By Warren Hrung
ABA DataBank
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The theory
A goal of interest rate caps is to make borrowing cheaper and reduce delinquencies for those with weaker credit. But basic economics suggests a tradeoff: if the interest rate cap is below the market-clearing rate, lenders will reduce the amount of credit extended. The Fed research extends the basic analysis to examine high-risk and low-risk borrowers (see Figure 1 from the associated blog post.) The market equilibrium has lenders charging high-risk borrowers a higher interest rate than low-risk borrowers to compensate for higher expected loan losses. With the imposition of a rate cap (icap) below the market-clearing rate for the high-risk borrowers (i*), the level of credit to high-risk borrowers falls (Lcap < L*) — that is, the rate cap leads to less credit for high-risk borrowers.
Figure 1.
There are only a few examples of a national rate cap in the United States. One such case is the 36% cap on certain loans to military service members and their families. More commonly, interest rate caps are set by individual states, and those state differences are what the Fed researchers analyze.
Empirical analysis
Comparison within states. The researchers studied interest rate caps on loans made by payday lenders, installment lenders, and auto-title lenders in Illinois, South Dakota and North Dakota. These states enacted 36% rate caps between 2016 and 2022. Banks and credit unions were not covered by these caps.
The study used Equifax data covering more than 35 million borrowers. Researchers sorted borrowers into 10 groups based on credit score, from the riskiest to the safest. After the caps took effect, lending to the riskiest borrowers fell by about 8%, while lending to the safest borrowers changed little. Furthermore, missed-payment rates for the riskiest group did not improve. In other words, these borrowers had less access to credit, but no reduction in terms of delinquency.
Comparison across states. The researchers also compared borrowers in those three states above with borrowers in seven states that did not adopt caps during the study period: Alabama, Delaware, Idaho, Missouri, South Carolina, Utah and Wisconsin. Borrowers were again grouped by credit score so that the riskiest borrowers could be compared across cap and no-cap states.
The results show that, before the caps took effect, loan balances for the riskiest borrowers were similar in both groups of states. After the caps were introduced, those balances fell sharply in cap states. Five quarters later, the riskiest borrowers in cap states had loan balances that were about $2,000 lower on average than similar borrowers in states without caps. The study were no less likely to miss payments. Therefore, the goal of lower delinquencies for the riskiest borrowers was not achieved.
Credit reallocation. The research also examines why rate caps do not seem to affect credit conditions in the aggregate. The authors hypothesize that after caps are imposed, lenders shift funding to safer borrowers, as a rate cap is less likely to be binding for more creditworthy borrowers. The results support that idea: borrowers in the middle of the credit score range in states with caps borrowed more after the caps took effect than similar borrowers in no-cap states. This is consistent with lenders in cap states re-allocating credit to relatively more creditworthy borrowers. Five quarters after rates were capped, borrowers in the middle of the credit distribution in cap states had loan balances over $1,500 higher on average than counterparts in no-cap states.
Interest rate caps for credit cards
There is no federal cap on credit card interest rates today. However, legislation proposing a cap has been introduced in recent years, and the New York Fed research offers a useful guide to the likely effects. The findings support the basic intuition that rate caps reduce access to credit for riskier borrowers, with no accompanying change in delinquencies. As a result, high-risk borrowers are unlikely to see much of a benefit from a cap on credit card rates.
