Modelling and forecasting mortality in Spain

Debón, Ana; Montes, Francisco; Puig, Francisco

doi:10.1016/j.ejor.2006.07.050

Cited by 53 publications

(46 citation statements)

References 16 publications

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“…This may be a problem if we are modelising death probabilities that are solved by performing a logit transformation. It is for that reason that we apply this model to logit death probability q xt as Debón et al (2008) [8],…”

Section: Lee-carter Modelmentioning

confidence: 99%

Breast cancer mortality in Spain: Has it really declined for all age groups?

et al. 2012

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Introduction: Incidence in Spain due to breast cancer has increased over the last few years, nevertheless mortality has decreased, especially since 1992. Despite this general decrease in mortality, the intensity has been different in all age groups. The main objective of this paper is to fit the mortality due to breast cancer for different age groups in Spain during Results: We found an evident decreasing trend during the last few years of the fit (1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008), furthermore we expect a decrease in the mortality due to breast cancer during the years of the forecast. Despite this decrease, the mortality rates have different intensities for each age group. Younger and central ages groups can notice an evident decreasing trend and extend it to forecast, on the other hand, for older age groups the trend in mortality seems to be stable.

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Section: Lee-carter Modelmentioning

confidence: 99%

Breast cancer mortality in Spain: Has it really declined for all age groups?

et al. 2012

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“…A detailed description of the model and its adjustment by different methods can be found in Debón et al (2008b).…”

Section: Lee-carter Model and Bootstrap Confidence Intervalsmentioning

confidence: 99%

“…All these indicators can be projected using the projections of q xt , obtained from an adequate methodology, in our study the Lee-Carter model (Lee and 3 Carter, 1992;Brouhns et al, 2002;Debón et al, 2008b). We used the simple Lee-Carter model as, while the other versions improved the adjustment, the goodness of fit had little influence on the mortality indicators (Lazar et al, 2009;Debón et al, 2010) and this paper is focused on the evolution of these indicators.…”

Section: Introductionmentioning

confidence: 99%

“…To study its future evolution, the mortality ratios have to be projected using an adequate methodology, namely the Lee-Carter model (Lee and Carter, 1992;Brouhns et al, 2002;Debón et al, 2008b). With the aim of incorporating the uncertainty measures suggested by Pedroza (2006) into predictions, confidence intervals are obtained for these predictions.…”

Section: Introductionmentioning

confidence: 99%

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Temporal Evolution of Mortality Indicators

Debón

Martínez-Ruiz

Montes

2012

North American Actuarial Journal

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In Spain, as in other developed countries, there have been significant changes in mortality patterns during the 20th and 21st centuries. One reflection of these changes is life expectancy, which has improved in this period, though the robustness of this indicator prevents these changes from being of the same order as those for the probability of death, q xt . If, moreover, we bear in mind that life expectancy offers no information as to whether this improvement is the same for different age groups, it is important and necessary to turn to other mortality indicators whose past and future evolution in Spain we are going to study.These indicators are applied to Spanish mortality data for the period 1981-2008, for the age range 0 to 99. To study its future evolution, the mortality ratios have to be projected using an adequate methodology, namely the Lee-Carter model (Lee and Carter, 1992;Brouhns et al., 2002;Debón et al., 2008b). With the aim of incorporating the uncertainty measures suggested by Pedroza (2006) into predictions, confidence intervals are obtained for these predictions. These intervals can be calculated using the methodology which Lee and Carter apply in their original article for expected lifetime confidence intervals, but they only take into account the error in the prediction of the mortality index k t obtained from the ARIMA model adjusted to its temporal series, excluding other sources of error such as that introduced by estimations of the other parameters in the model. That is why bootstrap procedures are preferred, as used in Koissi et al. (2006), permitting the combination of all sources of uncertainty.

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“…This model is widely employed both in the academic literature and by practitioners working for pension funds, life insurance companies, and public pension systems. The original approach has seen several extensions (see, e.g., Lee and Miller, 2001;Brouhns, Denuit, and Vermunt, 2002;Renshaw and Haberman, 2006), and has been applied to mortality data of many countries, including the G7 countries (Tuljapurkar, Li, and Boe, 2000), Spain (Debón, Montes, and Puig, 2008), Australia (Booth, Maindonald, and Smith, 2002), and China and South Korea (Li, Lee, and Tuljapurkar, 2004). Variations of the Lee-Carter model have been employed to forecast other demographic variables, such as fertility rates or migration flows (Girosi and King, 2008;Härdle and Myšičková, 2009).…”

Section: Stochastic Mortality Modelingmentioning

confidence: 99%

Stochastic Mortality, Macroeconomic Risks, and Life Insurer Solvency

2012

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Motivated by a recent demographic study establishing a link between macroeconomic fluctuations and the mortality index k t in the Lee-Carter model, we assess the impact of macroeconomic fluctuations on the solvency of a life insurance company. Liabilities in our stochastic simulation framework are driven by a GDP-linked variant of the Lee-Carter mortality model. Furthermore, interest rates and stock prices are allowed to react to changes in GDP, which itself is modeled as a stochastic process. Our results show that insolvency probabilities are significantly higher when the reaction of mortality rates to changes in GDP is incorporated.

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Modelling and forecasting mortality in Spain

Cited by 53 publications

References 16 publications

Breast cancer mortality in Spain: Has it really declined for all age groups?

Breast cancer mortality in Spain: Has it really declined for all age groups?

Temporal Evolution of Mortality Indicators

Stochastic Mortality, Macroeconomic Risks, and Life Insurer Solvency

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