About this book

Applied Microeconometrics MIT Press

Amazon

Penguin Random House

This website accompanies the book “Applied Microeconometrics” published by MIT Press in 2026.

This book discusses the theory and practice of applied microeconometrics. In particular, the book aims to provide an overview of the theory and practice of microeconometric methods frequently used for causal inference in applied research. Throughout the book, we will examine the range of tools which an applied microeconometrician, or any social scientist using quantitative methods with micro-level data, needs in their tool kit. This includes experimental methods, as well as observational methods such as difference-in-difference designs, regression discontinuity designs, instrumental variable methods, and machine learning among other themes.

The book is targeted at a graduate level, and assumes some familiarity with econometrics including tools from statistics and linear algebra. Nevertheless, the book builds up the methods discussed from first principles, laying out key assumptions for causal analysis, and a range of considerations which an applied researcher will need to know. In this sense, the book seeks to serve practitioners of microeconometrics and social scientists generally. It thus may suit readers from upper level undergraduate courses seeking a rigourous treatment of causal methods, masters students, PhD students, and researchers who may be well out of graduate school, and seeking an up to date compendium on the practice of applied microeconometrics.

Table of Contents

  1. Identifying Causal Effects
  2. Ignorable Treatment Assignment: Experiments and Random Assignment
  3. As Good as Random?: Constructing a Counterfactual with Observables
  4. Counterfactuals from the Real World: Difference-in-Differences, Synthetic Controls and their Derivatives
  5. Estimation with Local Manipulations I: Instrumental Variables and LATE
  6. Estimation with Local Manipulations II: Regression Discontinuity Designs
  7. Testing, Testing: Hypothesis Testing in (Quasi-)Experimental Designs
  8. Beyond Average Treatment Effects and Beyond the Population Under Study…
  9. Machine Learning

The book can be purchased directly from the MIT Press Book Store, or from other retailers such as Blackwell’s. Further retail information can be found on the book’s home page at MIT Press.

This website provides a wide array of “code call-outs” and illustrations discussed throughout the book. These can be followed along in R, Stata or Python. As well as the code call-outs, an introduction to each of these languages is provided. If you do not have familiarity with any of these languages and would like to follow along with the code call-outs you can refer to the introduction to any of the specific languages provided, which gives a sufficient base to follow along with code call-outs below.

For further information on accessing all data, refer to the data page of this site.