Centrální bankovnictví a finanční regulace - povinně specializační
CSF - elective
ET - povinně specializační
F,FT a B - povinně volitelný
Magisterský - vše
MEF - elective
Semestr - zimní
|Garanti:|| Mgr. Jakub Bechný
Mgr. Jan Žáček Ph.D.
There is no required literature. Lectures will be based on lecturers’ notes, presentations and handouts. Reference to relevant literature will be given when needed.
- DeJong, D. N., & Dave, C. (2011). Structural macroeconometrics. Princeton University Press, Edition 2.
- Galí, J. (2015). Monetary Policy, Inflation, and the Business Cycle: An Introduction to the New Keynesian Framework and Its Applications. Princeton University Press, Edition 2.
- McCandless, G. (2008). The ABCs of RBCs: An Introduction to Dynamic Macroeconomic Models. Harvard University Press.
- Pfeifer, J. (2018). A Guide to Specifying Observation Equations for the Estimation of DSGE Models. Unpublished manuscript, 1-81.
- Sheen, J., & Wang, B. Z. (2016). Assessing labor market frictions in a small open economy. Journal of Macroeconomics, 48, 231-251.
- Wickens, M. (2012). Macroeconomic theory: A Dynamic General Equilibrium Approach. Princeton University Press.
|Popis:||The course is intended for master students with interest in economic modelling. The course will introduce dynamic stochastic general equilibrium (DSGE) models as well as the essential tools needed for their construction and implementation.
The course employs a practical and very intensive approach to model building. Students will build DSGE models step-by-step: from households’ optimisation, through the firm’s problem to monetary authority. Students will acquire practical hands-on experience in building DSGE models which will allow them to develop and implement their versions of DSGE models using Matlab and Dynare toolbox.
The course is intended to be of a ‘workshop’ style. There is no clear division between lectures and seminars. Students will be introduced into the theoretical background of modelling and derivation of models’ building blocks. Students will also get an opportunity to implement acquired knowledge in Matlab-based practice sessions. Moreover, a guest lecture will demonstrate the practical implementation of DSGE models in policy analysis.
By the end of the course, students should acquire knowledge of and hands-on experience in DSGE modelling. More specifically, students should be able to:
- understand the basic structure of DSGE models;
- formulate and derive equations of standard DSGE models;
- approximate equilibrium conditions of DSGE models using the log-linearisation technique;
- understand solution techniques;
- calibrate, identify and diagnose DSGE models;
- implement DSGE models using Dynare toolbox;
- report and interpret results;
- perform sensitivity and robustness analyses;
- perform policy analyses;
- understand the zero lower bound.