• The Effect

    Nick Huntington-Klein

  • ▾ Chapters
    The Effect: An Introduction to Research Design and Causality
    • Additional Materials
    • Revision and Updates
    Introduction The Design of Research 1 - Designing Research 2 - Research Questions 3 - Describing Variables 4 - Describing Relationships 5 - Identification 6 - Causal Diagrams 7 - Drawing Causal Diagrams 8 - Causal Paths and Closing Back Doors 9 - Finding Front Doors 10 - Treatment Effects 11 - Causality with Less Modeling The Toolbox 12 - Opening the Toolbox 13 - Regression 14 - Matching 15 - Simulation 16 - Fixed Effects 17 - Event Studies 18 - Difference-in-Differences 19 - Instrumental Variables 20 - Regression Discontinuity 21 - A Gallery of Rogues: Other Methods 22 - Under the Rug References

The Effect: An Introduction to Research Design and Causality

The cover of The Effect

Click here to order your copy of The Effect from Chapman & Hall now! You can use code NHK20 to get a 20% discount. The book can also be ordered on Amazon or Barnes and Noble.

Welcome to the web version of The Effect. The Effect is now out in published form from Chapman & Hall, but they have allowed this free Bookdown version to remain here on theeffectbook.net. This Bookdown version will continue to be free, but I also hope that you will purchase the published version now that it is available. If you would like to be kept informed about updates to the book, such as when new teaching materials come out, please add your email to the mailing list (no more than one email/month).

The Effect is a book intended to introduce students (and non-students) to the concepts of research design and causality in the context of observational data. The book is written in an intuitive and approachable way and doesn’t overload on technical detail. Why teach regression and research design at the same time when they are fundamentally different things? First learn why you want to structure a design in a certain way, and what it is you want to do to the data, and then afterwards learn the technical details of how to run the appropriate model.

This book consists of a Part 1 dedicated to research design and causality, making use of causal diagrams to make the concept of identification straightforward, and a Part 2 dedicated to implementation and common research designs like regression with controls and regression discontinuity. You can see the chapters and navigate between them on the left (on in the dropdown menu up top if you’re on a small screen).

If you would like to run the code examples in this book, you’ll need the causaldata package, which contains the example data for most of the code chunks. Causaldata can be installed using install.packages('causaldata') in R, ssc install causaldata in Stata, or pip install causaldata in Python.

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0.1 Additional Materials

  • A video series accompanying the book. If you prefer the videos without the background music, those are available here.
  • Homework assignments to accompany the book
  • Source code for the book’s code, and citations for all software packages used (and downloadable data). Note this is code to produce the content of the book itself (graphs, calculations, etc.), not a repository for the book’s code examples.
  • The causaldata downloadable package for R, Stata, and Python, which provides data you can use with the book’s code examples

If you want a set of slides to see how the book’s material can be used, I can point you to the slides for my Applied Econometrics course, which sort of splits the difference between an econometrics course and a pure causality course. I also have slides for my Causality course. As per the readme which refers to the book not being complete, the causality course has not been updated in a while, but Lectures 1-7b should still be pretty handy in setting up your own course.

0.2 Revision and Updates

While updates to this book material will not be frequent at this point, to keep consistent with the published version, please do send any comments or questions about the material to nhuntington-klein@seattleu.edu or to me on Twitter at nickchk. You can also submit feedback, or report any typos or formatting errors you find, in the Feedback Form.

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