Econometrics Guide

Preface

This is a study guide rather than a textbook. The chapters summarise what I have learned over the years from Davidson and MacKinnon’s Econometric Theory and Methods, Chris Baum’s An Introduction to Modern Econometrics Using Stata, and a scatter of papers and lecture notes that helped me make sense of the same material from different angles. The aim is a single place where the workhorse estimators of applied econometrics — OLS, MLE, GLS, IV and GMM, models for censored, discrete, count, panel, and survival data, dynamic panels, and missing-data methods — sit side by side with the assumptions they rely on and the small code snippets needed to fit them.

Examples are written in R or Stata, whichever has the cleaner implementation for the procedure at hand. The code is meant to be short enough to read and re-run rather than a packaged tutorial. For applied causal-inference material — difference-in-differences, matching, doubly robust methods, mediation, causal discovery, and the rest — see the companion books Introduction to Causal Econometrics and Topics on econometrics and causal inference.