- 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
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.
Title: The Effect: An Introduction to Research Design and Causality
Author: Huntington-Klein, Nick
ISBN: 9781032125787
Binding:
Publisher: Taylor & Francis Ltd
Publication Date: 2022-01-05
Number of Pages: 620
Weight: 1.2113 kg
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)
