The Effect: An Introduction to Research Design and Causality

by Nick Huntington-Klein

Overview

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

Product Details

ISBN-13:	9781032125787
Publisher:	CRC Press
Publication date:	01/05/2022
Pages:	646
Sales rank:	177,779
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. To his great anguish, his toddler daughter refuses to learn about sampling variation and would rather listen to that one Moana song on repeat.

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