Coding and Code

This section links to resources that I or other people have compiled, and that I have found helpful in my RA work and personal research. Graduate Students and Research Assistants may find these particularly helpful. I will also include programs and Stata .ado files that I have written.

Adjust for US Inflation

Stata .do file that can be used to adjust US data for inflation. Date range is 1920-2018, and will be updated as the BLS makes their series available. This .do file allows users to convert data using annual or monthly inflation. Calculations are based on BLS series CUUR0000SA0, which includes "all items in U.S. city average, all urban consumers, not seasonally adjusted." Make sure to load the program into your Stata session before running. You can download the .do file here.

Brazil Maptile Geofiles

Brazilian geofiles that can be used with the maptile Stata program by Michael Stepner. I have compiled geofiles for Brazilian states, municipalities, arranjos (metropolitan areas) and microregions. You can find instructions for installation here.


Data science for economists

Lecture notes by Grant McDermott on coding and code management, databases, cloud computing, Machine Learning, R, etc.

Project Euler

Use any programming language you may want to practice to try to solve math problems. My colleague suggested trying to optimize runtime, if possible, to learn how to solve programming problems without relying on brute force. Note that problems tend to get much harder as you go. Most answers can be found on stackexchange, etc.

DataCamp

How I learned R and SQL.

Code and Data for the Social Sciences: A Practitioner's Guide

RA manual by Matthew Gentzkow and Jesse Shapiro.

BASH for those of us just trying to run things on the server

I have this Linux Bash Shell Cheat Sheet on my desk for easy access.

Nick Huntington-Klein's Causal Inference Animated Plots

These graphs are helpful in terms of helping a new student of econometrics intuitively understand what different methods are doing to the data. Thank you, EconTwitter, for helping me find these.