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Large losses and equilibrium in insurance markets

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Abstract

We show that if losses are larger than wealth, then individuals with the option of declaring bankruptcy will not insure if the loss probability is above a threshold. In an insurance market with adverse selection, if the high risks’ loss probability is above the threshold, then no trade occurs at the Rothschild–Stiglitz equilibrium. Active trade in insurance requires cross-subsidization. When a subset of individuals with significant costs of bankruptcy and default is included in the market, then the equilibrium outcome always involves positive levels of insurance coverage for some individuals, but the parameters of the model determine whether all types receive coverage, or whether null contracts are received by both high and low risks with no bankruptcy costs or just the low risks from that group.

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Notes

  1. According to the American Automobile Association (2011), the average cost of an auto crash fatality was $6 million and the average cost of an injury was $126 thousand in 2009.

  2. Peter (2016) assumes losses are less than wealth and analyzes the threshold premium-loading factor above which individuals do not insure.

  3. We thank Nathaniel Hendren for this insight.

  4. Insurance Services Office’s (ISO’s) Policy CG 00 01 04 13, Coverage A—Bodily Injury and Property Damage Liability of the commercial general liability (CGL) policy. https://www.insurancejournal.com/blogs/academy-journal/2016/02/29/399923.htm.

  5. Homeowners HO-3, HO 00 03 10 00, Personal Liability Coverage E.

  6. In Posey and Thistle (2017), the results of the current paper are employed in a health insurance model for individuals of varying pain tolerance to analyze a wide range of policy options for the use of genetic information.

  7. \(N^{\prime}\) (0) is negative (positive) if [u(w) – u(b)]/l, the slope of the line connecting the points (wl, u(b)) and (w, u(w)), is less (greater) than \(u^{\prime}\) (w), the slope of the tangent line at (w, u(w)). For given preferences there is always a loss large enough that the slope of the line is less than the slope of the tangent, so that \(N^{\prime}\) (0) is negative for larger loss amounts and positive for smaller loss amounts.

  8. It is assumed that when individuals are indifferent between contracts, they will choose the one with more coverage, but when they are indifferent between buying and not buying insurance, they will choose to go uninsured.

  9. Here we make the assumption used in Rothschild and Stiglitz (1976) that insurers can offer only a single contract. Menus of contracts are allowed in subsequent sections.

  10. For pH < 1, condition (4) implies u′(w) ≥ u′(wl), which contradicts the assumption of risk aversion.

  11. See Hendren’s (2013) Theorem 1 and the subsequent discussion.

  12. Point E0, which is directly north of the standard no insurance endowment and represents the state of the world where bankruptcy is declared, is analogous to Point A′ in Fig. 3 of Strohmenger and Wambach (2000) which represents the state of the world where no treatment is obtained and no insurance is purchased.

  13. The result in Proposition 2 can be extended to more than two risk types. Suppose there are n types, with 0 < p1 < p2 < ··· < pn < 1 and that pn > p*. Then applying the proof of Proposition 2 seriatim, the equilibrium contract for all types is the null contract.

  14. A locally competitive equilibrium is a set of contracts such that contracts in the set earn non-negative profits and no contract within a neighborhood of an equilibrium contract makes positive profits. Sandroni and Squintani (2007) show that, in markets with adverse selection, a locally competitive equilibrium always exists, is unique, and coincides with the Rothschild–Stiglitz equilibrium. Under the assumptions of Proposition 2, the locally competitive equilibrium is always the no trade equilibrium.

  15. This is analogous to a two-part tariff, where the marginal price determines the quantity of the good sold and the fixed fee extracts the consumer surplus (see, e.g., Oi 1971 or Tirole 1988, pp. 143–148).

  16. The critical value \(\lambda^{\prime}\), increases as pH gets closer to pL.

  17. This lower bound prevents solutions to the maximization problem that allocate all of the resources to the low risks, that is, the high risk cannot subsidize the low risks. This constraint also ensures that the solution to the maximization problem is a second best allocation.

  18. Note that in the absence of the individual rationality constraints associated with bankruptcy protection, the cross-subsidizing locus is also the feasible contract curve, but in our case, the contracts along the CLS that do not satisfy the individual rationality constraints are not feasible.

  19. Although wealth cannot be negative, \(w_{ij} - D_{ij}\) can. Since \(u\left( \cdot \right)\) is not restricted to a non-negative domain, the optimization problems and figures used for the analysis of type 0 individuals also apply for type 1 individuals with a different individual rationality constraint. Note that, \(w_{ij} - D_{ij}\) is equivalent to net worth, and equals wealth when \(D_{ij} = 0\)

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Acknowledgements

We thank Keith Crocker, Nathan Hendren, Casey Rothschild and Art Snow for helpful comments. Thistle’s research was supported by the Nevada Insurance Education Foundation.

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Correspondence to Lisa L. Posey.

Appendix: Proof of Proposition 3

Appendix: Proof of Proposition 3

The Lagrangian for the maximization problem is

$$\begin{aligned} {\mathcal{L}} =& U_{L} \left( {c_{L} } \right) \, + \mu_{H} \left[ {U_{H} \left( {c_{H} } \right) \, {-}U_{H} \left( {c_{L} } \right)} \right] \, + \mu_{L} \left[ {U_{L} \left( {c_{L} } \right) \, {-}U_{L} \left( {c_{H} } \right)} \right] \\ & + \gamma \{ \lambda \left[ {w{-}p_{H} l{-} \, \left( {1 \, {-}p_{H} } \right)w_{HG} {-}p_{H} w_{HB} } \right]I_{H} \\ & + \left( {1 \, {-}\lambda } \right)\left[ {w{-}p_{L} l{-} \, \left( {1 \, {-}p_{L} } \right)w_{LG} } \right) \, - p_{L} w_{LB} )]I_{L} \} \\ & + \delta \left[ {U_{H} \left( {c_{H} } \right) \, {-}U_{H} \left( {c_{H}^{*} } \right)} \right], \\ \end{aligned}$$

where μH, μL, γ, and δ are the Lagrange multipliers. The first-order conditions are

$$\partial {\mathcal{L}}/\partial w_{LG} = \, \left( {1 \, + \mu_{L} } \right)\partial U_{L} \left( {c_{L} } \right)/\partial w_{LG} - \mu_{H} \partial U_{H} \left( {c_{L} } \right)/\partial w_{LG} {-}\gamma \left( {1 \, {-}\lambda } \right)\left( {1 \, {-}p_{L} } \right) \, = \, 0$$
(6)
$$\partial {\mathcal{L}}/\partial w_{LB} = \, \left( {1 \, + \mu_{L} } \right)\partial U_{L} \left( {c_{L} } \right)/\partial w_{LB} - \mu_{H} \partial U_{H} \left( {c_{L} } \right)/\partial w_{LB} {-}\gamma \left( {1 \, {-}\lambda } \right)p_{L} = \, 0$$
(7)
$$\partial {\mathcal{L}}/\partial w_{HG} = \, \left( {\delta + \mu_{H} } \right)\partial U_{H} \left( {c_{H} } \right)/\partial w_{HG} - \mu_{L} \partial U_{L} \left( {c_{H} } \right)/\partial {\text{w}}_{HG} {-}\gamma \lambda \left( { 1 { }{-}p_{H} } \right) \, = \, 0$$
(8)
$$\partial {\mathcal{L}}/\partial w_{HB} = \, \left( {\delta + \mu_{H} } \right)\partial U_{H} \left( {c_{H} } \right)/\partial w_{HB} - \mu_{L} \partial U_{L} \left( {c_{H} } \right)/\partial w_{HB} {-}\gamma \lambda p_{L} ) \, = \, 0,$$
(9)

along with the complementary slackness conditions.

  1. A.

    (i) The resource constraint is binding: If at least one type buys insurance, then Ii =1 for some i, and non-satiation implies the resource constraint is binding. If neither type buys insurance, then IH = IL = 0 and the resource constraint becomes 0 = 0. (ii) Either both IR constraints are binding or both IR constraints are slack: We need to show (a) IRH binding implies IRL binding, (b) IRL binding implies IRH binding, (c) IRH slack implies IRL slack, and (d) IRL slack implies IRH slack. Observe that (a) and (d) are equivalent and (b) and (c) are equivalent. We first prove (b). Assume IRL is binding. Suppose, by way of contradiction, that IRH is slack, UH(cH) > UH(\(E_{0}\)). Since the Hs purchase a policy with positive coverage, either pH < p* or the Hs are subsidized. The first possibility is ruled out by hypothesis. Since the Ls do not purchase insurance, the Hs cannot be subsidized without violating the resource constraint. We now prove (d), that if IRL is slack then IRH is slack. If IRL is slack, then UL(cL) > UL(\(E_{0} )\). Assume, by way of contradiction, the IRH is binding, UH(cH) = UH(\(E_{0}\)). Since cL must break even, it lies on the type L fair odds line above (w, b). But this implies UH(cL) > UH(\(E_{0}\)), which is the desired contradiction.

  2. B.

    If both IR constraints are slack, then (i) The SSH constraint must be binding: Let (cH, cL) be a proposed solution to the maximization problem such that the resource constraint is binding. Suppose that SSH is slack, UH(cH) > UH(cL). Let cL = (wLG, wLB) and cL′ = (wLGε1, wLB + ε2), where ε2 = (1 − pL)/pL]ε1, ε1 > 0. If ε1 is small enough then SSH is still slack. But cL′ is a mean preserving contraction relative to cL, so UL(cL′) > UL(cL). So (cH, cL) cannot be a solution to the maximization problem. (ii) The high risks must be fully insured: If both self-selection constraints are binding, the equilibrium must be at a pooled policy cH = cL. Suppose the pooled policy offers less than full insurance. Then both types are better off at cL′, so (cH, cL) cannot be a solution to the maximization problem. Any pooled equilibrium must be at the population pooled policy cP. Now suppose SSL is slack and SSH is binding, UH(cH) = UH(cL), and cH offers less than full insurance. Let cH′ be a mean preserving contraction from cH. Then there is a cL′ such that SSH is binding, UH(cH′) = UH(cL′). Both types are better off at (cH′, cL′), so (cH, cL) cannot be a solution to the maximization problem.

    (iii) Equation (5) in the text gives the slope of the CSL: If both self-selection constraints are slack, then the expected utility of both types can be increased. So at least one self-selection constraint must be binding. From (8) and (9), we have

    $$\frac{{\left( {1 - p_{H} } \right)u^{\prime}(w_{HG)} }}{{p_{H} u^{\prime}\left( {w_{HB} } \right)}} = \frac{{\mu_{L} \left( {1 - p_{L} } \right)u^{\prime}\left( {w_{HG} } \right) + \gamma \lambda \left( {1 - p_{H} } \right)}}{{\mu_{L} p_{L} u^{\prime}\left( {w_{HB} } \right) + \gamma \lambda p_{H} }}.$$
    (10)

    Evaluated at any full insurance contract (wH, wH), this becomes

    $$\frac{{1 - p_{H} }}{{p_{H} }} = \frac{{\mu_{L} \left( {1 - p_{L} } \right)u^{\prime}\left( {w_{H} } \right) + \gamma \lambda \left( {1 - p_{H} } \right)}}{{\mu_{L} p_{L} u^{\prime}\left( {w_{H} } \right) + \gamma \lambda p_{H} }}.$$
    (11)

    This can hold as an equality if and only if μL = 0. If both self-selection constraints are binding, then both types must be at the pooled contract cP. Then high-risk utility is UH(cP). From (6) and (7), we have

    $$\frac{{\left( {1 - p_{L} } \right)u^{\prime}(w_{LG)} }}{{p_{L} u^{\prime}\left( {w_{LB} } \right)}} = \frac{{\mu_{H} \left( {1 - p_{H} } \right)u^{\prime}\left( {w_{LG} } \right) + \gamma \left( {1 - \lambda } \right)\left( {1 - p_{L} } \right)}}{{\mu_{H} p_{H} u^{\prime}\left( {w_{LB} } \right) + \gamma \left( {1 - \lambda } \right)p_{L} }}.$$
    (12)

    Evaluated at cP, this becomes

    $$\frac{{1 - p_{L} }}{{p_{L} }} = \frac{{\mu_{H} \left( {1 - p_{H} } \right)u^{\prime}\left( {w_{H} } \right) + \gamma \left( {1 - \lambda } \right)\left( {1 - p_{L} } \right)}}{{\mu_{H} p_{H} u^{\prime}\left( {w_{H} } \right) + \gamma \left( {1 - \lambda } \right)p_{L} }}.$$
    (13)

    This holds as an equality if and only if μH = 0. Then (11) and (13) imply that μH = μL = 0 at cP. If UH(cH) < UH(cP), then we have μL = 0, μH > 0, so that the low-risk self-selection constraint is slack and the high-risk self-selection constraint is binding.

    Using (8) to eliminate the Lagrangian multiplier γ in (12) yields

    $$\frac{{\left( {1 - p_{L} } \right)u'\left( {w_{LG} } \right)}}{{p_{L} u'\left( {w_{LB} } \right)}} = \frac{{\mu_{H} \left( {1 - p_{H} } \right)u^{\prime}\left( {w_{LG} } \right) + [\lambda \left( {1 - p_{H} } \right]^{ - 1} \left( {\mu_{H} + \delta } \right)\left( {1 - \lambda } \right)\left( {1 - p_{L} } \right)u'\left( {w_{H} } \right)}}{{\mu_{H} p_{H} u^{\prime}\left( {w_{LB} } \right) + [\lambda \left( {1 - p_{H} } \right]^{ - 1} \left( {\mu_{H} + \delta } \right)\left( {1 - \lambda } \right)p_{L} u'\left( {w_{H} } \right)}}.$$
    (14)

Rearranging (14) yields (5) in the text.

  1. C.

    If both IR constraints are binding, then (i) Both SS constraints are binding and (ii) both types obtain the null contract: This is Proposition 2. Observe that the IR and SS constraints coincide, so the SS constraints are binding and the null contract is unique.

  2. D.

    The solution is unique: Suppose that there are two distinct solutions to the constrained maximization problem, \((\tilde{c}_{H} ,\tilde{c}_{L}\)) and \(\left( {\hat{c}_{H} , \hat{c}_{L} } \right).\) Then we have UL(\(\tilde{c}_{L}\)) = UL(\(\tilde{c}_{L}\)). Since the CSL is downward sloping, one of the low-risk contracts, say,\(\tilde{c}_{L} ,\) must have more coverage than the other low-risk contract. But then the tax on the low risks must be higher, and, since net transfers must balance, the subsidy to the high risks must also be higher. This implies \(\tilde{w}_{H}\) > \(\hat{w}_{H}\) making the high risks better off. Then the solution (\(\tilde{c}_{H} ,\tilde{c}_{L}\)) Pareto dominates \(\left( {\hat{c}_{H} , \hat{c}_{L} } \right)\). Therefore, \((\tilde{c}_{H} ,\tilde{c}_{L}\)) is the unique solution.

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Posey, L.L., Thistle, P.D. Large losses and equilibrium in insurance markets. Geneva Risk Insur Rev 44, 222–244 (2019). https://doi.org/10.1057/s10713-019-00038-8

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