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On finite-time ruin probabilities in a generalized dual risk model with dependence
In this paper, we study the finite-time ruin probability in a reasonably generalized dual risK model, where we assume any non-negative non-decreasing cumulative operational cost function and arbitrary capital gains arrival process. Establishing an enlightening link between this dual risk model and its corresponding insurance risk model, explicit expressions for the finite-time survival probability in the dual risk model are obtained under various general assumptions for the distribution of the capital gains. In order to make the model more realistic and general, different dependence structures among capital gains and inter-arrival times and between both are also introduced and corresponding ruin probability expressions are also given. The concept of alarm time, as introduced in Das and Kratz (2012), is applied to the dual risk model within the context of risk capital allocation. Extensive numerical illustrations are provided
Structural Uncertainty and the Value of Statistical Life in the Economics of Catastrophic Climate Change
Using climate change as a prototype motivating example, this paper analyzes the implications of structural uncertainty for the economics of catastrophes. The paper shows that having an uncertain multiplicative parameter, which scales or amplifies exogenous shocks and is updated by Bayesian learning, induces a critical 'tail fattening' of posterior-predictive distributions. Such fattened tails have strong implications for situations (like climate change) where a catastrophe is theoretically possible because prior knowledge cannot place sufficiently narrow bounds on overall damages. At least potentially, the impact on cost-benefit analysis of fat-tailed uncertainty about the scale of damages'coupled with a high value of statistical life'outweighs the importance of discounting or anything else.
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Whither human survival and longevity or the shape of things to come
With the continuing increases in life expectancy, populations are ageing rapidly. Governments are concerned for the future of pensions and health care for which population forecasts are an important component for planning purposes. In this paper we focus on human survival rather than mortality rates which are the more usual starting point when estimating future populations. Using a simple model we link basic measures of life expectancy to the shape of the human survival function and consider its various forms. We then use the simple model as the basis for investigating actual survival in England and Wales from 1841 onwards and investigate the concept of a ‘maximum age’. We show how the model can be used in a predictive sense and demonstrate in two tests that show our model would have given more accurate results than comparable government forecasts using the same base information. We then go on to show that, based on trends in life expectancy, official population forecasts could undershoot the population at age 50+ by 0.6m, with consequent financial implications for pensions, health and social care
Current Topics on Risk Analysis: ICRA6 and RISK2015 Conference
Peer ReviewedPostprint (published version
Current Topics on Risk Analysis: ICRA6 and RISK2015 Conference
Artículos presentados en la International Conference on Risk Analysis ICRA 6/RISK
2015, celebrada en Barcelona del 26 al 29 de mayo de 2015.Peer ReviewedPostprint (published version
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Asset allocation decision models in life insurance
The problem of determining the optimal asset allocation strategies for a non-profit life company is approached from a rational decision- making framework. Initially, a number of methods for analysing investment risk are discussed, from which utility theory is felt to be the most appropriate. Stochastic simulation and numerical optimization methods are employed in order to allow more realistic assumptions to be used in these decision models.
The multiperiod consumption of dividends is dealt with by considering the expected utility of accumulated dividends, or pay-outs. At first, the case of an open fund is investigated in a static asset allocation framework. In general, the results produced are quite intuitive. At low levels of risk tolerance, the optimal portfolios seem reasonably matched in relation to the liabilities. As the risk tolerance level increases, the preference for matching is seen to reduce. If pay-outs are measured in real terms, greater proportions tend to be invested in the real asset classes. From a mean-variance perspective, the utility maximizing portfolios generally appear to be efficient. However, imposing insolvency constraints on the objective function can have the effect of shifting some of these portfolios away from the efficient frontier.
In the case of a closed fund, dynamic asset allocation strategies are investigated. Due to the restrictive assumptions it requires, the possibility of applying dynamic programming in this situation is rejected. Instead, it is proposed that the asset proportions be made functions of the duration of the liabilities, so that the expected utility may be maximized in respect of these function parameters. Overall, this appears to produce reasonable results, although the occasional emergence of less intuitive strategies leaves further scope for refining the treatment of multiperiod consumption
The Emergent Logic of Health Law
The American health care system is on a glide path toward ruin. Health spending has become the fiscal equivalent of global warming, and the number of uninsured Americans is approaching fifty million. Can law help to divert our country from this path? There are reasons for deep skepticism. Law governs the provision and financing of medical care in fragmented and incoherent fashion. Commentators from diverse perspectives bemoan this chaos, casting it as an obstacle to change. I contend in this Article that pessimism about health law’s prospects is unjustified, but that a new understanding of health law’s disarray is urgently needed to guide reform. My core proposition is that the law of health care provision is best understood as an emergent system. Its contradictions and dysfunctions cannot be repaired by some master design. No one actor has a grand overview—or the power to impose a unifying vision. Countless market players, public planners, and legal and regulatory decisionmakers interact in oft-chaotic ways, clashing with, reinforcing, and adjusting to each other. Out of these interactions, a larger scheme emerges—one that incorporates the health sphere’s competing interests and values. Change in this system, for worse and for better, arises from the interplay between its myriad actors. By quitting the quest for a single, master design, we can better focus our efforts on possibilities for legal and policy change. We can and should continuously survey the landscape of stakeholders and expectations with an eye toward potential launching points for evolutionary processes—processes that leverage current institutions and incentives. What we cannot do is plan or predict these evolutionary pathways in precise detail; the complexity of interactions among market and government actors precludes fine-grained foresight of this sort. But we can determine the general direction of needed change, identify seemingly intractable obstacles, and envision ways to diminish or finesse them over time. Dysfunctional legal doctrines, interest group expectations, consumers’ anxieties, and embedded institutional and cultural barriers can all be dealt with in this way, in iterative fashion. This Article sets out a strategy for doing so. To illustrate this strategy, I suggest emergent approaches to the most urgent challenges in health care policy and law—the crises of access, value, and cost
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