Course Objectives:
Develop more complex DSGE models incorporating various economic sectors.
Learn estimation techniques and calibration methods.
Analyze policy implications using DSGE models.
Target Audience:
Academics, PhD students, and professors with a basic understanding of DSGE models.
Course Structure: Module 1: Advanced DSGE Model Structures
Week 1: Incorporating capital and investment.
Week 2: Introducing government sector and fiscal policy.
Module 2: Estimation and Calibration
Week 3: Calibration techniques: parameter selection and data fitting.
Week 4: Estimation methods: Bayesian estimation and Maximum Likelihood.
Module 3: Policy Analysis and Shocks
Week 5: Analyzing monetary policy: Taylor rules and interest rate dynamics.
Week 6: Understanding and modeling different types of shocks (technology, policy, preference).
Readings:
"Dynamic Economic Analysis: Deterministic Models in Discrete Time" by Gerhard Sorger.
Selected articles from the Journal of Economic Dynamics and Control.
Assignments:
Weekly assignments on model expansion and policy analysis.
A mid-term project on estimating a DSGE model using real data.
Final Project:
Develop a medium-scale DSGE model and perform policy analysis using Bayesian estimation.