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.
Part II (Prof. Weinke): Dynamic stochastic general equilibrium (DSGE) models for positive and normative macroeconomic analysis. 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. On the normative side the concept of Ramsey optimal policy is presented.
Reference list (Prof. Burda): Ljungqvist and Sargent, Recursive Macroeconomics, 3nd edition (Cambridge, USA: 2012); selected journal articles available on moodle.
Reference list (Prof. Weinke): Selected articles, e.g., Galí, Jordi and Pau Rabanal (2004), Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Postwar U.S. Data?, in: NBER Macroeconomics Annual.
Any further documents needed for the lecture will be available on moodle.
StO/PO MA 2016: 6 LP, Modul: "Advanced Macroeconomic Analysis I (PhD-level)"
Die Veranstaltung wurde 6 mal im Vorlesungsverzeichnis WiSe 2020/21 gefunden: