Andrew Joung
Applied Economist
Causal Inference & Experimentation | NLP & Text-Based Data
PhD in Economics, University of Michigan · formerly Tools for Humanity
I'm an applied economist with a PhD in Economics from the University of Michigan (2026). My research uses quasi-experimental methods and large-scale administrative data to study how economic shocks reshape families and local labor markets. In my job market paper, I trace how parental job loss affects children's mobility and long-run human capital.
My research also leverages the use of unstructured data ("text-as-data"). I have published on the future of self-employment, using a BERT NLP model to classify work arrangements from open-ended survey responses. In ongoing work, I construct a novel linkage between archival NLRB union election and hospital records to study the effects of healthcare unions. I also created the NLRB Stats Archive, which digitizes seven decades of scanned government reports (1936–2009) into public data.
Before my PhD, I spent three years at The Wharton School of the University of Pennsylvania running large online behavioral experiments and randomized controlled trials with Fortune 500 companies. I received my BA in Economics from Vassar College.