Adult Polycystic Kidney Disease and Critical Illness Insurance

Abstract

Adult polycystic kidney disease (APKD) is a single-gene autosomal dominant genetic disorder leading to end-stage renal disease (ESRD, meaning kidney failure). It is associated with mutations in at least two genes, APKD1 and APKD2, but diagnosis is mostly by ultrasonography. We propose a model for critical illness (CI) insurance and estimate rates of onset of ESRD from APKD using two studies. Other events leading to claims under CI policies are included in the model, which we use to study (a) extra premiums under CI policies if the presence of an APKD mutation is known, and (b) the possible costs arising from adverse selection if this information is unavailable to insurers. The extra premiums are typically very high, but because APKD is rare, the possible cost of adverse selection is low. However, APKD is just one of a significant number of single-gene disorders, and this benign conclusion cannot be assumed to apply to all genetic disorders taken together. Moreover, ignoring known genetic risks in underwriting sets a precedent that could have unintended consequences for the underwriting of nongenetic risks of similar magnitude.     

The Genetics of Breast and Ovarian Cancer III: A new model of family history with insurance applications

Insurers’ access to genetic test results is often restricted and the only genetic information that might be collected during underwriting in some countries is family history. Previous studies have included family history in a simple way but only for diseases which have no cause other than gene mutations, because then the event ‘affected parent’ contributes all possible information short of a genetic test result. We construct a model of breast cancer (BC) and ovarian cancer (OC) — common diseases with rare genetic variants — in which the development of a family history is represented explicitly as a transition between states, hence as part of the applicant's own life history. This allows the impact of a moratorium to be modelled. We then apply this family history model to life insurance in a semi-Markov framework and to critical illness (CI) insurance in a Markov framework to: (a) estimate premium ratings depending on genotype or family history; and (b) model the potential cost of adverse selection.     

Adverse Selection in Term Life Insurance Purchasing due to the BRCA1/2 Genetic Test and Elastic Demand

Consumer groups fear that the use of genetic testing information in insurance underwriting might lead to the creation of an underclass of individuals who cannot obtain insurance; thus, these groups want to ban insurance companies from accessing genetic test results. Insurers contend that such a ban might lead to adverse selection that could threaten their financial solvency. To investigate the potential effect of adverse selection in a term life insurance market, a discrete‐time, discrete‐state, Markov chain is used to track the evolution of twelve closed cohorts of women, differentiated by family history of breast and ovarian cancer and age at issue of a 20‐year annually renewable term life insurance policy. The insurance demand behavior of these women is tracked, incorporating elastic demand for insurance. During the 20‐year period, women may get tested for BRCA1/2 mutations. Each year, the insurer calculates the expected premiums and expected future benefit payouts which determine the following year's premium schedule. At the end of each policy year, women can change their life insurance benefit, influenced by their testing status and premium changes. Adverse selection could result from (i) differentiated benefits following test results; (ii) differentiated lapse rates according to test results; and (iii) differentiated reactions to price increases. It is concluded that with realistic estimates of behavioral parameters, adverse selection could be a manageable problem for insurers.     

Welfare Effects of Banning Genetic Information in the Life Insurance Market: The Case of BRCA1/2 Genes

We investigate whether regulations that ban insurance companies from access to individuals' genetic tests are likely to lead to substantial adverse selection costs for the specific example of the so‐called breast cancer (BRCA1/2) genes. Using a data set including economic, demographic, and relevant family background information to simulate the market for 10‐year term life insurance, we find generally only modest adverse selection costs associated with such a regulatory ban. However, for family background groups that are at high risk for carrying one of these genes, the efficiency cost of adverse selection may be significant should the test become widely adopted.     

Pricing Term Insurance in the Presence of a Family History of Breast or Ovarian Cancer

Abstract

We estimate the increased mortality and term life insurance costs for women who have a family history of breast or ovarian cancer. Using data from the medical literature on age-specific and family history-specific incidence rates, we develop double-decrement models to evaluate the actuarial impact of breast cancer and ovarian cancer in the family. We also calculate the increased mortality and term insurance costs for women who test positive for the BRCA1 or BRCA2 gene mutation. We find that the type of affected relative and her age at onset of the disease are key underwriting factors. We find substantial mortality increases (up to 100%) for women with two relatives with cancer and women with a first-degree relative who developed cancer at an early age. Mortality increases for women with the BRCA gene mutation reach 150%. While some females with a family history of cancer can be accepted at standard rates, others may need to be quoted substandard rates, depending on the underwriting policy of the company. Females with the gene mutation can possibly be accepted at a rate that incorporates a severe mortality surcharge.     

Use of a Markov Model to Estimate Long-Term Insured Lives’ Mortality Risk Associated With BRCA1 and BRCA2 Gene Mutations

Abstract

There is uncertainty regarding the degree of insurance risk associated with BRCA1/2, the gene mutations associated with breast cancer. Most reports to date have been based on high-risk populations selected from families with multiple and/or early-onset cancers; more favorable data have been reported in studies without this selection bias.

This paper discusses use of a Markov model to estimate mortality risk associated with BRCA1/2 gene mutations in female life insurance applicants. The goal is to derive a range of risk estimates based on different assumptions of breast and ovarian cancer incidence. A particular strength of the model is that transition probabilities after cancer diagnosis vary with age and cancer stage, as do excess hazard rates.

Data calculated by the model indicate that no single mortality curve characterizes risk for all life insurance applicants with a BRCA1/2 mutation. Rather, mortality risk depends on breast and ovarian cancer incidence rates and subsequent mortality rates, and on the method used to deal with competing breast and ovarian cancer incidence and mortality rates. Further refinement of risk estimates will depend on better incidence data and on resolution of complex statistical problems, such as informative censoring.

Widespread use of genetic information by insurance consumers could have important economic implications. For companies that sell individually underwritten products, profitability might decrease. Consumers might find higher prices and reduced availability, with a corresponding decrease in quantity of insurance purchased. Insurance and consumer ramifications would vary by cover, with living-benefit products, such as critical-illness insurance, most adversely affected. Societal choices are limited. Given assumptions in the cited scenario, it is likely premiums would rise and quantity of insurance purchased would decrease even with no change in existing social policy; attempted legal or regulatory remedies would further accentuate price increases and reductions in quantity purchased.     

Huntington's disease,critical illness insurance and life insurance

We describe briefly a model of Huntington's disease (HD), a highly penetrant, dominantly inherited, fatal neurological disorder. Although it is a single-gene disorder, mutations are variable in their effects, depending on the number of times that the CAG trinucleotide is repeated in a certain region of the HD gene. The model covers: (a) rates of onset, depending on CAG repeat length as well as age; (b) post-onset rates of mortality; and (c) the distribution of CAG repeat lengths in the population. Using these, we study the critical illness and life insurance markets. We calculate premiums based on genetic test results that disclose the CAG repeat length, or more simply on a family history of HD. These vary widely with age and policy term; some are exceptionally high, but in a large number of cases cover could be offered within normal underwriting limits. We then consider the possible costs of adverse selection, in terms of increased premiums, under various possible moratoria on the use of genetic information, including family history. These are uniformly very small, because of the rarity of HD, but do show that the costs would be much larger in relative terms if family history could not be used in underwriting. We point out some difficulties involved in applying a moratorium that recognises simply a dichotomy between ‘carriers’ and ‘non-carriers’ of any mutation in a gene when these mutations are, in fact, very variable in their effects. These complexities suggest that restrictions on the disclosure, rather than on the use, of genetic information, if it became established as a principle, could deprive insurers of information needed for risk management even if not used in underwriting.     

Insurance and economic policy uncertainty

Just as the world has witnessed the increased importance of the insurance sector over the past few decades, it has also witnessed a sharp rise in risks and uncertainties. Surprisingly, studies analyzing the relationship between economic policy uncertainty and the insurance sector are almost non-existent. Another major limitation of insurance literature is the choice of methodology. Most studies on the insurance sector do not take into consideration issues of heterogeneity and cross-sectional dependence, and are therefore subject to errors. To address the identified gaps, this research investigates the impact of economic policy uncertainty on insurance premiums in a panel of 15 countries over the period 1998–2016 by employing heterogeneous panel estimation techniques with cross-sectional dependence. The Durbin-Hausman cointegration tests of Westerlund (2008) confirm that a long-run relationship exists between the variables. Findings from the error correction based panel estimations show that the insurance sector is not immune to the effects of economic policy uncertainty. Economic policy uncertainty raises insurance premiums both in the short and long run, although the long-run impact is greater than the short-run impact. In addition, economic policy uncertainty exerts a bigger influence on non-life insurance premium than on life insurance premium, indicating that the economic risks covered by non-life insurance are more sensitive to uncertainty than the mortality and longevity risks covered by life insurance. Our findings further show that national income, education, population, financial development and institutional quality all raise insurance premiums, while inflation lowers insurance premiums.     

寿险公司股权结构对经营绩效的影响——基于经理人代理成本视角

基于2012—2020年我国寿险公司的面板数据，实证检验股权结构对绩效的影响并探究其作用机制。结果表明：股权集中与绩效显著负相关，股权制衡与绩效显著正相关。机制检验发现，股权集中通过增加经理人代理成本削减绩效，股权制衡通过优化此类代理成本改善绩效。异质性分析表明，股权集中对成立时间短、发展速度慢的寿险公司绩效的负面影响更为显著。鉴于此，监管部门应适当降低寿险公司股东持股比例上限，引导非控股股东积极参与公司治理。     

Genetik und Versicherung aus ökonomischer Sicht

For some years direct gene tests have been available for many diseases and nearly every week new gene mutations are found and linked with diseases. By improving the diagnostic possibilities consequences for certain insurance branches will arise. Health and life insurance in particular will perhaps face radical chances, especially concerning the acceptance of contracts. If there is a contract between a policy holder and an insurance company, it is more important whether the cost-effectiveness of genetic screening is given. Exemplary this is calculated for a population-based screening for hemochromatosis. Furthermore it is relevant, whether the population will use available gene tests. The results of a pilot study will be presented. They show that there is a market for such products and that consequences for insurance companies are likely.     

Optimal life insurance with no-borrowing constraints: duality approach and example

We solve an optimal portfolio choice problem under a no-borrowing assumption. A duality approach is applied to study a family’s optimal consumption, optimal portfolio choice, and optimal life insurance purchase when the family receives labor income that may be terminated due to the wage earner’s premature death or retirement. We establish the existence of an optimal solution to the optimization problem theoretically by the duality approach and we provide an explicitly solved example with numerical illustration. Our results illustrate that the no-borrowing constraints do not always impact the family’s optimal decisions on consumption, portfolio choice, and life insurance. When the constraints are binding, there must exist a wealth depletion time (WDT) prior to the retirement date, and the constraints indeed reduce the optimal consumption and the life insurance purchase at the beginning of time. However, the optimal consumption under the constraints will become larger than that without the constraints at some time later than the WDT.     

Effective Underwriting in the Genetic Testing Era

This paper notes that prior to the availability of genetic test results, conventional life insurance underwriting had produced satisfactory mortality results even though a number of applicants insured at standard or better must have had serious genetic markers. The paper discusses the problems that may affect underwriting when an applicant is aware of a genetic risk factor.

The paper suggests use of pre-genetic testing era underwriting methodology, including medical history and family history, with strict financial underwriting to control antiselection. A set of underwriting rules is provided. The need for a sales organization that can produce a substantial amount of business is cited as necessary for success.

To spread equitably any excess cost on account of insuring persons with genetic markers, a risk pool is suggested. The pool manager would also inform a company of additional applications to other companies by genetically impaired applicants.

The purpose of the proposal is to deflect ill-advised political solutions and, at the same time, to control expenses by ensuring a high ratio of paid-for policies to applications.     

Household Life Cycle Protection: Life Insurance Holdings, Financial Vulnerability, and Portfolio Implications

Using the Survey of Consumer Finances, we examine the life cycle demand for different types of life insurance. Specifically, we test for the consumer's aversion to income volatility resulting from the death of a household's wage‐earner through the purchase of life insurance. We first develop a financial vulnerability index to control for the risk to the household. We then examine the life cycle demand for life insurance using several definitions of life insurance. We find, in contrast to previous research, that there is a relationship between financial vulnerability and the amount of term life or total life insurance purchased. In addition, we find older consumers use less life insurance to protect a certain level of financial vulnerability than younger consumers. Secondly, our study provides evidence that life insurance demand is jointly determined as part of a household's portfolio. Finally, we consider the impact of family members' nonmonetary contribution on the household's life cycle protection decision. Our results provide some evidence that households take into account the value of nonmonetary contribution in their insurance purchase.     

Guaranteed renewable life insurance under demand uncertainty

Guaranteed renewability (GR) is a prominent feature in many health and life insurance markets. We develop a model that includes unpredictable (and unobservable) fluctuations in demand for life insurance as well as changes in risk type (observable) over individuals' lifetimes. The presence of demand type heterogeneity leads to the possibility that optimal GR contracts may have a renewal price that is either above or below the actuarially fair price of the lowest risk type in the population. Individuals whose type turns out to be high risk but low demand renew more of their GR insurance than is efficient due to the attractive renewal price. This results in imperfect insurance against reclassification risk. Although a first‐best efficient contract is not possible in the presence of demand type heterogeneity, the presence of GR contracts nonetheless improves welfare relative to an environment with only spot markets.     

Relative Hedging of Systematic Mortality Risk

A number of problematic issues have arisen in anticipation of the potential role of molecular tests for genetic predispositions to illness in risk assessment by insurance underwriters. We argue in this paper that the regrettable history and current risks of genetic discrimination warrant a presumption that genetic predisposition status should not be used in any nonmedical contexts, unless compelling evidence can demonstrate that serious harm will result to third-party interests without such use. We argue that insurers should not be able to initiate testing for genetic predisposition. We also argue that there are many reasons to doubt whether patients’ test results will result in such serious adverse selection as to cause substantial harm to insurance markets, except possibly at higher policy amounts in life or disability income insurance. We conclude that the burden of proof must be on insurers to demonstrate necessity of use in specific cases in which test availability shows high probability of imminent, serious harm to insurance markets.     

Insurance contracts portfolios with heterogenous parametric life distributions

In this paper we consider two portfolios: one of m endowment insurance contracts and one of m whole life insurance contracts. We introduce the majorization order, Schur functions, and parametric families of distribution functions. We assume that the owners of the portfolios are exposed to different members of a known parametric family of distributions and study the effect of this stochastic heterogeneity on the premiums and death benefits of the insurance contracts. We show that the premiums paid in both contracts are Schur concave and that the death benefit awarded in the whole life contract is Schur convex. We provide upper and lower bounds for the premiums and for the death benefit, and compute the bounds for four parametric families of distribution functions used frequently in the Actuarial Sciences.     

Public Versus Private Insurance with Dual Theory: A Political Economy Argument

This paper analyzes the political support for public insurance in the presence of a private insurance alternative. The public insurance is compulsory and offers a uniform insurance policy. The private insurance is voluntary and can offer different insurance policies. Adopting Yaari's [Econometrica, 55, 95–115, 1987] dual theory to expected utility (i.e., risk aversion without diminishing marginal utility of income), we show that adverse selection on the private insurance market may lead a majority of individuals to prefer public insurance over private insurance, even if the median risk is below the average risk (so that the median actually subsidizes high-risk individuals). We also show that risk aversion makes public insurance more attractive and that the dual theory is less favourable to a mixed insurance system than the expected utility framework. Lastly, we demonstrate how the use of genetic tests may threaten the political viability of public insurance.     

Genetics,Alzheimer’s Disease,and Long-Term Care Insurance

Abstract

This paper applies a model of Alzheimer’s disease (AD) developed by Macdonald and Pritchard (2000) to the question of the potential for adverse selection in long-term care (LTC) insurance introduced by the existence of DNA tests for variants of the ApoE gene, the ε4 allele of which is known to predispose one to earlier onset of AD. It computes the expected present values (EPVs) of model LTC benefits with respect to AD for each of five ApoE genotypes, weighted average EPVs with and without adverse selection, and sample underwriting ratings. The paper concludes that adverse selection could increase costs significantly in a small LTC insurance market only if current population genetic risk is not much smaller than that observed in case-based studies, and if carriers of the ε4 allele are very much more likely to buy LTC insurance. Finally, the paper considers the cost of a combined retirement package, providing both pension and LTC insurance, and shows that it can reduce adverse selection.     

Income heterogeneity and index insurance demand

Weather index insurance as a tool to insure the income of agriculturally active households has triggered extensive discussions in the literature. Despite the convincing theoretical argumentation, the demand for these products stays behind expectations. Several studies revealed effects impacting the demand for index insurance, such as liquidity constraints, basis risk, lack of understanding and trust in insurers and products alike. This paper takes a different perspective and hypothesizes that low demand is due to heterogeneous risk exposure towards weather variability among potential insured. The paper tests the impact of income heterogeneity as a measure of risk exposure on insurance demand and finds that risk exposure negatively affects insurance demand. In order to increase demand, it is concluded that product design should emphasize more the importance of income risk composition and exposure of potentially insured.     

The impact of D&O insurance on excess corporate leverage

The governance effects of directors’ and officers’ liability insurance (D&O insurance), an important tool for risk diversification, are of strong concern in the capital market. Using a sample of Chinese A-share listed firms from 2009 to 2018, we examine the impact of D&O insurance on excess corporate leverage. We find that D&O insurance is negatively associated with excess corporate leverage and that this result is consistent with a series of robustness tests. Further analyses show that D&O insurance impedes excess corporate leverage mainly because of its effect on external monitoring. The effect is more pronounced for firms that are state-owned, have political connections and are located in provinces with low marketization than for other firms.