Description:
The objective of this course is to teach M.A. and Ph.D. students to use macroeconomic concepts and techniques for their own research and incorporates a higher degree of formal analysis than in the introductory master’s lecture (IAMA).
Part I (Prof. Burda): Methods of modern macroeconomics for researchers in the field. Stationary Markov environments, state-space methods, stochastic difference equations. Dynamic programming and Lagrangian methods, complete markets, dynamic stochastic general equilibrium models, solution techniques. The Ramsey problem.
Part II (Prof. Weinke): The focus lies on dynamic stochastic general equilibrium (DSGE) models for positive and normative macroeconomic analysis. Throughout this part of the course, special emphasis will be put on the fact that theory can be used as a lens to analyze data. To this end a number of theoretical and empirical concepts are presented: the computation of impulse response functions, structural vector autoregressions, as well as an introduction to structural estimation. The course also develops the concept of Ramsey optimal policy and concludes with an introduction to DSGE models featuring heterogeneous agents.
Literature:
Reference list (Prof. Burda): Ljungqvist and Sargent, Recursive Macroeconomics, 4th edition (Cambridge, USA: 2018); selected journal articles available on moodle.
Reference list (Prof. Weinke): selected articles, e.g., Galí, Jordi (2018): “The State of New Keynesian Economics: A Partial Assessment,” Journal of Economic Perspectives, Vol. 32(3), 87-112.
Time & venue:
Lectures: Wednesdays, 08:30-12:00; DIW Berlin, Mohrenstraße 58, 10117 Berlin, Ostrom-Hall (only on October 16: rooms 3.3.002 A+B, third floor)
Exam:
One final exam administered at the end of the semester.
More information can be found on Moodle.
