This project aims to understand the recent trend in concentration of rental property ownership in many major US cities and its consequences for the urban poor. First, we document recent changes in ownership of rental properties across US cities and market concentration in the urban housing markets. Second, we study the impacts of these changes on poor urban renters’ housing stability and housing costs. Third, we study how the movement towards larger corporate landlords affects eviction. The ultimate goal of this project is to understand how changes in the urban rental market structure and regulations in this market affect the lives of low-income urban residents.
I am looking for students to help with web scraping as well as to work directly with the the authors on the cleaning and analysis of multiple large proprietary data sets and have an opportunity for learning important research skills such as working with big data, data visualization, data analysis, and machine learning.
Requisite Skills and Qualifications:
Proficiency in a statistical/econometric software packages such as R, stata, or python is essential. We are specifically looking for at least one student who has experience with web scraping.
Prior experience with Latex and Git, and training in econometrics, statistics, and data science are preferred.