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.
Advanced Macroeconomic Theory 2, Part 1
This course will introduce students to the rigorous solution, estimation, and analysis of business cycle models. Numerical solution methods will be compared in the analysis of the real business cycle (RBC) model and numerical estimation techniques introduced in the analysis of New Keynesian models. Thus, the course will have a twofold focus on models and techniques.
The course provides an introduction to Advanced Macroeconomics at the undergraduate level, serving as a bridge between Intermediate Macroeconomics at the undergraduate level and graduate-Macroeconomics.
The first part of course is about economic growth. The second part of the course is about business cycles.