Consumer Credit Markets

12/31/2024
Featured in print Reporter
By Christopher Palmer

Consumer credit markets play a pivotal role both in the macroeconomy and in people’s lives because they are tightly linked to consumption, financial distress, household investment, financial inclusion, and monetary policy transmission. Put another way, what happens in credit markets doesn’t stay in credit markets. Both supply-side and demand-side disruptions and dysfunctions in credit markets have real effects on outcomes as widely varying as car prices, bankruptcy, education, and where people live. Public policy reflects this importance, with significant regulatory efforts dedicated to supporting healthy credit markets, including consumer financial protection, mortgage guarantees, bankruptcy statutes, and banking supervision. In this article, I review my recent research highlighting the value of understanding both credit supply and credit demand to appreciate the many ways credit-market imperfections affect household financial wellbeing and the broader economy. I conclude with a discussion of promising areas for research to inform public policy issues.

Why Are Credit Markets Special?

Consumer credit markets are special for several reasons. First, credit is not a final good; consumers value debt not for its own sake but in service of consumption or investment in assets and human capital or to self-insure against shocks. Trouble in credit markets therefore affects outcomes in other markets and households’ financial resilience. Second, credit contracts entail long-term commitments with ongoing cash-flow obligations that affect households’ continuing ability to spend, save, borrow, and handle unexpected shocks. Making such decisions necessitates forward-looking optimization under uncertainty, and a wide variety of households struggle on some level with this complexity. Especially when borrowing costs are high and compound over time, the financial consequences of indebtedness can quickly spiral into nonfinancial consequences. This long-term nature of credit decisions also elevates the importance of consumer expectations, which often seem to be formed with some degree of irrationality. Third, household credit access is often limited by asymmetric information between lenders and borrowers, leading to significant borrowing constraints at both the extensive margin, such as credit access, and the intensive margin, such as credit limits and interest rates. Fourth, an important channel of monetary policy is its impact on borrowing conditions for households. Credit market frictions impact the pass-through of monetary stimulus or tightening, inhibiting the ability of monetary policies to meet their mandates.

Household Budgeting

Even though committing to a monthly budget — category-specific monthly spending limits — is a central feature of personal-finance advice, classical economic theory, such as the permanent income hypothesis, does not acknowledge any role for monthly budgeting. Similarly, the economic literature on credit constraints acknowledges the existence of binding credit limits but does not explain why households might voluntarily attempt to constrain their own per-period spending. Whether to cope with their own self-control issues or their inability to otherwise insure against all financial shocks, many households use a monthly budget. However, in the absence of a precise way to set category-specific monthly spending limits, many households target cognitively accessible round numbers and exhibit left-digit bias, meaning, for example, that amounts ending in $99 seem disproportionately lower than amounts just higher. While this decision-making may help households avoid overspending, it has several unintended consequences that I explore in a series of papers focusing on the auto-loan industry. The auto-loan market itself is a useful laboratory for studying how consumer credit supply and demand interact. Auto loans are the largest category of non-mortgage consumer debt in the US, directly affect car purchasing behavior, and are held by most US households.

First, with Bronson Argyle and Taylor Nadauld, I demonstrate that households indeed target specific round-number monthly payments when they shop for cars and car loans, a phenomenon we refer to as “monthly payment targeting.”1 We show that many borrowers base their debt decisions primarily on the associated monthly payment consistent with the complexity of making affordability decisions and with the ubiquity of heuristic budgeting. Monthly payment targeting makes demand particularly sensitive to a loan’s maturity and relatively less sensitive to interest rates because of the outsize effect of longer maturity on reducing monthly payments. On the supply side, this leads lenders, who are often car dealers themselves, to cater to the demand-side preference for low monthly payments by offering longer-term loans, keeping car buyers indebted for longer and raising total interest payments.

The emphasis consumers place on monthly payment levels affects the prices they pay for cars, too. With Argyle, Nadauld, and Ryan Pratt, I find that when a lender restricts the maturity of a car loan, consumers are more likely to negotiate the price of that car down, even when the seller and the lender are not integrated.2 For example, a given lender may be unwilling to make a five-year car loan on used cars more than four years old. In January 2023, when a 2018 Honda Accord switched from being four to five years old, that lender would demand a higher monthly payment. To cope, buyers with more expensive credit terms negotiate larger discounts from car sellers. This dynamic underscores the broad importance of credit conditions for related markets. Lengthening maturities for consumer loans over time can contribute to inflation by pushing up the prices of finance-dependent goods like cars. Moreover, the effectiveness of monetary or fiscal policy is attenuated when the change in demand induced by such policies is partially offset by changes in durable goods prices.

Not Shopping Around for Credit

A textbook example of credit market imperfections directly affecting consumers is the failure to shop around for credit, which limits what people buy. Consumers often fail to find the best interest rate available to them. Using car loans as a setting again, Argyle, Nadauld, and I estimate that the average borrower needs around three quotes to find close to the best available rate.3 Higher interest rates from not shopping around for credit combined with a focus on monthly payment sizes means consumers may cut back on their spending to maintain their targeted payment levels. We show that people facing expensive loans because of high loan search costs, such as those who have few potential lenders nearby, often cope by buying older and less expensive cars instead of searching for a better interest rate.

Figure 1 illustrates the interconnectedness between credit markets and final goods markets. When borrowers are just below a key credit-score threshold with a given lender, they face sharply higher interest rates, which then reduces the amount they ultimately spend on a car. The cost of searching for credit thus distorts consumption levels; this highlights the importance of credit access for households and the value of financial inclusion for an economy. Furthermore, to the extent that the cost of shopping for credit partially decouples borrowing costs from lending costs, this could hinder the pass-through of monetary policy. Future research could examine whether the post-COVID-19 acceleration of digital banking has changed competition and facilitated access to financial services.

This figure is a two-panel scatter plot titled "Credit Scores, Interest Rates, and Car Purchases" and consists of two graphs showing relationships between credit scores and financial outcomes. For each graph: The x-axis represents "Credit score relative to cutoff" ranging from -20 to +20 points. A vertical dashed line at 0 marks the "Credit-score threshold at a given lender." The left graph shows Average Interest Rate: The y-axis ranges from 5.0% to 7.0%. There is a sharp discontinuity at the threshold, with interest rates dropping from approximately 6.8% to 5.5% when crossing above the cutoff. Below the threshold (negative scores), interest rates cluster around 6.5-7.0%. Above the threshold (positive scores), interest rates cluster around 5.3-5.5%. The right graph shows Average Car Purchase Price: The y-axis ranges from $17,500 to $19,500. There is also a sharp discontinuity at the threshold as credit scores increase. Below the threshold, purchase prices generally range from $17,700 to $18,000. Above the threshold, purchase prices show slightly more variation but generally cluster from about $19,200 to $18,700. The source line reads: "Source: Argyle B, Nadauld TD, Palmer C. NBER Working Paper 25668, March 2019, Review of Financial Studies 33 (11), pp. 5416–5462, and NBER Working Paper 26645, January 2020, and The Review of Financial Studies 36(7), pp. 2685–2720."
Figure 1

Supporting Borrowers Through Credit Market Policies

A number of public policies seek to support healthy credit markets through stimulus during recessions, support for consumer decision-making, and regulations that protect consumers from financial distress. Below, I review my research studying the effectiveness of such policies.

The importance of consumer credit for monetary policy

The importance of well-functioning consumer credit markets is exemplified by how mortgage market frictions modulate the pass-through of monetary policy to households. My research with Marco Di Maggio and Amir Kermani shows that the refinancing spurred by quantitative easing (QE) raises consumption and is an important channel through which monetary policy operates.4 Many central banks now purchase large amounts of long-term bonds to drive down long-term interest rates when extraordinary monetary stimulus is warranted. We document the causal effects of Federal Reserve QE mortgage purchases on mortgage refinancing, equity extraction, and consumption. Households with better access to credit and lower interest rates because of QE were more likely to increase their durables consumption and extract home equity during the Great Recession. Figure 2 illustrates one dimension of this refinancing channel, showing that many households finance a car purchase with some of the savings from refinancing into lower interest payments.

This figure is a two-panel scatter plot titled "Mortgage Refinancing, Interest Payments, and Car Purchases" and consists of two graphs showing the effects of mortgage refinancing over time. For each graph: The x-axis represents "Months since mortgage refinance" ranging from -12 to +12 months. A vertical dashed line at 0 marks the "Month of mortgage refinance." The left graph shows Difference in monthly mortgage interest payment, relative to month of refinancing: The y-axis ranges from $0 to -$300. Before refinancing (negative months), payments remain steady near $0. After refinancing (positive months), there is an immediate drop to about -$250, with the savings appearing to slightly increase over time. The right graph shows Difference in probability of car purchase, relative to month of refinancing: The y-axis ranges from -0.1 pp to 0.5 pp (percentage points). Before refinancing, the probability hovers slightly below 0. After refinancing, there is a sharp increase in the probability of car purchase, peaking at about 0.45 percentage points, but then sharply drops to and settles at a level around 0.1 percentage points. The source line reads: "Source: "How Quantitative Easing Works: Evidence on the Refinancing Channel," Di Maggio M, Kermani A, Palmer C. NBER Working Paper 22638, September 2016, and The Review of Economic Studies 87(3), May 2020, pp. 1948–1528."
Figure 2

Are you paying attention?

Across a wide range of decisions, households update their decisions infrequently. This inertia has consequences as consumers, for example, spend money on gym memberships they don’t use, fail to refinance into lower mortgage interest payments, and miss out on retirement saving subsidies. Such consumer stickiness motivates a variety of policies to promote active choice, information gathering, and competition among providers. One of the most common forms of consumer protection is mandated disclosure, resulting in much of the fine print and paperwork that accompanies consumer debt contracts. To test whether disclosure improves consumer outcomes, I partnered with Paul Adams, Stefan Hunt, and Redis Zaliauskas to test whether redesigned disclosure can increase the interest depositors earn on their savings.5 In a series of randomized controlled field trials with five UK banks, we find that most people ignore disclosures, regardless of how they are designed or delivered or how valuable their information content might be.

If inattention is a ubiquitous demand-side friction that is important for understanding a wide variety of consumer behaviors, it is natural to ask how inattention is affected by policy. Given the importance of the refinancing channel of monetary policy transmission, inattention to refinancing opportunities could be a particularly valuable friction for policy to address. Figure 3 illustrates the scope of the policy opportunity using data on the US mortgage market. Interest rates on the flow of newly originated mortgages (dark gray line) are reasonably responsive to monetary policy (light gray line). By contrast, because of the prevalence of fixed-rate mortgages and the slow responsiveness of borrowers to refinancing opportunities most of the time, interest rates on the stock of outstanding mortgages (blue line) reflect conventional monetary policy only sluggishly.

This figure is a line graph is titled "Interest Rates on Outstanding and Newly Originated Mortgages" and shows a single graph tracking three different interest rates from 1990 to 2024. The graph displays three distinct lines: •	Average rate on outstanding mortgages (blue line) •	Average rate on new mortgages (black line) •	Federal Funds Effective Rate (gray line) The y-axis shows interest rates ranging from 0% to 12%. The x-axis has markers from 1990 to 2020 in 5-year intervals, but the line extends until 2024. Key features: •	All three rates show a general downward trend over the 30-year period. •	The average rate on outstanding mortgages (blue) declines more gradually than the other rates, starting around 9% in 1990 and ending near 4% in 2024. •	The average rate on new mortgages (black) shows more volatility than outstanding mortgages, generally tracking lower and responding more quickly to market changes. It started at around 10% in 1990 and gradually declined to around 3% by 2020 before spiking sharply to about 8% by 2024. •	The Federal Funds Effective Rate (gray) shows the most volatility and typically runs lower than both mortgage rates, with periods near 0% after 2008 and again in 2020. The line started at around 9% in 1990 and after experiencing sharp variation, finishes at around 5% in 2024. The source line reads: "Source: "The Last Mile of Monetary Policy: Inattention, Reminders, and the Refinancing Channel," Byrne S, Devine K, King M, McCarthy Y, Palmer C. NBER Working Paper 31043, March 2023."
Figure 3

A follow-up study inspired by the savings field experiments suggests a way in which policy could matter. Partnering with Shane Byrne, Kenneth Devine, Michael King, and Yvonne McCarthy, I analyze a large-scale field experiment in Ireland to study the potential of reminders about mortgage refinancing opportunities to improve refinancing decisions.6 Testing several possible interventions, we find that combining disclosures with a simple follow-up reminder letter increases refinancing from 9 percent to 16 percent. Monetary policy is sometimes maligned as “pushing on a string” because it ultimately relies on credit demand to respond to the change in financial slack. However, our results demonstrate that readily implementable communication strategies can improve and complement monetary policy transmission through the refinancing channel.

Balancing credit access and consumer protection

One of the strongest tensions in consumer credit policy is between efforts to increase credit access and efforts to minimize financial distress. This policy pendulum swings back and forth over time, sometimes emphasizing one objective over the other. For example, as subprime mortgage foreclosures spiraled in the wake of the global financial crisis, many commentators argued for tighter mortgage lending standards. Subprime mortgages accounted for most foreclosures during the crisis despite only having a 13 percent market share of outstanding mortgages at the time. A central question in the postmortem has been the extent to which this subprime crisis was driven by looser lending standards during the pre-crisis credit boom or by falling house prices during the bust. Given that house prices fell by an average of 30 percent, would so many mortgages have defaulted even if they had been originated under tighter credit standards? I take up this question using a new methodology to estimate loan default models when factors such as house price declines are themselves partially driven by loosening credit, eventually leading to a credit and housing bust.7 Even accounting for the potential feedback between credit and prices, I find that most defaults were driven by house-price declines and would have happened even under tighter underwriting standards.

Although this conclusion does not fully excuse risky lending practices, it highlights the importance of balancing consumer protection with financial inclusion. If credit-market regulations lock many potential borrowers out of credit markets, these real consequences deserve to be weighed alongside efforts to prevent consumer financial distress.

Future Considerations for Research and Policy

The lessons discussed above suggest several potential paths for research to inform policy. First, research could quantify the distortions created when credit access is restricted and characterize the trade-offs between preserving credit access and protecting consumers from financial distress. For example, usury laws cap the maximum interest rate that lenders can charge but can make it difficult for high-risk households to access credit. Capital requirements aim to ensure banks have sufficient cushions to weather shocks without bailouts or harmful cuts to credit supply but can tilt lending away from consumers who value credit access the most. Regulations that make subprime lending unattractive for lenders can lock households out of credit markets, preventing them from accumulating wealth through homeownership. The net welfare effects of credit-market access merit significant attention, including through the lens of equal opportunity across groups. Second, consumers interacting with credit markets necessarily form expectations about a host of economic variables.8 There is currently only limited evidence on ways to sharpen the forecasting ability of consumers whose expectations are persistently inaccurate. Third, recent work shows that a significant portion of household liabilities are not observable to analysts using traditional data sources.9 Learning why, when, and how consumers resort to such “shadow debt,” including studies of credit deserts, could inform financial inclusion efforts.

Endnotes

1.

Monthly Payment Targeting and the Demand for Maturity,” Argyle B, Nadauld TD, Palmer C. NBER Working Paper 25668, March 2019, and The Review of Financial Studies 33(11), January 2020, pp. 5416–5462.

2.

The Capitalization of Consumer Financing into Durable Goods Prices,” Argyle B, Nadauld TD, Palmer C, Pratt RD. NBER Working Paper 24699, September 2020, and The Journal of Finance 76(1), September 2020, pp. 169–210.

3.

Real Effects of Search Frictions in Consumer Credit Markets,” Argyle B, Nadauld TD, Palmer C. NBER Working Paper 26645, January 2020, and The Review of Financial Studies 36(7), November 2022, pp. 2685–2720.

4.

How Quantitative Easing Works: Evidence on the Refinancing Channel,” Di Maggio M, Kermani A, Palmer C. NBER Working Paper 22638, September 2016, and The Review of Economic Studies 87(3), May 2020, pp. 1498–1528.

5.

Testing the Effectiveness of Consumer Financial Disclosure: Experimental Evidence from Savings Accounts,” Adams PD, Hunt S, Palmer C, Zaliauskas R. NBER Working Paper 25718, May 2020, and Journal of Financial Economics 141(1), July 2021, pp. 122–147.

6.

The Last Mile of Monetary Policy: Consumer Inattention, Disclosures, and the Refinancing Channel,” Byrne S, Devine K, King M, McCarthy Y, Palmer C. NBER Working Paper 31043, March 2023.

7.

An IV Hazard Model of Loan Default with an Application to Subprime Mortgage Cohorts,” Palmer C. NBER Working Paper 32000, December 2023, and forthcoming in the Journal of Finance.

9.

Personal Bankruptcy, Moral Hazard, and Shadow Debt,” Argyle B, Iverson B, Nadauld TD, Palmer C. NBER Working Paper 28901, June 2021.