Literature

With the growth in the importance of data and various reproducibility crises (or just a constant state of crisis?), there has been a surge of efforts putting ideas similar to this course into writing.

Here are some with different focuses

• Coding for Economists Pretty cool, fairly recent online book, focus towards metrics.

• Research Software Engineering with Python — the closest in many ways to this course. One author is Greg Wilson, who founded the Software Carpentry project. EPP grew out of “translating” an early version of Software Carpentry to economics in 2010. Naturally, we took some different branches since, but the core ideas remain the same.

• Software Design by Example, by the very same Greg Wilson. This goes into much more detail on software development, no specific focus on scientific software / data analysis.

• The Plain Person’s Guide to Plain Text Social Science — similar ideas, different angle. The introduction is a pure piece of beauty and gives some great background if you have mostly worked with Tablets, Word, and similar tools (as opposed to programming a lot yourself)

• The Turing Way — self-identifies as “an open source community-driven guide to reproducible, ethical, inclusive and collaborative data science.” Geared a bit towards larger projects, many very nice ideas.

• Code and Data for the Social Sciences: A Practitioner’s Guide — From 2014 and some specifics are a bit outdated. Also, we go well beyond this in the course. However, if you feel that you need some premier economists’ writing on the topic to gear up your motivation, this is for you.

• A Gentle Introduction to Effective Computing in Quantitative Research — A bit more geared towards number crunching than this course, less strong on the software engineering side. Very useful as a complement.