Macroeconomic Research Princeton University Press, 2007 By Fabio Canova

Course Outline

Part I: Bayesian Inference

  1. Introduction to Bayesian inference
  2. Linear regression
  3. Priors and likelihood

Part II: Bayesian VARs 4. Vector Autoregressions (VARs) 5. Bayesian Vectorautoregressions (BVARs) 6. Structural Vectorautoregressions (SVARs) 7. Further Topics (Potentially Sign-Restrictions, Regime-Switching, Stochastic Volatility, Time-Varying VARs)

Part III: Bayesian Analysis of DSGE Models 8. Dynamic Stochastic General Equilibrium (DSGE) 9. Bayesian Estimation of DSGEs 10. Bayesian Analysis of DSGEs

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Alexander Meyer-Gohde
Alexander Meyer-Gohde
Professor of Financial Markets and Macroeconomics

My research interests include macroeconomics, macro-finance, econometrics, and numerical methods