Course Objectives:
Master advanced DSGE modeling techniques and applications.
Apply DSGE models to current economic research questions.
Contribute to academic research and policy-making using advanced DSGE models.
Target Audience:
Experienced academics, advanced PhD students, and professors specializing in macroeconomics.
Course Structure: Module 1: State-of-the-Art DSGE Modeling Techniques
Week 1: Nonlinear DSGE models and solution techniques.
Week 2: Incorporating heterogeneous agents and incomplete markets.
Module 2: Advanced Computational Methods
Week 3: High-dimensional models and computational challenges.
Week 4: Using advanced tools: MATLAB toolboxes, R, and Python.
Module 3: DSGE Models in Frontier Research
Week 5: DSGE models in climate economics and macro-finance.
Week 6: DSGE models for emerging market economies and developing countries.
Readings:
"Advanced Macroeconomics" by David Romer.
Selected cutting-edge research papers from top economic journals.
Assignments:
Weekly assignments on advanced model development and computational techniques.
A mid-term project involving the development of a novel DSGE model.
Final Project:
Conduct original research using advanced DSGE models, culminating in a research paper suitable for academic publication.