Syllabus
Registration via LPIS
Day | Date | Time | Room |
---|---|---|---|
Friday | 10/13/23 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 10/20/23 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 10/27/23 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 11/03/23 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 11/10/23 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 11/17/23 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 11/24/23 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 12/01/23 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 12/15/23 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 12/22/23 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 01/12/24 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 01/19/24 | 11:00 AM - 01:00 PM | D4.0.144 |
Friday | 01/26/24 | 11:00 AM - 01:00 PM | D4.0.144 |
Thursday | 02/01/24 | 11:30 AM - 01:00 PM | TC.0.01 |
The course offers an introduction into dynamic macroeconomics. Topics covered include an overview of empirical stylized facts of the macroeconomics of the long run (growth) and the short-run (business cycles). We discuss the empirical measurement and characterization of business cycles. The course gives an introduction into dynamic macro modelling in continuous and discrete time. A particular focus will lie on learning and using the macroeconomic methods with which one can solve, simulate and analyze macroeconomic methods.
Upon completion of the course, students will have acquired familiarity with the follow topics:
- Intro, Stylized facts in macroeconomics in the long-run (growth, Kaldor stylized facts) and short-run (business cycle stylized facts, trend-cycle decompositions): 1-2 lectures
- Dynamic optimization in discrete and continuous time (Dynamic Lagrangian, Hamiltonian), based on the stochastic growth model as the example model: ~ 2 lectures
- Introduction to Matlab/ Dynare (with the stochastic growth model as the example model) and interpreting the model solution output (impulse responses and model simulation) ~ 2 lectures
- Behind the scene: Linearization and Log-linearization ~ 1 lecture
- Behind the scene: Obtaining the solution of linear dynamic systems (Undetermined coefficients, eigenvalue decompositions, graphically: Phase diagram); using the solution (policy functions) to compute IR and model simulation ~ 2 lectures
- Crash course in Bayesian estimation ~ 1 lecture
- maybe a look into other simple macro models: consumption-savings model, the RBC model
The course is mainly lecture-based. Homework assignment and exercises (in groups) will be used to deepen the understanding of the materials discussed.
Grading is based on:
· Over the course, 2 assignments in groups, 22.5 points each (45 points in total)
· Active course participation (5 points)
· Final exam (50 points), you need to score at least 50% of the points
Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.
1. Solid knowledge and routine handling of intermediate macroeconomics at the level of basic text books (keywords: IS-LM model and its extension to a model with aggregate supply and aggregate demand; bibliographical reference e.g. Blanchard: Macroeconomics, 7th edition, Pearson, chapters 1-9)
2. Routine handling of basic microeconomic concepts (keywords: household optimum and the derivation of consumption demand and labour supply derivation; properties of Cobb-Douglas utility or production functions, monopoly price formation)
flexible; arrange a meeting on short notice via email katrin.rabitsch@wu.ac.at
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