Beschreibung:
Payday loans continue to be a commonly used yet controversial source of credit for low-income consumers. We study the consequences of capping online payday loan sizes using a fuzzy regression kink design. The interaction of lenders’ underwriting rules with state loan caps creates exogenous variation in loan offers. We exploit this variation to estimate the effect of capping loan sizes on total subsequent indebtedness on any type of subprime credit, late payment and default. We find that a) online payday customers are severely credit constrained and b) larger payday loans may help alleviate credit problems. We discuss our findings on the costs of restricting online payday lending in light of state-level regulation on the margin—minor restrictions on lending rules—such as implementing ceilings on loan principals, expanding mandatory loan repayment periods and limiting the frequency of borrowing or the practice of rolling over debt from one pay cycle to the next. Our work is the first to empirically study online payday loans in this way