Teaching

Graduate Macroeconomics (TA Session Discussion Notes)

I was the Teaching Assistant of UCSD’s PhD First Year macro sequence. Below I publish the notes I have used for the discussion session with first years. They tend to be very detailed in algebraic derivations, since the objective is to make them easily comprehensible by students who are facing this material for the first time. Use them at your own risk.

  1. Fundamentals of Value Function Iteration
  2. Analytical and Numerical Solutions to VFI
  3. Inefficient Equilibria - Economy with Externalities
  4. Describing and Characterizing Competitive Equilibria
  5. Endogenous Growth with Human Capital Externalities
  6. The Romer Model
  7. Government Consumption and Distortionary Taxation

Introduction to Statistics and Probability with Python (in Portuguese)

I taught “Introduction to Stats and Probability with Python” at Institute for Higher Education of Brasília (IESB), a private university in Brasília, Brazil. This class was part of a graduate degree in Data Science and was meant to cover basic principles of statistics and statistical programming.

  1. Basic Concepts of Statistics and Statistical Programming
  2. Data Types (Time Series, Panel Data, Cross-Section); Descriptive Statistics; Introduction to pandas.
  3. Intro do Data Visualization; Intro to matplotlib and seaborn
  4. Mean, Median, Mode, Quantiles and Standard Deviation
  5. No slides (review before midterm)
  6. Functions, Probability, Density Functions, Z-scores
  7. Central limit theorem, standard errors and confidence intervals
  8. Hypothesis testing, t-statistics, p-value
  9. Intro to regression analysis; intro to statsmodels