The Effect: An Introduction to Research Design and Causality

by Nick Huntington-Klein

Overview

This book is about research design, specifically concerning research that uses non-experimental data to figure out whether one thing causes another. It is separated into two halves, each with different approaches to that subject. Concepts are demonstrated with a heavy emphasis on graphical intuition and the question of what we do to data.

Product Details

ISBN-13:	9781032580227
Publisher:	CRC Press
Publication date:	07/09/2025
Edition description:	2nd ed.
Pages:	686
Product dimensions:	7.00(w) x 10.00(h) x (d)

About the Author

Nick Huntington-Klein is a professor of economics at Seattle University specializing in the study of the education system and applied econometrics. He is known as someone who can clearly explain complex topics in econometrics, and his teaching materials have been shared online tens of thousands of times. His daughter is not yet old enough to find this hopelessly uncool.

Table of Contents

Introduction xix

I The Design of Research 1

1 Designing Research 3

2 Research Questions 9

3 Describing Variables 19

4 Describing Relationships 45

5 Identification 67

6 Causal Diagrams 87

7 Drawing Causal Diagrams 101

8 Causal Paths and Closing Back Doors 115

9 Finding Front Doors 129

10 Treatment Effects 143

11 Causality with Less Modeling 161

II The Toolbox 173

12 Opening the Toolbox 175

13 Regression 179

14 Matching 267

15 Simulation 327

16 Fixed Effects 381

17 Event Studies 407

18 Difference-In-Differences 435

19 Instrumental Variables 469

20 Regression Discontinuity 505

21 A Gallery of Rogues: Other Methods 555

22 Under the Rug 579

Bibliography 601

Index 617

Editorial Reviews

"Nick has created a classic. Can’t say it any other way.  It’s the replacement for Mastering Metrics that we all wanted.  This is the book that will empower students in both understanding what econometrics is or can be, and how to get from A to B with programming practice.  He has created numerous on-ramps into econometrics that can help hit many different types of students at where they are, rather than teaching to students who most resemble the kind of student that our econometrics and statistics professors were when they were the students’ age.  I mean that in the most flattering way possible.

I think the book is phenomenal and will sell well. It’s basically an ambitious book that seeks to take students with zero knowledge of causal inference, but also zero knowledge of programming languages, and possibly even minimal knowledge of statistics, and over 600 pages with excellent writing, extensive programming examples across multiple languages, and causal graphs cover just about everything remotely conceivable to make a student conversant and maybe even competent. Except for my book, there’s nothing like what Nick has done on the market …It will be a very popular companion textbook on many econometrics courses, and may even help facilitate the creation of more causal inference courses are all levels. I think Nick has absolutely nailed it."

- Scott Cunningham, Baylor University (author of Causal Inference: A Mix Tape)

From the Publisher