Research and Communication in Economics

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Getting Started →
Install your tools, set up a project, and write your first script.

How to Complete an Economics Research Project

Follow these chapters in order. Each builds on the previous one.

1
Getting Started
Installation, interface basics, and your first script
 2
Project Organization
Folder structure, master scripts, paths, best practices
 3
Causal Inference in Theory
Selection bias, potential outcomes, and identification strategies
 4
Finding a Project
Question + Data + Identification: how to design a feasible research project
 5
Data Fundamentals
Reading/writing files, reshaping, aggregating, merging, Stata traps
 6
Descriptive Analysis
Summary statistics, visualization, publication tables
 7
Basic Regression
OLS, standard errors, fixed effects
 8
Causal Inference in Practice
Instrumental variables, difference-in-differences, event studies, regression discontinuity
 9
Automation
Loops, functions, working with large datasets

In-Class Stata Sessions

Hands-on coding exercises from class, with live quizzes.

Complete Project Walkthrough
Full project from raw data to publication-ready output: DD, event study, IV, RD, tables, figures
Diff-in-Diff and Event Studies
Two-way fixed effects, event study specifications, parallel trends, dynamic effects.
Introduction to Stata
From setup to regression: exploring data, creating variables, importing, reshaping, merging, loops, OLS, fixed effects, IV.

In-Class Exercises

Exercise 1: Basic (Job Training & Unemployment) Exercise 2: Advanced (Minimum Wage & Employment)

Worked Examples

Complete research projects you can follow start to finish.

BAC Laws and Hit-and-Run Crashes
Complete DiD analysis: data collection, cleaning, merging, regression
Texting Bans and Traffic Accidents
Event study examining texting-while-driving bans using FARS data.

Auxiliary Modules

LaTeX for Empirical Economics
Generate publication-quality tables and documents from scripts using standalone package
Programming Tips
Running scripts from the command line, logging, cross-platform considerations, and shell basics

These tutorials build on materials originally developed by Sydnee Caldwell and Benjamin Deaner for MIT 14.33. Their Stata tutorials formed the foundation for much of the reference guide content. Thanks also to past TAs Arthur Wickard and Isabel Di Tella for their contributions to the course materials. Additional resources from UCLA, Princeton, Gentzkow & Shapiro's coding guide .