potterzot

About

I am a phd student in the economics program at Washington State University, where I work as a Research Assistant with Hayley Chouinard, Michael Brady, and Phil Wandschneider to look at roadblocks that may be unique to historically underserved farmers in applying to USDA conservation programs. My research interests have to do with markets and policies for scarce resources, especially water and land issues in international development. I'm also interested in the intersection of causal inference and machine learning, and in research methodology and design generally.

I want to do research that has a practical impact, is statistically valid (i.e. no forking paths (pdf)), and is reproducible and replicable. In short, I want my research to matter. I think open science and reproducible research methods are an important part of that, and in general I believe in the power of collaborative communities and human ingenuity.

I also like open source software. I've been a Linux user for over 15 years, and currently run Arch Linux on my laptop and desktop. I write software with vim, sublime text, and Rstudio. I tend to use Amazon EC2 instances for quick testing, and also for setting up longer-term projects when necessary.

I've written several R packages and a few python programs: rnassqs provides easy access to USDA agricultural data from the NASS QuickStats API, rkclass provides instrumental variables regression analysis in R, though there are better packages to use for that. Most of my work is available on my github profile. Written work is available here.

The code to generate this site is open source and available on the site repository, which now includes an extensive note-taking system, as well as links to my bibtex library and get_paper.py, a python script that fetches published article metadata when provided with a DOI.

I'm infrequently active on twitter, where I mostly follow an assortment of awesome data people.

I also write some fiction, and in early mornings, you can usually find me on one of my favorite running trails.