Using Market Concentration and its Implications for the Urban Poor

Award:
Josh Purtell Gabriel Mazuera Nicole Zhen Joojo Ocran

Proposal Description:

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 will document recent changes in ownership of rental properties across US cities and market concentration in the urban housing markets. Second, we will study the impacts of these changes on poor urban renters’ housing stability and housing costs. Third, we will 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 poor urban residents.

This project is in an early stage and is an opportunity to be directly involved with the research process. The research assistant will work directly with the faculty 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 are essential. Prior experience with Latex and Git, and training in econometrics, statistics, and data science are preferred. Additional experience working with SQL or experience working with large data sets, while not required, is also a plus.