The goal of the project is to investigate the impact of economic shocks on regional labor market outcomes. The project involves the digitization of historical data by disaggregated geographic units. The RAs will assist the researchers in constructing historical time-series data by using optimal character recognition (OCR) software and data parsing scripts, and some statistical analyses and modeling using the constructed data. The RAs will combine datasets from multiple sources and use modern statistical techniques to analyze them. This project is on current work by Rodrigo Adao (Booth, University of Chicago), Costas Arkolakis (Yale University) and Sun Kyoung Lee (Columbia University).
Requisite Skills and Qualifications:
We are looking for students with diverse background in terms of research skills.
Prior experience in web-scraping, and/or students with some statistics/econometrics courses such as Computational Tools for Data Science (CPSC 262/STAT 262) are especially welcome to apply. When applying, please list your major(s) and relevant courses that you have taken, along with the scanned transcripts (unofficial copy is fine) in your cover letter as in one pdf, and explain briefly (3-5 sentences) why you are interested in working on this project.
- Justin Katz '18
- Christopher Champa '18
- Gabriel Rojas '19