Financial Mistakes among Elderly Homeowners
Research in behavioral economics has documented that consumers make suboptimal financial decisions, and that cognitive impairments like Alzheimer’s and dementia can explain a large share of such mistakes among the elderly population. This project seeks to isolate financial mistakes among elderly homeowners which lead to severe property tax and mortgage delinquencies, or even the loss of a home. Such mistakes might include missing payments, a lack of take-up of local tax forbearance policies, and failure to use subsidized loan products like government-sponsored reverse mortgages to cover existing debts.
I am seeking a team or RAs to work towards the creation of a nationwide database of property tax delinquencies and mortgage foreclosures linked to public health records. The bulk of the RA work involves web scraping, submitting written data requests to governmental offices, and formatting property addresses across different databases to track homeowners over time. The results of this study will speak to the extent to which nudges, financial counseling, and/or mental health service provision can mitigate intergenerational wealth inequality and improve household welfare.
Requisite Skills and Qualifications
The data acquisition portion of this project involves compiling records from municipal tax authority and state public health 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 data 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 (e.g. tigris in R), to geo-locating data points. However, familiarity with these tools is not a requirement.
Basic 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, public health, computer science, mathematics/statistics, physics, and political science.