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In many policy areas it is essential to use the best estimates of life expectancy, but it is vital to most areas of pension policy. This paper presents the conceptual differences between static period and dynamic cohort mortality tables, estimates the differences in life expectancy for Portugal and Spain, and compares official estimates of both life expectancy estimates for Australia, the United Kingdom, and the United States for 1981, 2010, and 2060. These comparisons reveal major differences between period and cohort life expectancy in and between countries and across years. The implications of using wrong estimates for pension policy, including financial sustainability, are explored.
Mortality volatility is crucially important to many aspects of index-based longevity hedging, including instrument pricing, hedge calibration and hedge performance evaluation. This paper sets out to develop a deeper understanding of mortality volatility and its implications on index-based longevity hedging. First, we study the potential asymmetry in mortality volatility by considering a wide range of generalised autoregressive conditional heteroskedasticity (GARCH)-type models that permit the volatility of mortality improvement to respond differently to positive and negative mortality shocks. We then investigate how the asymmetry of mortality volatility may impact index-based longevity hedging solutions by developing an extended longevity Greeks framework, which encompasses longevity Greeks for a wider range of GARCH-type models, an improved version of longevity vega, and a new longevity Greek known as “dynamic Delta”. Our theoretical work is complemented by two real-data illustrations, the results of which suggest that the effectiveness of an index-based longevity hedge could be significantly impaired if the asymmetry in mortality volatility is not taken into account when the hedge is calibrated.
Chapter 1 offers a survey of human rights concerns in American foreign relations in the 1980s. First, it traces the human rights breakthrough in US foreign policy during the 1970s, emphasizing the important role individual members of Congress played in this development. The chapter notes the varied motivations behind congressional human rights activism and the selective adoption of human rights concerns. The chapter then examines the role of human rights in the 1980 presidential election between Jimmy Carter and Ronald Reagan, noting the candidates’ different visions for human rights concerns in US foreign policy. Aside from putting Reagan in the White House, the 1980 election also altered the composition of Congress, with Republicans winning control of the Senate. The chapter explores the implications this new political landscape had for congressional attention to human rights and summarizes the measures members of Congress employed to address human rights issues. Surveying American attention to human rights in the 1980s, the chapter examines liberal and conservative visions of human rights. Finally, the chapter situates human rights concerns within the context of other expressions of morality in American foreign relations.
The introductory chapter is a brief recap of the history and origins of wind power, from windmills in ancient times to today’s multi-megawatt turbines. Energy security has arguably been the historic driver for wind power, and it was a primary source of mechanical power until the advent of the Industrial Revolution, when it was superceded by coal and oil. The first electricity-generating wind turbines were built in the late nineteenth centry, and the technology was pursued most vigorously in Denmark, a country with limited energy reserves: the role of this country in creating the modern wind turbine is described. The worldwide energy crisis of the 1970s brought wind power into the frame internationally, and the pivotal role of legislation under President Carter in expanding the market for wind energy in the US and elsewhere is outlined. Since then, the rationale for wind power has expanded to include climate change, and the technology has grown exponentially in terms of global installation of wind power and the physical size of wind turbines. The chapter concludes by introducing some of the technological steps that have enabled this process, which are detailed in subsequent chapters.
There is considerable uncertainty regarding changes in future mortality rates. This article investigates the impact of such longevity risk on discounted government annuity benefits for retirees. It is critical to forecast more accurate future mortality rates to improve our estimation of an expected annuity payout. Thus, we utilize the Lee–Carter model, which is well-known as a parsimonious dynamic mortality model. We find strong evidence that female retirees are likely to receive more public lifetime annuity than males in the USA, which is associated with systematic mortality rate differences between genders. A cross-country comparison presents that the current public annuity system would not fully cover retiree's longevity risk. Every additional year of life expectancy leaves future retirees exposed to high risk, arising from high volatility of lifetime annuities. Also, because the growth in life expectancy is higher than the growth of expected public pension, there will be a financial risk to retirees.
The existence of long memory in mortality data improves the understandings of features of mortality data and provides a new approach for establishing mortality models. The findings of long-memory phenomena in mortality data motivate us to develop new mortality models by extending the Lee–Carter (LC) model to death counts and incorporating long-memory model structure. Furthermore, there are no identification issues arising in the proposed model class. Hence, the constraints which cause many computational issues in LC models are removed. The models are applied to analyse mortality death count data sets from three different countries divided according to genders. Bayesian inference with various selection criteria is applied to perform the model parameter estimation and mortality rate forecasting. Results show that multivariate long-memory mortality model with long-memory cohort effect model outperforms multivariate extended LC cohort model in both in-sample fitting and out-sample forecast. Increasing the accuracy of forecasting of mortality rates and improving the projection of life expectancy is an important consideration for insurance companies and governments since misleading predictions may result in insufficient funds for retirement and pension plans.
Longevity models allow for stochastic variation in the underlying force of mortality, so that instead of assuming, for example, that mortality follows a Gompertz model, we now assume thait changes with time, and can be modelled as a stochastic process. In this chapter we introduce the Lee-Carter and Cairns-Blake-Dowd models for longevity. We illustrate some of the structural assumptions of the models, and demonstrate key features. We also discuss briefly how the models are applied in actuarial risk management.
The Lee–Carter (LC) model is a basic approach to forecasting mortality rates of a single population. Although extensions of the LC model to forecasting rates for multiple populations have recently been proposed, the structure of these extended models is hard to justify and the models are often difficult to calibrate, relying on customised optimisation schemes. Based on the paradigm of representation learning, we extend the LCmodel to multiple populations using neural networks, which automatically select an optimal model structure. We fit this model to mortality rates since 1950 for all countries in the Human Mortality Database and observe that the out-of-sample forecasting performance of the model is highly competitive.
As a benchmark mortality model in forecasting future mortality rates and hedging longevity risk, the widely employed Lee–Carter model (Lee, R.D. and Carter, L.R. (1992) Modeling and forecasting U.S. mortality. Journal of the American Statistical Association, 87, 659–671.) suffers from a restrictive constraint on the unobserved mortality index for ensuring model’s identification and a possible inconsistent inference. Recently, a modified Lee–Carter model (Liu, Q., Ling, C. and Peng, L. (2018) Statistical inference for Lee–Carter mortality model and corresponding forecasts. North American Actuarial Journal, to appear.) removes this constraint and a simple least squares estimation is consistent with a normal limit when the mortality index follows from a unit root or near unit root AR(1) model with a nonzero intercept. This paper proposes a bias-corrected estimator for this modified Lee–Carter model, which is consistent and has a normal limit regardless of the mortality index being a stationary or near unit root or unit root AR(1) process with a nonzero intercept. Applications to the US mortality rates and a simulation study are provided as well.
In the late 1970s, the Environmental Protection Agency (EPA) unveiled the bubble policy as a central part of Jimmy Carter's plan to reform environmental regulations that many believed had grown too proscriptive and too costly for American industry. Since the EPA's formation, regulators had dictated method and means for reducing air pollution. The bubble returned the prerogative to business. But despite bipartisan support, the bubble never took off. Drawing on EPA records and interviews, this article shows how skeptical regulators intentionally made the bubble unwieldy, driving away businesses wary of uncertainty. Though Ronald Reagan's election seemed to lift the bubble's fortunes, his undiscerning assault on the administrative state ironically deflated the EPA's development of a viable alternative to the proscriptive model.
The Age-Period-Cohort-Improvement (APCI) model is a new addition to the canon of mortality forecasting models. It was introduced by Continuous Mortality Investigation as a means of parameterising a deterministic targeting model for forecasting, but this paper shows how it can be implemented as a fully stochastic model. We demonstrate a number of interesting features about the APCI model, including which parameters to smooth and how much better the model fits to the data compared to some other, related models. However, this better fit also sometimes results in higher value-at-risk (VaR)-style capital requirements for insurers, and we explore why this is by looking at the density of the VaR simulations.
With regulatory reform again on the presidential agenda, the history of the Office of Information and Regulatory Affairs (OIRA) provides a useful case study of organizational effectiveness. In 1981, President Ronald Reagan charged OIRA with imposing cost-benefit analysis on agency regulations, formalizing a new process of centralized regulatory review. But OIRA’s effectiveness flowed less from a single executive order than from the previous decade of presidential experimentation with regulatory review and Reagan’s continued investment in its institutionalization. This article draws extensively on archival documents to understand how regulatory review established itself as a constant of presidential management through the development of attributes such as staff capacity, organizational complexity, bureaucratic leverage, and reputation. Today’s policymakers should heed broader lessons for enhancing organizational effectiveness: singular structural and procedural changes are necessary, but not sufficient, for achieving reform.
This article proposes a neural-network approach to predict and simulate human mortality rates. This semi-parametric model is capable to detect and duplicate non-linearities observed in the evolution of log-forces of mortality. The method proceeds in two steps. During the first stage, a neural-network-based generalization of the principal component analysis summarizes the information carried by the surface of log-mortality rates in a small number of latent factors. In the second step, these latent factors are forecast with an econometric model. The term structure of log-forces of mortality is next reconstructed by an inverse transformation. The neural analyzer is adjusted to French, UK and US mortality rates, over the period 1946–2000 and validated with data from 2001 to 2014. Numerical experiments reveal that the neural approach has an excellent predictive power, compared to the Lee–Carter model with and without cohort effects.
Motivated by a recent discovery that the two-step inference for the Lee–Carter mortality model may be inconsistent when the mortality index does not follow from a nearly integrated AR(1) process, we propose a test for a unit root in a Lee–Carter model with an AR(p) process for the mortality index. Although testing for a unit root has been studied extensively in econometrics, the method and asymptotic results developed in this paper are unconventional. Unlike a blind application of existing R packages for implementing the two-step inference procedure in Lee and Carter (1992) to the U.S. mortality rate data, the proposed test rejects the null hypothesis that the mortality index follows from a unit root AR(1) process, which calls for serious attention on using the future mortality projections based on the Lee–Carter model in policy making, pricing annuities and hedging longevity risk. A simulation study is conducted to examine the finite sample behavior of the proposed test too.
The Criminal Code of Canada prohibits persons from aiding or abetting suicide and consenting to have death inflicted on them. Together, these provisions have prohibited physicians from assisting patients to die. On February 6, 2015, the Supreme Court of Canada declared void these provisions insofar as they “prohibit physician-assisted death for a competent adult person who (1) clearly consents to the termination of life and (2) has a grievous and irremediable medical condition (including an illness, disease or disability) that causes enduring suffering that is intolerable to the individual in the circumstances of his or her condition.” This declaration of invalidity was scheduled to take effect one year (later extended by six months) after the ruling, to give the government time to put legislation in place. We trace the history of this decision, discuss how it has forever changed the debate on physician-assisted dying, and identify the issues that must be resolved to write the legislation. Of special importance here are the topics of access, safeguards, and conscientious objection.
This paper outlines the extensive range of public programs offered by the Carter Observatory, including ‘public nights’, new planetarium and audio-visual shows, displays, the Carter Memorial Lectures, the annual Astronomical Handbook and other publications, a monthly newspaper column and three monthly radio programs. It also deals with the Observatory’s involvement in undergraduate and postgraduate astronomy at Victoria University of Wellington, various adult education training programs, ‘Overnight Extravaganzas’, holiday programs, and the recent development of the Education Service in response to the introduction of an astronomy curriculum into schools throughout New Zealand. Some possible future developments in the public astronomy and education areas are also discussed.
This article chronicles the formation and first season of the dance company Ballet Caravan (1936–1940) with a special focus on the role of Lincoln Kirstein in the troupe's founding. This account of the Caravan's early history draws upon an array of primary sources to offer new perspectives on the company's relationship to modern dance circles and its parent organizations (the American Ballet and School of American Ballet, co-founded by Kirstein and George Balanchine in 1934). It traces Ballet Caravan's touring activities during 1936 (including its debut at Bennington College) and details ballets created for the company by Lew Christensen, Eugene Loring, and William Dollar, as well as previously unknown early choreographic work by Erick Hawkins. This account reveals that Ballet Caravan was initially conceived of neither as a dancer-driven initiative nor a deliberate attempt by Kirstein to pursue an American artistic agenda (as it has been previously understood by scholars), but rather was a practical response to institutional crises in the larger Balanchine–Kirstein ballet enterprise. The American Ballet and Ballet Caravan thus reveal themselves in 1936 as more contiguous than distinct, sharing personnel and aesthetic values, as well as the involvement of Balanchine himself.
Considering the substantial systematic longevity risk threatening annuity providers’ solvency, indexing benefits on actual mortality improvements appears to be an efficient risk management tool, as discussed in Denuit et al. (2011) and Richter and Weber (2011). Whereas these papers consider indexing annuity payments, the present work suggests that the length of the deferment period could also be subject to revision, providing longevity-contingent deferred life annuities.
We compare quantitatively six simulation strategies for mortality projection with the Poisson Lee–Carter model. We test these strategies on New Zealand mortality data and discuss the simulated results of the mortality index, death rates, and life expectancy.
Longevity risk faced by annuity portfolios and defined-benefit pension schemes is typically long-term, i.e. the risk is of an adverse trend which unfolds over a long period of time. However, there are circumstances when it is useful to know by how much expectations of future mortality rates might change over a single year. Such an approach lies at the heart of the one-year, value-at-risk view of reserves, and also for the pending Solvency II regime for insurers in the European Union. This paper describes a framework for determining how much a longevity liability might change based on new information over the course of one year. It is a general framework and can accommodate a wide choice of stochastic projection models, thus allowing the user to explore the importance of model risk. A further benefit of the framework is that it also provides a robustness test for projection models, which is useful in selecting an internal model for management purposes.