This paper examines a classic rationale for voluntary take-up over automatic enrollment in transfer programs: take-up may be advantageously “self-targeted” on characteristics that are infeasible to use as eligibility criteria. Using a correlation test, we find self-targeting in eight U.S. transfers: on average, recipients have lower consumption and lifetime incomes than similar eligible nonrecipients. Self-targeting focuses redistribution toward the lifetime poor and also increases transfers' within-lifetime insurance value. With a new sufficient-statistics result, we value the social benefits of self-targeting at approximately nine cents per transfer dollar, offsetting the social costs of take-up in some programs.

This paper studies imperfectly-perceived private information in insurance markets when contracts endogenously respond. Equilibrium contracts, pooling, and welfare depend on the joint distribution of risk and misperception. In the Health and Retirement Study (HRS), I show that misperceptions typically co-vary with (medical, long-term care, disability, and mortality) risk type: high types under-perceive their risk, low types over-perceive. I develop a general model and algorithm to estimate the equilibrium contracts, pooling, and welfare impact of misperceptions that is applicable in many settings. I offer suggestive evidence from US annuity markets that contracts are distorted due to misperceptions, with welfare likely increasing.

We study Colonel Blotto games with sequential battles and a majoritarian objective. For a large class of contest success functions, the equilibrium is unique and characterized by an even split: each battle that is reached before one of the players wins a majority of battles is allocated the same amount of resources from the player's overall budget. As a consequence, a player's chance of winning any particular battle is independent of the battlefield and of the number of victories and losses the player has accumulated in prior battles. This result is in stark contrast to equilibrium behavior in sequential contests that do not involve either fixed budgets or a majoritarian objective. We also consider the equilibrium choice of an overall budget.

Intensifying climate change makes protection against natural disaster risk — either through ex ante insurance or ex post aid — a first-order public policy issue. Flood risk protection in the U.S. traditionally featured ex post aid through FEMA and heavily subsidized insurance through the National Flood Insurance Program (NFIP). In an effort to correct subsidy-induced overbuilding and under-mitigation in flood-prone areas, the NFIP recently moved to actuarially fair insurance premiums. But this change has two unintended consequences: a fiscal spillover onto FEMA disaster aid as insurance coverage declines in flood-prone areas, and household exposure to uninsurable reclassification risk from uncertain climate projections. We develop a model of optimal flood insurance that incorporates the static and dynamic tradeoffs of subsidizing premiums. We then use a variety of identification strategies and data to estimate the five key parameters needed to implement this model. We find that the fiscal spillover and reclassification risk protection benefits significantly outweigh the moral hazard costs, and that the optimal subsidy to flood insurance is 46%, comparable to the level of subsidization before the recent reform.

Distinct risks are typically insured separately. A single “aggregate” contract that pays more when many shocks occur simultaneously, but less when positive shocks offset negative shocks, is utility-increasing absent moral hazard. However, an aggregate contract discourages diversification, leading to a novel insurance-incentive trade-off. We study the US Federal Crop Insurance Program (FCIP), where farmers can choose the “scope” of their policy — whether to insure each field separately, or all fields of the crop as an aggregate unit. Starting in 2009, the FCIP introduced a large subsidy increase for aggregate insurance. We show that farms that moved to aggregate insurance reduced crop diversity and irrigation, farmed less and conserved more land, and insured price risk — all reducing the diversification of their risks. This increased the variability of farm yield by 14%, raising the fiscal cost of aggregate insurance by about $1.5 billion per year. We derive and estimate a formula for the optimal contract scope. We find that an aggregate policy is never welfare maximizing, but that the optimal policy lies partway between separate and aggregate. More generally, we discuss scope's widespread relevance in insurance design.

Natural-catastrophe risk has emerged as a major driver of insurance unaffordability and unavailability. I study a novel Australian policy response: government-provided, mandatory, cost-neutral reinsurance for cyclone damage in home insurance. I find that public reinsurance reduces home insurance premiums by 23 percent, and increases the probability of insurance being offered by 12 percent. Theoretically and empirically, I show that the cost of holding capital against correlated or ambiguous risks drives private insurance prices up, and consequently that the fiscally-balanced public reinsurance decreases prices by substituting in cheaper public capital that doesn't require a correlation, ambiguity, or risk premium.

Every insurance contract bundles risks, and explicit bundling discounts are common. I show theoretically that bundling arises in a competitive market whenever correlation between risk types enables insurer “cream-skimming”: willingness-to-pay for insurance against one risk must be negatively correlated with expected costs from the other risk. I analyze long-term care insurance, in which both-spouse bundles are discounted by 20–35%. I show that cream-skimming incentives are sufficient to explain these discounts, and rule out standard economies-of-scale. Counterfactually, banning bundling would raise welfare by 5% by correcting separate-market unraveling, while mandatory family bundling would reduce welfare by 5% by exacerbating advantageous selection.

Estimates of the expected present discounted value (EPDV) of future payouts on both immediate and deferred annuities are sensitive to the discount rate used to value future payment streams and assumptions about future mortality rates. This paper illustrates this with respect to annuities that were available in the US retail insurance market in 2020. The spread between the interest rates on Treasury and corporate bonds was high by historical standards as a share of the riskless Treasury yield during much of 2020, making the choice of discount rate more consequential than in the past. The EPDV estimates also depend on whether the rapid but since-attenuated decline in US old-age mortality rates during the 1990s and early 2000s is extrapolated to future decades. The “money's worth” is the EPDV divided by the annuity's purchase price. Our central estimates, using discount rates drawn from the corporate BBB yield curve and future mortality rates that combine a Society of Actuaries individual annuitant mortality table with projections of future mortality improvements from the Social Security Administration, suggest money's worth values for annuities offered to 65-year-old men and women of about 92 cents per premium dollar. Recent Department of Labor rulemaking requires defined contribution plan sponsors to provide participants with estimates of the annuity income stream that their plan balance could purchase. These estimates, like EPDVs, are also sensitive to both prospective rate of return and mortality rate assumptions.

As climate change intensifies weather-related risks, agricultural losses become more correlated across space, increasing the importance of well-designed crop insurance. A core design choice in the Federal Crop Insurance Program (FCIP) is unit structure: farmers can insure fields separately or aggregate them into a single policy. Aggregate policies are discounted because aggregation mechanically reduces expected payouts when yields are imperfectly correlated. But the current formula does not account for the endogeneity of correlation: farmers with aggregate policies reduce crop diversification, raising correlation and eroding the actuarial basis for the discount. We show how diversification could be priced directly. Focusing on wheat, we recommend using two observable variables for pricing: the mixture of winter versus spring varieties and the number of fields planted. Using county-level claims data, we estimate the relationship between wheat diversification and within-farm yield correlation, then use simulations calibrated to FCIP contracts to characterize how correlation affects the gap between aggregate and separate payouts. We show that current pricing misses economically meaningful variation in expected payouts: for a four-field farm, moving from a 50/50 winter–spring mixture to full concentration in one variety increases expected aggregate payouts from 65 percent to 81 percent of separate payouts — a 16 percentage point unpriced swing. Incorporating these factors would allow farmers to internalize the costs of their diversification decisions, reducing moral hazard and improving the program's fiscal performance.

Insurance markets globally are buckling under the pressure of increasingly severe natural catastrophes. Direct public provision of insurance—the traditional policy response—has often failed to address the underlying market frictions and in many cases has accentuated them. A novel and increasingly popular alternative is public reinsurance: government-backed protection for insurers against catastrophe tail risk, rather than direct coverage of households. I provide the first comprehensive survey of public reinsurance programs around the world, cataloguing their design along key dimensions including pricing, participation rules, mitigation incentives, risk coverage, payment triggers, and shortfall financing. Drawing on evidence from programs spanning flood, earthquake, hurricane, and multi-peril catastrophe risk across dozens of countries, I evaluate the advantages and disadvantages of each design choice. I conclude with lessons for the design of a potential U.S. public catastrophe reinsurer.