Seminario de Análisis Empírico

Empirical analysis seminar: reading and replicating applied microeconomics research, with lecture slides and assignments.

← All teaching

Fall 2026

Tentative — subject to change during the term.

Syllabus

• Syllabus

Slides

• Lecture 1 - Where data comes from: surveys, administrative records, and big data
• Lecture 2 - Your AI chat partner: LLMs as a chatbot

Problem Sets

• Homework 1 - Where data comes from
• Homework 2 - Asking the AI, and then verifying it

Data

The running example for the course. Neither analysis file sits ready-made on a portal: both were cut from the national releases by the build script, so you can rebuild either one.

• municipios_clean.csv — 2,469 municipios: population, schooling, illiteracy, poverty rates
• enigh_hogares_raw.csv — 91,414 households: income, household size, state, survey weight
• coneval_pobreza.csv — CONEVAL poverty indicators, for the join exercises
• build_data_real.R — the script that produces all three
• Read me first — provenance, attribution, and what to read before you compute anything

Sources: INEGI, Censo de Población y Vivienda 2020 · INEGI, ENIGH 2024 · CONEVAL, Medición de la pobreza municipal 2020. Accessed 2026-08-16. Nothing in these files is simulated or imputed.

Spring 2026

Syllabus

• Syllabus

Slides

• Lecture 1 - Intro to R
• Lecture 2 - Working with data in R
• Lecture 3 - Basics of programming
• Lecture 4 - Stats review
• Lecture 5 - Summarizing data
• Lecture 6 - Potential outcomes and the experimental ideal

R Code

• Lecture 1
• Lecture 2
• Lecture 3
• Lecture 4
• Lecture 5
• Lecture 6