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Modeling Long-Run Cause of Death Mortality Trends

Modeling Long-Run Cause of Death Mortality Trends
Author: Michael Sherris
Publisher:
Total Pages: 0
Release: 2011
Genre:
ISBN:

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This paper models relationships between trends in cause of death mortality rates for five main causes of death (circulatory system, cancer, respiratory system, external causes, infectious and parasitic diseases) across nine major countries (USA, Australia, Switzerland, Japan, Singapore, Italy, Norway, Sweden, UK). Trends and relationships between mortality rates for causes of death are important since these trends are hidden in aggregate data. Vector Error Correction Models (VECM) are used to model the common trends in causes of death by country. A VECM is a multivariate dynamic system allowing for long-run relationships between variables and common stochastic trends. The paper demonstrates that mortality rates by causes of death have common stochastic trends in many countries but these also differ across countries highlighting the potential for geographical diversification of mortality trends. The results confirm long-run relationships exist between the five main causes of death, indicating dependence between these competing risks. Cause of death analysis provides valuable information that can improve the estimation of aggregate mortality trends.


Forecasting Mortality Trends Allowing for Cause-of-Death Mortality Dependence

Forecasting Mortality Trends Allowing for Cause-of-Death Mortality Dependence
Author: Severine Arnold (-Gaille)
Publisher:
Total Pages: 16
Release: 2013
Genre:
ISBN:

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Longevity risk is amongst the most important factors to consider for pricing and risk management of longevity products. Past improvements in mortality over many years, and the uncertainty of these improvements, have attracted the attention of experts, both practitioners and academics. Since aggregate mortality rates reflect underlying trends in causes of death, insurers and demographers are increasingly considering cause-of-death data to better understand risks in their mortality assumptions. The relative importance of causes of death has changed over many years. As one cause reduces, others increase or decrease. The dependence between mortality for different causes of death is important when projecting future mortality. However, for scenario analysis based on causes of death, the assumption usually made is that causes of death are independent. Recent models, in the form of Vector Error Correction Models (VECM), have been developed for multivariate dynamic systems and capture time dependency with common stochastic trends. These models include long-run stationary relations between the variables, and thus allow a better understanding of the nature of this dependence. This paper applies VECM to cause-of-death mortality rates in order to assess the dependence between these competing risks. We analyze the five main causes of death in Switzerland. Our analysis confirms the existence of a long-run stationary relationship between these five causes. This estimated relationship is then used to forecast mortality rates, which are shown to be an improvement over forecasts from more traditional ARIMA processes, that do not allow for cause-of-death dependencies.


Improving Longevity and Mortality Risk Models with Common Stochastic Long-Run Trends

Improving Longevity and Mortality Risk Models with Common Stochastic Long-Run Trends
Author: Michael Sherris
Publisher:
Total Pages: 0
Release: 2011
Genre:
ISBN:

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Modeling mortality and longevity risk presents challenges because of the impact of improvements at different ages and the existence of common trends. Modeling cause of death mortality rates is even more challenging since trends and age effects are more diverse. Despite this, successfully modeling these mortality rates is critical to assessing risk for insurers issuing longevity risk products including life annuities. Longevity trends are often forecasted using a Lee-Carter model. A common stochastic trend determines age-based improvements. Other approaches fit an age-based parametric model with a time series or vector autoregression for the parameters. Vector Error Correction Models (VECM), developed recently in econometrics, include common stochastic long-run trends. This paper uses a stochastic parameter VECM form of the Heligman-Pollard model for mortality rates, estimated using data for circulatory disease deaths in the United States over a period of 50 years. The model is then compared with a version of the Lee-Carter model and a stochastic parameter ARIMA Heligman-Pollard model. The VECM approach proves to be an improvement over the Lee-Carter and ARIMA models as it includes common stochastic long-run trends.


Future Directions for the Demography of Aging

Future Directions for the Demography of Aging
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
Total Pages: 409
Release: 2018-07-21
Genre: Social Science
ISBN: 0309474108

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Almost 25 years have passed since the Demography of Aging (1994) was published by the National Research Council. Future Directions for the Demography of Aging is, in many ways, the successor to that original volume. The Division of Behavioral and Social Research at the National Institute on Aging (NIA) asked the National Academies of Sciences, Engineering, and Medicine to produce an authoritative guide to new directions in demography of aging. The papers published in this report were originally presented and discussed at a public workshop held in Washington, D.C., August 17-18, 2017. The workshop discussion made evident that major new advances had been made in the last two decades, but also that new trends and research directions have emerged that call for innovative conceptual, design, and measurement approaches. The report reviews these recent trends and also discusses future directions for research on a range of topics that are central to current research in the demography of aging. Looking back over the past two decades of demography of aging research shows remarkable advances in our understanding of the health and well-being of the older population. Equally exciting is that this report sets the stage for the next two decades of innovative researchâ€"a period of rapid growth in the older American population.


Modelling Mortality with Common Stochastic Long-Run Trends

Modelling Mortality with Common Stochastic Long-Run Trends
Author: Severine Arnold (-Gaille)
Publisher:
Total Pages: 0
Release: 2015
Genre:
ISBN:

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Modelling mortality and longevity risk is critical to assessing risk for insurers issuing longevity risk products. It has challenged practitioners and academics alike because of first the existence of common stochastic trends and second the unpredictability of an eventual mortality improvement in some age groups. When considering cause-of-death mortality rates, both aforementioned trends are additionally affected by the cause of death. Longevity trends are usually forecasted using a Lee-Carter model with a single stochastic time series for period improvements, or using an age-based parametric model with univariate time series for the parameters. We assess a multivariate time series model for the parameters of the Heligman-Pollard function, through Vector Error Correction Models which include the common stochastic long-run trends. The model is applied to circulatory disease deaths in U.S. over a 50-year period and is shown to be an improvement over both the Lee-Carter model and the stochastic parameter ARIMA Heligman-Pollard model.


Old and New Perspectives on Mortality Forecasting

Old and New Perspectives on Mortality Forecasting
Author: Tommy Bengtsson
Publisher: Springer
Total Pages: 349
Release: 2019-03-28
Genre: Social Science
ISBN: 3030050750

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This open access book describes methods of mortality forecasting and discusses possible improvements. It contains a selection of previously unpublished and published papers, which together provide a state-of-the-art overview of statistical approaches as well as behavioural and biological perspectives. The different parts of the book provide discussions of current practice, probabilistic forecasting, the linearity in the increase of life expectancy, causes of death, and the role of cohort factors. The key question in the book is whether it is possible to project future mortality accurately, and if so, what is the best approach. This makes the book a valuable read to demographers, pension planners, actuaries, and all those interested and/or working in modelling and forecasting mortality.


Disease Control Priorities, Third Edition (Volume 2)

Disease Control Priorities, Third Edition (Volume 2)
Author: Robert Black
Publisher: World Bank Publications
Total Pages: 419
Release: 2016-04-11
Genre: Medical
ISBN: 1464803684

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The evaluation of reproductive, maternal, newborn, and child health (RMNCH) by the Disease Control Priorities, Third Edition (DCP3) focuses on maternal conditions, childhood illness, and malnutrition. Specifically, the chapters address acute illness and undernutrition in children, principally under age 5. It also covers maternal mortality, morbidity, stillbirth, and influences to pregnancy and pre-pregnancy. Volume 3 focuses on developments since the publication of DCP2 and will also include the transition to older childhood, in particular, the overlap and commonality with the child development volume. The DCP3 evaluation of these conditions produced three key findings: 1. There is significant difficulty in measuring the burden of key conditions such as unintended pregnancy, unsafe abortion, nonsexually transmitted infections, infertility, and violence against women. 2. Investments in the continuum of care can have significant returns for improved and equitable access, health, poverty, and health systems. 3. There is a large difference in how RMNCH conditions affect different income groups; investments in RMNCH can lessen the disparity in terms of both health and financial risk.


Explaining Divergent Levels of Longevity in High-Income Countries

Explaining Divergent Levels of Longevity in High-Income Countries
Author: National Research Council
Publisher: National Academies Press
Total Pages: 200
Release: 2011-06-27
Genre: Social Science
ISBN: 0309217105

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During the last 25 years, life expectancy at age 50 in the United States has been rising, but at a slower pace than in many other high-income countries, such as Japan and Australia. This difference is particularly notable given that the United States spends more on health care than any other nation. Concerned about this divergence, the National Institute on Aging asked the National Research Council to examine evidence on its possible causes. According to Explaining Divergent Levels of Longevity in High-Income Countries, the nation's history of heavy smoking is a major reason why lifespans in the United States fall short of those in many other high-income nations. Evidence suggests that current obesity levels play a substantial part as well. The book reports that lack of universal access to health care in the U.S. also has increased mortality and reduced life expectancy, though this is a less significant factor for those over age 65 because of Medicare access. For the main causes of death at older ages-cancer and cardiovascular disease-available indicators do not suggest that the U.S. health care system is failing to prevent deaths that would be averted elsewhere. In fact, cancer detection and survival appear to be better in the U.S. than in most other high-income nations, and survival rates following a heart attack also are favorable. Explaining Divergent Levels of Longevity in High-Income Countries identifies many gaps in research. For instance, while lung cancer deaths are a reliable marker of the damage from smoking, no clear-cut marker exists for obesity, physical inactivity, social integration, or other risks considered in this book. Moreover, evaluation of these risk factors is based on observational studies, which-unlike randomized controlled trials-are subject to many biases.


Causes-of-Death Mortality

Causes-of-Death Mortality
Author: Severine Arnold (-Gaille)
Publisher:
Total Pages:
Release: 2015
Genre:
ISBN:

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Over the last century, the assumption usually made was that causes of death are independent, although it is well-known that dependancies exist. Recent developments in econometrics allow, through Vector Error Correction Models (VECM), to model multivariate dynamic systems including time dependency between economic variables. Common trends that exist between the variables may then be highlighted, the relation between these variables being represented by a long-run equilibrium relationship. In this work, VECM are developed for causes-of-death mortality. We analyze the five main causes of death across ten major countries representing a diversity of developed economies. The World Health Organization website provides cause-of-death information over about the last 60 years. Our analysis reveals that long-run equilibrium relationships exist between the five main causes of death, improving our understanding of the nature of dependence between these competing risks over recent years. It also highlights that countries had usually different past experience in regards to cause-of-death mortality trends and thus, applying results from one country to another may be misleading.