The Costs of Hedging Disaster Risk and Home Prices in the Face of Climate Change

with Ammon Lam and Ryan Lewis (Link)

Climate change threatens to increase the damages of natural disasters and the cost of insuring against them. We study how the cost of hedging disaster risk changes home prices by using a 2012 law that mandated flood insurance premium increases for properties discontinuously around flood zone boundaries and based on the timing of construction. With a triple-difference design, we find that homes that experience the largest increase in premiums experience the largest decline in home values. Evidence suggests that the effect is partly driven by increases in perceived risks triggered by increases in premiums. While the effect on home prices is unrelated to current hazard risk, the estimate is three times larger for homes that are exposed to long-term sea level rise than those not exposed, suggesting that insurance pricing can accelerate the incorporation of climate risk in asset markets. Buyers of these homes also reduce the probability of taking out mortgages, as insurance is required for mortgages.

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 How Do Health Insurance Costs Affect Firm Labor Composition and Technology Investment?

with Janet Gao, Lawrence Schmidt, Cristina Tello-Trillo (Link)

Employer-sponsored health insurance is a significant component of labor costs. We examine the causal effect of health insurance premiums on firms’ employment, both in terms of quantity and composition, and their technology investment decisions. To address endogeneity concerns, we instrument for insurance premiums using idiosyncratic variation in insurers' recent losses, which is plausibly exogenous to their customers who are employers. Using Census microdata, we show that following an increase in premiums, firms reduce employment. Relative to higher-income coworkers, lower-income workers see a larger increase in their likelihood of being separated from their jobs and becoming unemployed. Firms also invest more in information technology, potentially to substitute labor.

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 How Does Investor Demand Affect CLO Creation, Firm Borrowing, and Investment?

with Abhishek Bhardwaj and Saptarshi Mukherjee 

(Link to Preliminary Version, Major Extension in Progress)

The collateralized loan obligation (CLO) market has grown drastically, with the amount outstanding rising from $100 Billion in 2005 to $650 Billion in 2020. We examine the effect of investors' demand on new CLO deal formation as well as on corporate borrowing and investment. We do so by using detailed data from insurance companies, which are the largest group of CLO investors. We present three main findings. First, when insurers experience favorable operating cash flows, they are more likely to invest in CLO deals, especially deals by CLO managers whom they previously invested with. Second, when CLO managers are more exposed to insurers' favorable cash flows through past relationships, they are more likely to launch new CLO deals. Third, among borrowing firms, those more affected (through CLO managers) are more likely to receive new loans, as well as increase leverage and investment. Our results imply that investor demand affects CLO deal formation, as well as corporate borrowing and capital structure decisions. We also present evidence that insurers' aggregate demand for CLOs, proxied by their cash flows, is important for the growth of the CLO market segment that is exposed to insurers through past relationships.

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Measuring the Climate Risk Exposure of Insurers

with Hyeyoon Jung, Robert Engle, and Xuran Zeng (Link)

Insurance companies can be exposed to climate-related physical risk through their operations and to transition risk through their $12 trillion of financial asset holdings. We assess the climate risk exposure of property and casualty (P&C) and life insurance companies in the U.S. We construct a novel physical risk factor by forming a portfolio of P&C insurers’ stocks, with each insurer’s weight reflecting their operational exposure to states associated with high physical climate risk. We then estimate the dynamic physical climate beta, representing the stock return sensitivity of each insurer to the physical risk factor. In addition, using the climate beta estimates introduced by Jung et al. (2021), we calculate the expected capital shortfall of insurers under various climate stress scenarios. We validate our approach by utilizing granular data on insurers’ asset holdings and state-level operational exposure. Our findings indicate a positive association between larger exposures to risky states and higher holdings of brown assets with higher sensitivity to physical and transition risk, respectively.