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README.md

Material for TA sessions at Bocconi University

Structure of TA sessions

This is a tentative schedule: even though most of the material is ready and present in this folder, unexpected things might come up. However, this is what I will try to cover in each of the 6 meetings:

  1. Introduction to Numerical Methods in Macroeconomics and introduction to Python
    • Perturbation methods
    • Projection methods
    • Numpy
    • Scipy
    • Matplotlib
  2. Global solution methods under no uncertainty (example: household's problem in the neoclassical growth model)
    • Value Function iteration (VFI)
    • Policy Function iteration (PFI)
    • Time iteration (TI)
  3. Global solution methods under uncertainty (example: household's problem in the stochastic neoclassical growth model)
    • Markov chains as discretized AR(1) processes
    • VFI, PFI and TI under stochastic environments
    • Simulation
    • Endogenous grid methods (if time allows)
  4. Bewley-like models: idiosyncratic shocks to endowments in a simple exchange economy
  5. Bewley-like models: idiosyncratic shocks to labor income in a RBC model
  6. Advanced tools
    • Binning (theory in class, here only code)
    • Transition dynamics (aka, MIT shocks; theory in class, here only code)
    • Krusell and Smith (1998): overview of code and highlight of main steps (if time allows)
    • Reiter's (2009) method: solving models with idiosyncratic and aggregate shocks (if time allows)

For each session, there is a Jupyter notebook. I might use extra material in class (e.g., slides) but they will have no additional content relative to the notebooks, so I will not post them here.

Extra topics: web scraping, machine learning and natural language processing

Economists are learning their way through programming, and some used Python to scrape the web, run machine learning algorithms or parse natural language. These practices are becoming popular, so they deserve a bit of our attention.

While I will not have time to cover them, I want to showcase how those tools can be useful to us. I will post some code I used in the past and, if I have time, I will accompany it with notebooks explaining the main steps and decisions.