Do Closing Minority Depository Institutions Affect Credit in Their Communities
Abstract: I investigate the role of Minority Depository Institutions (MDIs) in promoting credit accessibility in underserved, racially diverse urban communities. I construct a panel dataset and employ an event-study design, treating MDIs and non-MDIs branch closures within census tracts as interventions. The effects are largely minimal, with a few notable exceptions: 1) Asian MDI branch closures lower large mortgage originations within the Asian community, 2) Hispanic MDI branch closures lower small business loan (SBL) originations for small firms, 3) non-MDI branch closures lower mortgage originations in Black communities served by Black MDIs and 4) non-MDI branch closures lower small-sized mortgage originations. Surprisingly, non-MDI bank branch closures increase total SBL originations. Using lender-level Herfindahl–Hirschman index (HHI), I show branch closures do not lead to more concentrated lending markets, rather encourage entry of non-local and non-bank lenders. The results highlight the evolving role of physical bank branches in an increasingly digital banking landscape.
Abstract: I study the proximity of mission-oriented community banks, Minority Depository Institutions to historically segregated urban areas that faced restricted mortgage activity. To achieve this, I construct a panel dataset and apply a Poisson Generalized Estimating Equation (GEE) framework to investigate whether MDIs are more likely to locate in historically redlined urban areas, based on Home Owners Loan Corporations (HOLC) \enquote{residential security maps} when compared to non-MDIs. I find Black MDIs are 9 percent more likely to locate in census tracts for each one point increase in their HOLC scores whereas non-MDI bank branches are 10 percent less likely to locate in census tracts for each one point increase in their HOLC scores. The findings indicate how historical federal policies still shape credit markets and how Black MDIs co-exist with larger banks in their current local markets.
Abstract: The Paycheck Protection Program (PPP) was an emergency measure taken during Covid-19 pandemic to support small businesses that faced mandated business closures. Using Federal Deposit Insurance Corporation (FDIC) Call Report data from June 2020, I measure how much PPP loans/assets were given out by FDIC registered banks. I use nonparametric multivariate Kernel regressions and semiparametric smooth coefficient Kernel regressions to understand what institutional features lead to a higher amount of PPP loans/asset for every bank. I find that commercial and industrial loan commitments (C&I) to large businesses, C&I loans larger than $250,000 issued to small businesses, unused C&I loan commitments, core deposits and the status of the institutions as community banks, all positively influence the amount of PPP loans/asset that are disbursed by banks.
Abstract: I study whether facing extreme weather events increases the likelihood of multiple loan take-up by rural Bangladeshi households. Microcredit loans are marketed to low income rural households that do not have access to commercial banks. These institutions charge higher interest rates than commercial banks and practice predatory lending. Using count data models, I show that households that face extreme weather events, households that own agricultural or non agricultural enterprises, households with members suffering from chronic illness and those who have faced sudden illness or death of an earning member are all significantly likely to make up multiple loans from microcredit institutions.