ABSTRACT
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
TABLE OF CONTENTS
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
Identification
chapter 6|14 pages
Causal Diagrams
chapter 7|14 pages
Drawing Causal Diagrams
chapter 8|14 pages
Causal Paths and Closing Back Doors
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