Just as it takes a village to raise a child, it takes many people to help me write a book like this. The people to whom I am indebted range from the scholars whose work has inspired me–Alberto Abadie, Josh Angrist, Susan Athey, David Card, Esther Duflo, Guido Imbens, Alan Krueger, Robert LaLonde, Steven Levitt, Alex Tabarrok, John Snow, and many more–to friends, mentors, and colleagues.
I am most indebted first of all to my former advisor, mentor, coauthor, and friend Christopher Cornwell. I probably owe Chris my entire career. He invested in me and taught me econometrics as well as empirical designs more generally when I was a grad student at the University of Georgia. I was brimming with a million ideas and he somehow managed to keep me focused. Always patient, always holding me to high standards, always believing I could achieve them, always trying to help me correct fallacious reasoning and poor knowledge of econometrics. I would also like to thank Alvin Roth, who has encouraged me over the last decade in my research. That encouragement has buoyed me throughout my career repeatedly. Finally, I’d like to thank Judea Pearl for inviting me to UCLA for a day of discussions around an earlier draft of the Mixtape and helping me improve it.
But a book like this is also due to countless conversations with friends over the years, as well as reading carefully their own work and learning from them. People like Mark Hoekstra, Rebecca Thornton, Paul Goldsmith-Pinkham, Mark Anderson, Greg DeAngelo, Manisha Shah, Christine Durrance, Melanie Guldi, Caitlyn Myers, Bernie Black, Keith Finlay, Jason Lindo, Andrew Goodman-Bacon, Pedro Sant’anna, Andrew Baker, Rachael Meager, Nick Papageorge, Grant McDermott, Salvador Lozano, Daniel Millimet, David Jaeger, Berk Ozler, Erin Hengel, Alex Bartik, Megan Stevenson, Nick Huntington-Klein, Peter Hull as well as many many more on #EconTwitter, a vibrant community of social scientists on Twitter.
I would also like to thank my two students, Hugo Rodrigues and Terry Tsai. Hugo and Terry worked tirelessly to adapt all of my blue collar Stata code into R programs. Without them, I would have been lost. I would also like to thank another couple of students, Brice Green and Ian McBride, for debugging all of the R code to confirm it worked by non-authors. Blagoj Gegov helped create many of the figures into Tikz. I would like to thank Ben Chidmi for adapting a simulation from R into Stata, and Yuki Yanai for allowing me to use his R code for a simulation. Thank you to Zelijko Hrcek for helping make amendments to the formatting of the LaTeX when I was running against deadline. And thank you to my friend, Seth Hahne, for creating several beautiful illustrations throughout the book. I would also like to thank Seth Ditchik for believing in this project, my agent Lindsay Edgecombe for her encouragement and work on my behalf, and Yale University Press. I would like to thank the health economist, Marcelo Perraillon, whose insightful approach to using simulated variables and figures to illustrate estimation challenges with regression discontinuity shaped my own pedagogy. I also acknowledge him for introducing me to the “cmogram” command in Stata. I would also like to thank Valerio Filoso for introducing me to the “reganat” command in Stata, as well as derivations and proofs for the Frisch-Waugh-Lovell theorem.
I’d also like to thank Kyle Butts for converting the book to an HTML document and converting the R scripts into a set of teaching resources. Tom Caputo generously created python code for all the exercises.
Finally, I’d like to thank my close friends, Baylor colleagues, students and family for tolerating my eccentric enthusiasm for causal inference and economics for years. I have benefited tremendously from many opportunities and resources, and for that and other things I am very grateful.
All errors in this book were caused entirely by my stupidity, not the people listed above.