Master
2022/2023
Dynamic Stochastic General Equilibrium Models
Category 'Best Course for Career Development'
Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Category 'Best Course for New Knowledge and Skills'
Type:
Elective course (Economics and Economic Policy)
Area of studies:
Economics
Delivered by:
Department of Theoretical Economics
Where:
Faculty of Economic Sciences
When:
2 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Arsenii Mishin
Master’s programme:
Economics and Economic policy
Language:
English
ECTS credits:
6
Contact hours:
40
Course Syllabus
Abstract
This course continues the sequence of macroeconomics courses for Master's students. It aims to deepen our understanding of modern tools used in the analysis of macroeconomic processes and policies. A challenge facing policymakers is how to evaluate the net effects of forces operating on different parts of the economy. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. DSGE models have also become the standard workhorse models for the analysis of aggregate fluctuations. The primary focus of this course will be on the analysis, solution, calibration, estimation, and extension of DSGE models. We will also emphasize computational methods and apply them to solve DSGE models.
Learning Objectives
- To deepen understanding of modern tools for the analysis of macroeconomic processes.
- To increase competitiveness of students in doing research where demand is rising for more rigorous work on studying macroeconomic processes.
- To learn and practice quantitative methods which are actively used in modern macro research.
Expected Learning Outcomes
- Critically evaluate the logic of DSGE modeling
- Apply computer programs to the work with DSGE models.
- Derive model's equations, compute the solution, perform model's calibration and estimation.
- Learn how to introduce different changes into the basic RBC model and evaluate their effects on the main results.
- Learn the theory and practice of parameter estimation in DSGE models using several examples and Dynare's estimation toolbox.
- Learn some basic tools and apply them to the work with non-linear models.
- Differentiate DSGE modeling with other approaches to macroeconomic modeling.
Course Contents
- Overview of DSGE Models
- Introduction to MATLAB and Dynare
- The Methodology of DSGE Analysis: RBC Example
- Extensions of the Basic RBC Model
- Estimation of DSGE Models
- Introduction to Non-linear Models
Interim Assessment
- 2022/2023 2nd module0.1 * Class Participation + 0.4 * Report + 0.3 * Home Assignments + 0.2 * Presentation
Bibliography
Recommended Core Bibliography
- Macroeconomic theory : a dynamic general equilibrium approach, Wickens, M., 2008
- Methods for applied macroeconomic research, Canova, F., 2007
- Structural macroeconometrics, DeJong, D. N., 2007
- The ABCs of RBCs : an introduction to dynamic macroeconomic models, McCandless, G., 2008
- Wickens, M. (2008). Macroeconomic Theory : A Dynamic General Equilibrium Approach. Princeton: Princeton University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=350058
Recommended Additional Bibliography
- Bayesian estimation of DSGE models, Herbst, E. P., 2016
- Kenneth L. Judd. (1998). Numerical Methods in Economics. The MIT Press.
- Ljungqvist, L., & Sargent, T. J. (2012). Recursive Macroeconomic Theory (Vol. 3rd ed). Cambridge, Mass: The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=550665
- Numerical methods in economics, Judd, K. L., 1998