Time series analysis and stochastic forecasting: An econometric study of mortality and life expectancy

Denton, Frank T.; Feaver, Christine H.; Spencer, Byron G.

doi:10.1007/s00148-005-0229-2

Cited by 30 publications

(23 citation statements)

References 25 publications

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“…The Lee-Carter method is one. Others include procedures involving stochastic (autoregressive models) and bootstrapping methods based on random samples drawn from historical series of changes in mortality rates, as in Denton, Feaver, and Spencer (2005). some idea as to the possible degree of understatement that may exist in the use of period expectancies.…”

Section: Resultsmentioning

confidence: 99%

“…They show the path to be virtually linear over 160 years, with an average increment of a quarter of a year per year and no sign of slowing. For two other examples see the study of mortality rates in the G7 countries by Tuljapurkar, Li, and Boe (2000) and the study of the Canadian record in Denton, Feaver, and Spencer (2005); the downward paths of mortality based on logarithmic summary measures in these two studies are virtually linear too, again with no sign of moderation. We note briefly the mathematics of the standard period life table and then develop the dynamic framework.…”

Section: Introductionmentioning

confidence: 99%

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A Dynamic Extension of the Period Life Table

Denton

Spencer

2011

DemRes

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Dynamic Extension of the Period Life Table

Denton

Spencer

2011

DemRes

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“…In this sense, the population dataset embraces a number of distinct categories, so that the sampling frame can be ordered by these categories into separate strata, by using stratified sampling. However, if we consider the dataset by single ages, the correlations between the residuals for adjacent age groups tend to be high (as noted in Denton et al 2005). This suggests that we are dealing with a certain class of dependent process.…”

Section: mentioning

confidence: 96%

The Poisson Log-Bilinear Lee-Carter Model

D’Amato

Lorenzo

Haberman

et al. 2011

North American Actuarial Journal

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractLife insurance companies deal with two fundamental types of risks when issuing annuity contracts: financial risk and demographic risk. As regards the latter, recent work has focused on modelling the trend in mortality as a stochastic process. A popular method for modelling death rates is the Lee-Carter model. This methodology has become widely used and there have been various extensions and modifications proposed to obtain a broader interpretation and to capture the main features of the dynamics of mortality rates. In order to improve the measurement of uncertainty in survival probability estimates, in particular for older ages, the paper proposes an extension based on simulation procedures and on the bootstrap methodology. It aims to obtain more reliable and accurate mortality projections, based on the idea of obtaining an acceptable accuracy of the estimate by means of variance reducing techniques. In this way, the forecasting procedure becomes more efficient. The longevity question constitutes a critical element in the solvency appraisal of pension annuities. The demographic models used for the cash flow distributions in a portfolio impact on the mathematical reserve and surplus calculations and affect the risk management choices for a pension plan. The paper extends the investigation of the impact of survival uncertainty for life annuity portfolios and for a guaranteed annuity option in the case where interest rates are stochastic. In a framework in which insurance companies need to use internal models for risk management purposes and for determining their Solvency Capital Requirement, the authors consider the surplus value, calculated as the ratio between the market value of the projected assets to that of the liabilities, as a meaningful measure of the company's financial position, expressing the degree to which the liabilities are covered by the assets.

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“…Life expectancy at birth is the average number of years that a new born could expect to live, if subjected to the age-specific mortality rates of a given period. It is an indicator of mortality and health conditions [9].…”

Section: Life Expetancy (Le)mentioning

confidence: 99%

Power Law Behavior and Self-Similarity in Modern Industrial Accidents

Lopes

Machado

2015

Int. J. Bifurcation Chaos

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This paper analyzes several natural and man-made complex phenomena in the perspective of dynamical systems. Such phenomena are often characterized by the absence of a characteristic length-scale, long range correlations and persistent memory, which are features also associated to fractional order systems. For each system, the output, interpreted as a manifestation of the system dynamics, is analyzed by means of the Fourier transform. The amplitude spectrum is approximated by a power law function and the parameters are interpreted as an underlying signature of the system dynamics. The complex systems under analysis are then compared in a global perspective in order to unveil and visualize hidden relationships among them.

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Time series analysis and stochastic forecasting: An econometric study of mortality and life expectancy

Abstract: C43, C53, J10, Mortality, life expectancy, stochastic forecasting,

Cited by 30 publications

References 25 publications

A Dynamic Extension of the Period Life Table

A Dynamic Extension of the Period Life Table

The Poisson Log-Bilinear Lee-Carter Model

Power Law Behavior and Self-Similarity in Modern Industrial Accidents

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