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PhD level course on advanved macro models dealing with agent heterogeneity.
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Week 1-Intro to Python
Week 2-Numerical Methods
Week 3- Dynamic Programming
Week 4- Incomplete Markets Models
Week 5- Aggregate Uncertainty

Advanced Macro

The objective of the course is to go over the main workhorse models in macro, with an emphasis on models with heterogenous agents, and to show some leading applications of these models in recent literature. By the end of the course one should know the basic toolkits to solve and simulate macro models and should be able to apply/extend them for research purposes.

  1. Intro to python
  2. Recursive methods and representative agent model
  3. Models with (exogenously) incomplete markets: equilibrium determination of wealth inequality (the Aiyagary model)
  4. Models with aggregate uncertainty (the Krusell and Smith model)
  5. Heterogeneity and macroeconomic policy: implications of heterogeneity for the transmission and efficacy of monetary and fiscal policy.

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