Agenda

The two-day conference featured a keynote address and eight sessions of researchers presenting their work with members of CFPB’s Office of Research serving as discussants. The conference was held in person at CFPB headquarters at 1700 G Street NW, Washington DC.

Thursday, December 15, 2022

Check-in and breakfast (1 hour)

Opening remarks (15 minutes)

Buy Now, Pay Later Credit: User Characteristics And Effects On Spending Patterns

Presenting author: Emily Williams (Harvard Business School)

Firms offering “buy now, pay later” (BNPL) point-of-sale installment loans with minimal underwriting and low interest have captured a growing fraction of the market for short-term unsecured consumer credit. We provide a detailed look into the US BNPL market by constructing a large panel of BNPL users from transaction-level data. We document characteristics of users and usage patterns and use BNPL roll-out to provide new insights into consumer responses to unsecured credit access. BNPL access increases both total spending levels and the retail share in total spending, with magnitudes too large for standard intertemporal and static substitution effects to explain. These findings hold for consumers with and without inferred liquidity constraints. Our findings are more consistent with a “liquidity flypaper effect” where additional retail liquidity through BNPL “sticks where it hits”, than a standard lifecycle model with liquidity constraints. (joint with Justin Katz and Marco Di Maggio)

Buy Now Pay (Pain?) Later

Presenting author: Ben Lourie (University of California, Irvine)

“Buy Now Pay Later” (BNPL) is a largely unregulated FinTech innovation that provides consumers with easy access to credit for specific retail purchases. The BNPL market is projected to reach $1 trillion by 2025, but we know little about the effects of BNPL on consumers’ financial wellbeing. Using banking data for 10.6 million U.S. consumers, we find that first-time BNPL users experience rapid increases in overdraft charges and credit card interest and fees, as compared to non-users. An instrumental variable exploiting consumers’ pre-BNPL shopping habits increases the credibility of BNPL having a causal negative effect on users’ financial wellbeing. Our results contribute to the academic literature by expanding our understanding of a major development in household finance, and indicate that regulators should take seriously the concern that BNPL could have significant negative welfare implications. (joint with Ed deHaan, Jungbae Kim, and Chenqi Zhu)

Read paper | View presentation slides

Moderator: Patrick Heck
Discussant: Cortnie Shupe

Breakout (15 minutes)

Is There Crowd-Out in Mortgage Refinance?

Presenting author: Ryan Goodstein (FDIC)

We examine whether supply-side capacity constraints contribute to the well documented “failure to refinance” among certain borrowers who would benefit financially from doing so. Using comprehensive loan-level data from the National Mortgage Database (NMDB), we show that, conditional on the potential financial benefits of refinancing and other observables, borrowers with low loan balances, low incomes, or low credit scores have substantially lower mortgage prepayment rates during refinance booms compared to periods of lower refinancing activity. In contrast, borrowers with high loan balances, high incomes, or high credit scores have higher prepayment rates when markets are operating at or near full capacity. These patterns hold after controlling for a rich set of observable characteristics and among borrowers that are likely able to qualify for a conventional refinance loan, indicating that some borrowers are crowded out from refinancing when capacity constraints bind. Overall our findings suggest that in addition to demand-side explanations for differences in refinancing highlighted in previous literature, supply-side factors also play an important role. (joint with Nick Frazier)

Read paper

Frictions in Mortgage Refinancing

Presenting author: Gaston Illanes (Northwestern University)

Households often fail to refinance mortgages, foregoing substantial reductions in interest payments. We implement a large-scale experiment on the mortgage borrowers in a Chilean bank to study whether information interventions affect refinancing behavior. We randomly assign borrowers to receive treatments that target distinct information frictions, and track their search and refinancing behavior over time. We find that the most effective intervention—giving information about gains from refinancing and details about how to refinance—increases search for refinancing offers by 20%, with significantly larger effects for those with the largest gains from refinancing. We develop and estimate an equilibrium model of refinancing to evaluate alternative policies that affect refinancing frictions, as well as its implications for market power and the passthrough of monetary policy. (Joint with Vivek Bhattacharya, José Ignacio Cuesta, Ana Maria Montoya, and Raimundo Undurraga)

Closing Costs, Refinancing, and Inefficiencies in the Mortgage Market

Presenting author: David Zhang (Rice University)

I use a structural model to quantify the cross-subsidization in the US mortgage market due to heterogeneous borrower refinancing tendencies. Actively refinancing borrowers gain up to 3% of their loan amount relative to non-refinancing borrowers in expectation. In equilibrium, the presence of borrowers with high refinancing inertia reduces mortgage interest rates particularly on lower upfront closing cost mortgages which have more valuable refinancing options. As a result, actively refinancing borrowers refinance excessively relative to a perfect information, no cross-subsidization benchmark, an effect that accounts for around 28% of all US refinancing and generates significant deadweight losses due to administrative resource costs. Policies that reduce disparities in refinancing behavior can increase efficiency in the market while also having attractive distributional properties.

Moderator: Judith Ricks
Discussant: David Lowe

Regulation and Market Power: Evidence from Manufactured Home Loans (Helen Banga)

Medical Collection Furnishing and Consumer Credit Outcomes (Alyssa Brown and Eric Wilson)

Measuring Consumer Credit Conditions (Claire Brennecke, Brian Bucks, Christa Gibbs, Samantha LeBuhn, Michelle Kambara, and Caroline Ratcliffe)

Consumer Savings App Strategies and Savings Outcomes (Caroline Ratcliffe, Jeremy Burke, Patrick Heck, Margaret Bolton, and Elizabeth Saunders)

Protecting Those Who Protect Us: Evidence of activated Guard and Reserve servicemembers’ usage of credit protections under the Servicemembers Civil Relief Act (Charles A. Goldman and Yael Katz)

Using the courts for private debt collection: How state garnishment laws affect civil judgments and access to credit (Scott Fulford and Éva Nagypál)

Doomscrolling of Consequence (Joseph Harvey and Linda Salisbury)

The Price of Financial Inclusion: Equilibrium Effects of Rural Banking Policy in India (Jonathan Hawkins-Pierot)

Same-sex Mortgage Applicants in the Home Mortgage Disclosure Act (HMDA) Data (Alice Jun)

Flood Risk and Mortgage Supply (Éva Nagypál)

Credit When You Need It

Presenting author: Ben Keys (The Wharton School of the University of Pennsylvania)

We estimate the causal effect of emergency credit provision on the household balance sheet. To do so, we link application data from the U.S. Federal Disaster Loan program, which provides loans to households that have uninsured damages from a federally-declared natural disaster, to a panel of credit records before and after the shock. We exploit discontinuous variation in loan approval rules, which led those with debt-to-income ratios below 40% to be differentially likely to be approved. Using an instrumented difference-in-differences research design, we find that credit provision at the time of a shock can significantly reduce the worst outcomes, reducing the likelihood of loan delinquency by 33% and the likelihood of bankruptcy by 2 percentage points. Credit provision in a time of crisis has real consumption effects in the form of additional car purchases even 3 years after loan receipt. Our findings suggest that well-timed liquidity provided to households in acute need can have substantial and persistent positive effects. (Joint with Ben Collier, Dan Hartley, and Xian Ng)

The Impact of Social Insurance on Household Debt

Presenting author: Sasha Indarte (The Wharton School of the University of Pennsylvania)

This paper investigates how the expansion of social insurance affects households’ accumulation of debt. Insurance can reduce reliance on debt by lessening the financial impact of adverse events like illness and job loss. But it can also weaken the motive to self-insure through savings, and households’ improved financial resilience can increase access to credit. Using data on 10 million borrowers and a quasi-experimental research design, we estimate the causal effect of expanded insurance on household debt, exploiting ZIP code-level heterogeneity in exposure to the staggered expansions of one of the largest US social insurance programs: Medicaid. We find that a one percentage point increase in a ZIP code’s Medicaid-eligible population increases credit card borrowing by 0.74%. Decomposing this effect in a model of household borrowing, we show that increased credit supply in response to households’ improved financial resilience fully accounts for this rise in borrowing and contributed 33% of the net welfare gains of expanding Medicaid. (Joint with Gideon Bornstein)

Read paper | View presentation slides

Pay-As-You-Go Insurance: Experimental Evidence on Consumer Demand and Behavior

Presenting author: Raymond Kluender (Harvard Business School)

Pay-as-you-go contracts reduce minimum purchase requirements which may increase market participation. We randomize the introduction and price(s) of a novel pay-as-you-go contract to the California auto insurance market where, despite a universal mandate, 17 percent of drivers are uninsured. The pay-as-you-go contract increases insurance take-up by 10.6 percentage points (87%) and days with insurance available by 4.5 days over the 3-month experiment (26%). Demand is price-sensitive and coverage increases are smaller at higher prices. The pay-as-you-go contract increases insurance coverage in part by relaxing liquidity requirements: purchase behavior for more than half of drivers is consistent with a cost of credit in excess of payday lending rates and 19 percent of enrolled drivers have a purchase rejected for insufficient funds. Insurance coverage converges between the traditional and pay-as-you-go contract over time. I discuss potential explanations and their implications for similar financial technologies (e.g., buy-now-pay-later, earned wage access) and the uninsured driver problem.

Read paper | View presentation slides

Moderator: Jason Dietrich
Discussant: Éva Nagypál