Local governments recover missing revenues from overdue tax bills by auctioning off claims to homes in what is known as either a tax lien or tax deed sale. This project examines the role of tax delinquencies in facilitating corporate real estate purchases in U.S. prime property markets, and the effects of these purchases on housing affordability and local demographic change. It has been alleged in the popular media that tax lien sales accelerate gentrification within major cities, promote wealth inequality, and allow certain companies to greatly expand their real estate holdings by converting cheap housing to commercial development projects.
I am seeking a team of RAs to assist in the creation of a nationwide database of local tax sale auction records through a combination of web scraping and submitting FOIA requests. These records will then be merged with larger databases of property transactions, business permits, and Census data covering major U.S. metros.
Requisite Skills and Qualifications:
The data acquisition portion of this project involves compiling records from municipal tax authority and treasury websites. This may require a large number of web searches, web scraping (i.e. batch downloading files and text, or converting PDFs to tabular format in Excel), submitting written FOIA requests via email to the relevant public official(s), and cleaning the raw data to ensure consistency across jurisdictions. Therefore, attention to detail and professional writing skills are crucial to the execution of the research.
Prior experience with web scraping is preferred. I am especially interested in candidates who have experience applying ArcGIS, Google Maps API, and related software packages, to geo-locating data points.
Proficiency in statistical/econometric software packages such Stata or R is required for aspects of the project which involve cleaning the source data collected.
I welcome applicants with interests in other fields besides economics – including but not limited to – finance, urban studies, computer science, mathematics/statistics, physics, and political science.
- Robby Hill
- Fyze Tulyag
- Lisa Dong