This 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 course begins with economic growth and then proceeds to business cycles. Knowledge of functions, derivatives, and constrained optimization, along with basic statistics is assumed.
This course introduces students to the dynamic stochastic general equilibrium (DSGE) models used in modern monetary macroeconomics called New Keynesian models. The basic model equations including nominal frictions such as price stickiness are derived carefully, and model solution techniques are discussed. Numerical solutions of the models are obtained and the models are simulated and analyzed using Dynare in MATLAB. Possible extensions to the core model that may be treated in class include an analysis of optimal monetary policy.
After completing the course, students should understand the dynamic mechanisms of nominal rigidities and the policy tradeoffs facing monetary policy. Mechanically, students will be able to derive, solve and simulate simple DSGE models and should be able to read and understand more elaborate models found in the literature.
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.
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.