Research

December 3, 2024

Published Research

Using Administrative Data to Examine Telemedicine Usage Among Medicaid Beneficiaries During the COVID-19 Pandemic (w/ Emma Dean and Daniel Kaliski), Medical Care (July 2022). Published version;

A World Without Borders Revisited: The Impact of Online Sales Tax Collection on Shopping and Search, Journal of Economics & Management Strategy (Spring 2022). Published version; Working paper version

Credit Card Trends During the COVID-19 Pandemic, Federal Reserve Bank of Philadelphia Supervisory Research Forum Spotlight (2021 Q4). Published version;

Other Publications

Timing of Flood Insurance Payments (w/ John Orellana-Li)

Working Papers

Pricing Protection: Credit Scores, Disaster Risk, and Home Insurance Affordability (w/ Joshua Blonz and Joakim Weill)

Abstract: This paper leverages novel data on 15 million home insurance policies to understand how credit scores and natural disaster risks affect the price of home insurance. We find that individuals with subprime credit pay 30% more for home insurance than individuals with super-prime credit. These differences are not explained by property or contract-level characteristics, and likely reflect how insurers use credit score to price anticipated future claim filing behavior. Leveraging a house-level match with a proprietary disaster risk model, we find that the passthrough of expected annual disaster losses is close to one on average, higher than one for individuals with lower credit scores, and below one in high insurance-regulation states like California. We show that despite a passthrough rate for disaster risk close to one, disaster risks account for less than a quarter of premiums on average, and around a third in high-risk states like Florida and Louisiana. These findings reveal that at the policy-level, the disaster risk component of insurance prices is on average smaller than the discount given to people with high credit scores. Insurance prices often depend more on who lives in a home than on the disaster risk a home is exposed to.

Flood Risk Exposures and Mortgage-Backed Security Asset Performance and Risk Sharing (w/ Jacob Dice and David Rodziewicz)

Abstract: The distribution of risks for residential real estate, including flood risk, depends largely on how these risks are allocated across individual mortgages and within mortgage-backed securities (MBS). This paper is the first to document how flood risks relate not only to individual mortgage performance and underwriting, but also how flood risks correlate to MBS performance and structure. Across residential mortgages we find that defaults are concentrated among the most flood-prone properties and this risk is somewhat offset by larger down payments and slightly higher mortgage rates. Even when mortgages are combined into MBS’s, we show that average mortgage default within MBS’s increases with average flood risk and that higher flood risk is primarily offset by increased credit protection or subordination; a one unit increase in flood risk is associated with a 2.6 percent increase in subordination. Ultimately, our analysis suggests that flood risk is reflected in mortgage-level performance and pricing and is partially, but not fully, accounted for in MBS deal-level performance and structure.

California Wildfires, Property Damage, and Mortgage Repayment (w/ Siddhartha Biswas and David Zink)

Abstract: We find that 90-day delinquencies were 4 percentage points higher and prepayments were 16 percentage points higher for properties that were damaged by wildfires compared to properties 1 to 2 miles outside of the wildfire, which suggests higher risks to mortgage markets than found in previous studies. We find no significant changes in delinquency or prepayment for undamaged properties inside a wildfire boundary. Prepayments are not driven by increased sales or refinances, suggesting insurance claims drive prepayment. We provide evidence that underinsurance may force borrowers to prepay instead of rebuild.

Not Cashing In on Cashing Out: An Analysis of Low Cash-Out Refinance Rates (w/ Igor Livshits and Collin Wardius)

Abstract: Lowering a borrower’s interest rate is one of the most effective ways to reduce a borrower’s debt burden. Mortgage refinancing offers a chance to shift debt balances from high-interest loans into a low-interest mortgage through “cashing out” some of the home’s equity. Borrowers could reduce their monthly payments by up to 13 percent by folding a student loan with a 6 percent interest rate into a mortgage with a 3 percent interest rate. Using anonymized data on mortgage refinancing behavior, we find that over half of borrowers with high-interest loans and available home equity do not take advantage of their cash-out opportunities. Strikingly, this pattern is seen among borrowers who have already chosen to refinance their mortgage, thereby overcoming inertia, information frictions, and large fixed costs associated with the decision to refinance. Furthermore, even when the last remaining fixed cost (cash-out surcharge) is eliminated for student-loan borrowers by a policy change at Fannie Mae, we find that the presence of a student loan does not significantly affect borrowers’ propensity to cash out after these surcharges are eliminated.

Does Algorithmic Risk Assessment Affect Physician Prescribing? Understanding Aggregate Versus Micro-Level Impacts (w/ Emma Dean and Daniel Kaliski)

Abstract: Multiple states use algorithmic risk scores to combat the opioid epidemic, but their overall impact remains unclear. Using national and Florida administrative data, we find the null effects of these risk scores’ adoption in the aggregate masks heterogeneous effects across patient groups. Our findings are consistent with a simple theoretical model where physicians rely more strongly on external signals of risk for new patients. Furthermore, physicians increased prescribing for opioid-naïve patients while decreasing prescribing for patients with a history of safe opioid use, possibly increasing overdose risk and reducing effective pain management.

Less is More Expensive: Bulk Buying and Cognitive Costs

Abstract: Increasing the salience of unit prices can reduce consumption inequality. Using Nielsen data, we show that low-income households forgo savings by not buying in bulk. We estimate that low-income households could save 5% on groceries if they bought in bulk like high-income households. Using novel data on state-level unit-price regulations, we find that cognitive costs discourage low-income households from bulk buying. Mandating unit price display, a policy adopted by nine states, may reduce cognitive costs, increase the salience of unit prices, and close the “bulk buying gap” by 26%.

Research In Progress

Measuring Flood Insurance Noncompliance (w/ Solomon Tarlin and David Wylie)

Made from Scratch: SNAP and Lottery Sales (in progress) with Jason Sockin