We examine the impact of a payday lender moving into a neighbourhood on nearby debtors' uses of formal credit. We also look at what the effects are of payday lenders leaving neighborhoods, and what kind of regulations best protect borrowers from the harmful effects of payday loans. The USOAR student would support the project by conducting analysis of what kinds of neighbourhoods payday lenders move into. We would start with basic descriptive statistics (we can help support learning how to code), but depending on the student, we could move to more complex predictive models to be included in our larger analysis.
Are payday lenders harmful for borrowers, and if so why? The existing research is mixed. Our project hopes to answer what happens to the formal credit borrowing behaviour of people who live close to a payday lender that enters, or a payday lender that exits. Additionally, we can use different regulations that are introduced to police payday loans and assess their effectiveness at helping borrowers achieve financial resiliency. We are looking for a student that would be interested in helping us find out more information about what kinds of neighbourhoods payday lenders exit and leave. If there are particular characteristics that stand out, we can control for these in our larger analysis. Depending on the student, we could also extend the project to look at probabilistic models of payday entry and include more sophisticated ways of controlling for relevant neighbourhood characteristics.
-some experience with coding is desirable but not a dealbreaker
-coding experience in widely used statistical software (either R or STATA)
-presenting and communicating scientific results
-exposure to hypothesis testing, including how to formulate hypotheses, how to use statistical processes to test for them, and how to interpret results
-experience working within a research team that has an organized structure with researchers at a variety of points in their career