The Effect: An Introduction to Research Design and Causality is about research design, specifically concerning research that uses observational data to make a causal inference. It is separated into two halves, each with different approaches to that subject. The first half goes through the concepts of causality, with very little in the way of estimation. It introduces the concept of identification thoroughly and clearly and discusses it as a process of trying to isolate variation that has a causal interpretation. Subjects include heavy emphasis on data-generating processes and causal diagrams.

Concepts are demonstrated with a heavy emphasis on graphical intuition and the question of what we do to data. When we “add a control variable” what does that actually do?

Key Features:

  •  • Extensive code examples in R, Stata, and Python
  • • Chapters on overlooked topics in econometrics classes: heterogeneous treatment effects, simulation and power analysis, new cutting-edge methods, and uncomfortable ignored assumptions
  • • An easy-to-read conversational tone
  • • Up-to-date coverage of methods with fast-moving literatures like difference-in-differences


part I|172 pages

The Design of Research

chapter 21|6 pages

Designing Research

chapter 2|10 pages

Research Questions

chapter 3|26 pages

Describing Variables

chapter 4|22 pages

Describing Relationships

chapter 5|20 pages


chapter 6|14 pages

Causal Diagrams

chapter 7|14 pages

Drawing Causal Diagrams

chapter 9|14 pages

Finding Front Doors

chapter 10|18 pages

Treatment Effects

chapter 11|12 pages

Causality with Less Modeling

part II|428 pages

The Toolbox

chapter 17412|4 pages

Opening the Toolbox

chapter 13|88 pages


chapter 14|60 pages


chapter 15|54 pages


chapter 16|26 pages

Fixed Effects

chapter 17|28 pages

Event Studies

chapter 18|34 pages


chapter 19|36 pages

Instrumental Variables

chapter 20|50 pages

Regression Discontinuity

chapter 22|22 pages

Under the Rug