nep-ias New Economics Papers
on Insurance Economics
Issue of 2010‒07‒24
eleven papers chosen by
Soumitra K Mallick
Indian Institute of Social Welfare and Bussiness Management

  1. The incentive for prevention in public health Systems By Renaud Bourlès
  2. Disability risk, disability insurance and life cycle behavior By Hamish Low; Luigi Pistaferri
  3. Waiting times and the decision to buy private health insurance. CHERE Working Paper 2010/9 By Meliyanni Johar; Glenn Jones; Michael Keane; Elizabeth Savage; Olena Stavrunova
  4. Understanding, Modeling and Managing Longevity Risk: Key Issues and Main Challenges By Pauline Barrieu; Harry Bensusan; Nicole El Karoui; Caroline Hillairet; Stéphane Loisel; Claudia Ravanelli; Yahia Salhi
  5. The demand for private health insurance: do waiting lists or waiting times matter? CHERE Working Paper 2010/8 By Meliyanni Johar; Glenn Jones; Michael Keane; Elizabeth Savage; Olena Stavrunova
  6. The Uncertain Mortality Intensity Framework: Pricing and Hedging Unit-Linked Life Insurance Contracts By Jing Li; Alexander Szimayer
  7. Joiners and leavers stayers and abstainers: Private health insurance choices in Australia By Stephanie Knox; Elizabeth Savage; Denzil Fiebig; Vineta Salale
  8. What Does Health Reform Mean for the Healthcare Industry? Evidence from the Massachusetts Special Senate Election By Mohamad Al-Ississ; Nolan H. Miller
  9. Agricultural Insurances Based on Meteorological Indices: Realizations, Methods and Research Agenda By Antoine Leblois; Philippe Quirion
  10. Insurance and Investment within Family Networks By Manuela Angelucci; Giacomo de Giorgi; Imran Rasul; Marcos A. Rangel
  11. Risk Pooling, Risk preferences, and Social Networks By Orazio Attansio; Abigail Barr; Juan Camilo Cardenas; Garance Genicot; Costas Mehgir

  1. By: Renaud Bourlès (École Centrale de Marseille and Greqam)
    Abstract: This paper examines the effect of moral hazard on public health insurance contract. It models primary prevention in a two period model with classification risk. Agent’s preferences appear to play an important role in the optimal determination of preventive effort and insurance between generations. If absolute prudence is larger than twice absolute risk aversion, moral hazard increases intergenerational insurance and classification risk. This highlights a tradeoff between prevention and insurance arising from classification risk. An increase in the difference between prudence and twice risk aversion (that we define as the degree of “protectiveness”) moreover makes public insurance contracts more stable (when competing with spot insurance) if the cost of prevention is low enough when agents preferences exhibit CRRA. Under a formulated utility function with linear reciprocal derivative, we finally show that an increase in agent’s degree of “protectiveness” enhances the stability of public insurance and the extent of intergenerational insurance.
    Keywords: Public health insurance; Classification risk; Moral Hazard; Prudence.
    JEL: D81 D91 G22
    Date: 2010–02–17
  2. By: Hamish Low (Institute for Fiscal Studies and Trinity College, Cambridge); Luigi Pistaferri (Institute for Fiscal Studies and Stanford University)
    Abstract: The Disability Insurance (DI) program in the US is a large social insurance program that offers income replacement benefits to people with work limiting disabilities. The proportion of DI claimants in the US is now almost 5% of the working-age population and the cost is three times that of unemployment insurance. The key questions in thinking about the size and growth of the DI program are whether program claimants are genuinely unable to work, and how valuable is the insurance provided. This paper has three aims: 1. We provide a framework for weighing up the insurance value of disability benefi…ts against the incentive cost of inducing healthy individuals to stop work at different points of their life-cycle. 2. We estimate the risks to health that may lead to work-limiting disabilities and the risk to wages that may lead to individuals choosing not to work. We also estimate the extent of false awards made through the DI program alongside the proportion of awards to those in genuine need. 3. We use our model and estimates to characterize the economic effects of the disability insurance and to consider how policy reforms would affect behaviour and standard measures of household welfare. We differentiate disability status by its severity, and show that a severe disability shock leads to a decline in wages of 40%, as well as a substantial rise in the fixed cost of going to work. In terms of the effectiveness of the DI program, we estimate high levels of rejections of genuine applicants. In our counterfactual simulations, this means that household welfare increases as the program becomes less strict, despite the worsening incentives for false applications that this implies. On the other hand, incentives for false applications are reduced by reducing generosity and increasing reassessments, and these policies increase household welfare, despite the worse insurance implied.
    Keywords: Disability, social security, savings behavior, wage risk
    JEL: D91 H53 H55 J26
    Date: 2010–05
  3. By: Meliyanni Johar (CHERE, University of Technology, Sydney); Glenn Jones; Michael Keane; Elizabeth Savage; Olena Stavrunova
    Abstract: Over 45% of Australians buy health insurance for private treatment in hospital. This is despite having access to universal and free public hospital treatment. Anecdotal evidence suggests that one possible explanation for the high rate of insurance coverage is to avoid long waiting times for public hospital treatment. In this study, we investigate the effect of expected waiting time on individual decisions to buy private health insurance. Individuals are assumed to form an expectation of their own waiting time as a function of their demographics and health status. We estimate models of expected waiting time using administrative data on the population hospitalised for elective procedures in public hospitals in 2004-05 and use the parameter estimates to impute expected waiting times for individuals in a representative sample of the population. We model the impact of expected waiting time on the decision to purchase private health insurance. In the insurance demand model, cross-sample predictions are adjusted by the individualsÂ’ probability of hospital admission. We find that expected waiting time does not increase the probability of buying insurance but a high probability of experiencing a long wait does. Overall we find there is no significant impact of waiting time on insurance purchase. In addition, we find that the inclusion of individual waiting time variables removes the evidence for favourable selection into private insurance, as measured by self-assessed health. This result suggests that a source of the favourable selection by reported health status may be aversion to long waits among healthier people.
    Keywords: Private health insurance, Australia
    JEL: I11 J7 H51
    Date: 2010–05
  4. By: Pauline Barrieu (Department of Statistics - London School of Economics); Harry Bensusan (CMAP UMR 7641 - Centre de Mathématiques Appliquées - Ecole Polytechnique - Polytechnique - X - CNRS : UMR7641); Nicole El Karoui (CMAP UMR 7641 - Centre de Mathématiques Appliquées - Ecole Polytechnique - Polytechnique - X - CNRS : UMR7641); Caroline Hillairet (CMAP UMR 7641 - Centre de Mathématiques Appliquées - Ecole Polytechnique - Polytechnique - X - CNRS : UMR7641); Stéphane Loisel (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429); Claudia Ravanelli (Swiss Financial Institute - École Polytechnique Fédérale de Lausanne); Yahia Salhi (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I : EA2429, CERDALM - SCOR Global Life)
    Abstract: This article investigates the latest developments in longevity risk modelling, and explores the key risk management challenges for both the financial and insurance industries. The article discusses key definitions that are crucial for the enhancement of the way longevity risk is understood; providing a global view of the practical issues for longevity-linked insurance and pension products that have evolved concurrently with the steady increase in life expectancy since 1960s. In addition, the article frames the recent and forthcoming developments that are expected to action industry-wide changes as more effective regulation, designed to better assess and efficiently manage inherited risks, is adopted. Simultaneously, the evolution of longevity is intensifying the need for capital markets to be used to manage and transfer the risk through what are known as Insurance-Linked Securities (ILS). Thus, the article will examine the emerging scenarios, and will finally highlight some important potential developments for longevity risk management from a financial perspective with reference to the most relevant modelling and pricing practices in the banking industry.
    Keywords: Longevity Risk ; securitization ; risk transfer ; incomplete market ; life insurance ; stochastic mortality ; pensions ; long term interest rate ; regulation ; population dynamics
    Date: 2010
  5. By: Meliyanni Johar (CHERE, University of Technology, Sydney); Glenn Jones; Michael Keane; Elizabeth Savage; Olena Stavrunova
    Abstract: Besley, Hall, and Preston (1999) estimated a model of the demand for private health insurance in Britain as a function of regional waiting lists and found that increases in the number of people waiting for more than 12 months (the long-term waiting list) increased the probability of insurance purchase. In the absence of waiting time data, the length of regional long-term waiting lists was used to capture the price-quality trade-off of public treatment. We revisit Besley et al.Â’s analysis using Australian data and test the use of waiting lists as a proxy for waiting time in models of insurance demand. Unlike Besley et al., we find that the long-term waiting list is not a significant determinant of the demand for insurance. However we find that long waiting times do significantly increase insurance. This suggests that the relationship between waiting times and waiting lists is not as straightforward as is commonly assumed.
    Keywords: waiting time, waiting lists, health insurance, regional aggregation
    JEL: I11 J7 H51
    Date: 2010–06
  6. By: Jing Li; Alexander Szimayer
    Abstract: We study the valuation and hedging of unit-linked life insurance contracts in a setting where mortality intensity is governed by a stochastic process. We focus on model risk arising from different specifications for the mortality intensity. To do so we assume that the mortality intensity is almost surely bounded under the statistical measure. Further, we restrict the equivalent martingale measures and apply the same bounds to the mortality intensity under these measures. For this setting we derive upper and lower price bounds for unit-linked life insurance contracts using stochastic control techniques. We also show that the induced hedging strategies indeed produce a dynamic superhedge and subhedge under the statistical measure in the limit when the number of contracts increases. This justifies the bounds for the mortality intensity under the pricing measures. We provide numerical examples investigating fixed-term, endowment insurance contracts and their combinations including various guarantee features. The pricing partial differential equation for the upper and lower price bounds is solved by finite difference methods. For our contracts and choice of parameters the pricing and hedging is fairly robust with respect to misspecification of the mortality intensity. The model risk resulting from the uncertain mortality intensity is of minor importance.
    Keywords: unit-linked life insurance contracts, mortality model risk, price bounds, stochastic control
    JEL: G13 G22 C61
    Date: 2010–07
  7. By: Stephanie Knox (CHERE, University of Technology,Sydney); Elizabeth Savage (CHERE, University of Technology,Sydney); Denzil Fiebig; Vineta Salale
    Abstract: The percentage of Australians taking up Private Health Insurance (PHI) was in decline following the introduction of Medicare in 1984 (PHIAC). To arrest this decline the Australian Government introduced a suite of policies, between 1997 and 2000, to create incentives for Australians to purchase private health insurance. These policies include an increased Medicare levy for those without PHI on high incomes, introduced in 1997, a 30% rebate for private hospital cover (introduced 1998), and the Lifetime Health Cover (LHC) policy where PHI premiums are set at age of entry, increasing for each year older than 30 years (introduced 2000). In 2004 the longitudinal study on Household Income and Labour Dynamics in Australia (HILDA), included a series of questions on private health insurance and hospital use. We used the HILDA data to investigate the demographic, health and income factors related to the PHI decisions, especially around the introduction of the Lifetime Health Cover policy. Specifically we investigate who was most influenced to purchase PHI (specifically hospital cover) in 2000 as a response to the Lifetime Health Cover policy deadline. Are those who have joined PHI since the introduction of LHC different from those who joined prior to LHC? What are the characteristics of those who have dropped PHI since the introduction of LHC? We model the PHI outcomes allowing for heterogeneity of choice and correlation across alternatives. After controlling for other factors, we find that LHC prompted moderately well-off working age adults (30-49 yrs) to purchase before the 2000 deadline. Young singles or couples with no children, and the overseas born were more likely to purchase since 2000, while the relatively less well-off continue to drop PHI in spite of current policy incentives.
    Keywords: private health insurance, incentives, Australia
    JEL: I10
    Date: 2010–02
  8. By: Mohamad Al-Ississ; Nolan H. Miller
    Abstract: President Obama's health insurance reform efforts, as embodied in the bills passed by the House and Senate in late 2009 and signed into law in March of 2010, have been described both as a boon and a death blow for private insurance industries. Using stock-price data on health care firms in the S&P health index, we exploit Republican Scott Brown's surprise victory in the Massachusetts Special Senate election to fill the seat of the late Ted Kennedy, which stripped Democrats of the 60-vote majority needed to pass the bill in the Senate, to evaluate the market's assessment of health reform on the health care industry. We find that the reduced likelihood of Health Reform’s passage after the Brown election led to a significant increase in health industry stocks and average cumulative abnormal returns of 1.2 percent, corresponding to an increase in total market value of approximately $14.5 billion. Focusing on managed care (insurance) firms, we find an average cumulative abnormal return of 6.5 percent (a $6.7 billion increase in market value), with individual firms’ cumulative abnormal returns ranging from around 5 to 9 percent.
    JEL: D72 G14 I11
    Date: 2010–07
  9. By: Antoine Leblois (CIRED (Centre International de Recherche sur l’Environnement et le Développement)); Philippe Quirion (CIRED, CNRS, LMD-IPSL (Laboratoire de Météorologie Dynamique – Institut Pierre-Simon Laplace))
    Abstract: In many low-income countries, agriculture is mostly rain-fed and yields highly depend on climatic factors. Furthermore, farmers have little access to traditional crop insurance, which suffers from high information asymmetry and transaction costs. Insurances based on meteorological indices could fill this gap since they do not face such drawbacks. However their implementation has been slow so far. In this article, we first describe the most advanced projects that have taken place in developing countries using these types of crop insurances. We then describe the methodology that has been used to design such projects, in order to choose the meteorological index, the indemnity schedule and the insurance premium. We finally draw an agenda for research in economics on this topic. In particular, more research is needed on implementation issues, on the assessment of benefits, on the way to deal with climate change, on the spatial variability of weather and on the interactions with other hedging methods.
    Keywords: Agriculture, Insurance, Climatic Risk
    JEL: G21 O12 Q12 Q18 Q54
    Date: 2010–06
  10. By: Manuela Angelucci; Giacomo de Giorgi; Imran Rasul; Marcos A. Rangel
    Abstract: In this paper family networks affecting informal insurance and investment is being studied. Panel data from the randomized evaluation of PROGRESA in rural Mexico and the information on surnames of household heads and their spouses to identify extended families have been used. Members of an extended family: 1) share risk with each other but not with households without relatives in the village; 2) invest more in their children's human capital when hit by positive income shocks, and disinvest less when hit by negative shock, and 3) have a higher long-term increase in capital, income, and consumption than households without relatives in the village. [Working Paper No. 260]
    Keywords: extended family networks, investment, risk-sharing
    Date: 2010
  11. By: Orazio Attansio; Abigail Barr; Juan Camilo Cardenas; Garance Genicot; Costas Mehgir
    Abstract: Using date from a field experiment conducted in seventy Colombian municipalities, we investigate who pools risk with whom when risk pooling arrangements are not formally enforced. We explore the roles played by risk attitudes and network connections both theoretically and empirically. We find that pairs of participants who share a bond of friendship or kinship are more likely to (1) join the same risk pooling group and to (2) group assortatively with respect to risk attitudes. Also, consistent with our theoretical finding that when there is a problem of trust the process of pooling assortativley with respect to risk preferences is perturbed, we find (3) only weak evidence of such assorting among unfamiliar individuals.
    Keywords: Field experiment; risk sharing; social sanctions; Insurance; Group formation: matching.
    JEL: C93 D71 D81 O12
    Date: 2009

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