I have an ongoing interest in effective workflows for conducting empirical research. I lecture on these topics and enjoy teaching these skills to younger economists.
“Code, Data, and Version Control: Best Practices for Economic Research” is a crash course in how to organize empirical projects, write good code, manage and validate data, and make effective use of version control.
The presentation is intended for a broad audience, including research assistants, PhD students, and post-PhD researchers in economics and related disciplines. It is agnostic about programming language, though a few examples use Stata syntax.
Here is a short, high-level version of “Code, Data, and Version Control: Best Practices for Economic Research” tailored to beginning researchers, such as undergraduate thesis-writers or research assistants.
I gave a three-part lecture series on “Organizing Data for Economic Research” while on faculty at UC Davis. The first two parts ( Managing Workflow and Handling Data) are superseded by my newer lectures and contain much stale advice, but they are specifically targeted at Stata users. The third part ( Sharing Your Work) is not covered in my recent lectures.
For template code broadly reflective of my current thinking, check out the replication package for “Disability Insurance in the Great Recession: Ease of Access, Program Enrollment, and Local Hysteresis” (joint with Melissa Kearney and Riley Wilson).