Mortality Effects of Temperature Changes in the United Kingdom

Seklecka, Malgorzata; Pantelous, Athanasios A.; O’Hare, Colin

doi:10.2139/ssrn.2810968

Cited by 2 publications

(15 citation statements)

References 48 publications

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“…In this section, a brief overview of the TRM model proposed recently by is provided, which drives the analysis of the following sections. It should be mentioned here that the TRM model provides a smooth expression for the calculation of central mortality rates, m x , t , which are a ratio of deaths, D x , t counts by a single age x and year t , and exposure‐to‐risk, E x , t , data in the same interval.…”

Section: Temperature‐related Mortality Modelmentioning

confidence: 99%

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The impact of parameter uncertainty in insurance pricing and reserve with the temperature‐related mortality model

Seklecka

Pantelous

O’Hare

2018

Journal of Forecasting

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Changes in mortality rates have an impact on the life insurance industry, the financial sector (as a significant proportion of the financial markets is driven by pension funds), governmental agencies, and decision makers and policymakers. Thus the pricing of financial, pension and insurance products that are contingent upon survival or death and which is related to the accuracy of central mortality rates is of key importance. Recently, a temperature‐related mortality (TRM) model was proposed by Seklecka et al. (Journal of Forecasting, 2017, 36(7), 824–841), and it has shown evidence of outperformance compared with the Lee and Carter (Journal of the American Statistical Association, 1992, 87, 659–671) model and several others of its extensions, when mortality‐experience data from the UK are used. There is a need for awareness, when fitting the TRM model, of model risk when assessing longevity‐related liabilities, especially when pricing long‐term annuities and pensions. In this paper, the impact of uncertainty on the various parameters involved in the model is examined. We demonstrate a number of ways to quantify model risk in the estimation of the temperature‐related parameters, the choice of the forecasting methodology, the structures of actuarial products chosen (e.g., annuity, endowment and life insurance), and the actuarial reserve. Finally, several tables and figures illustrate the main findings of this paper.

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Section: Temperature‐related Mortality Modelmentioning

confidence: 99%

“…Recently, Seklecka, Pantelous, and O'Hare () introduced a new temperature‐related mortality (TRM) model in which an additional factor related to climate change was included. The main structure of the TRM model is based on the celebrated Lee and Carter () model and its numerous extensions.…”

Section: Introductionmentioning

confidence: 99%

The impact of parameter uncertainty in insurance pricing and reserve with the temperature‐related mortality model

Seklecka

Pantelous

O’Hare

2018

Journal of Forecasting

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“…That increase in all age intervals is primarily due to several factors, such as socioeconomic, medical improvements, lifestyle, living environment, climate change, and many others (Cairns, Kallestrup-Lamb, Rosenskjold, Blake, & Dowd, 2016;French & O'Hare, 2013Hanewald, 2011;Niu & Melenberg, 2014;Seklecka et al, 2017;Tapia Granados, 2008. That increase in all age intervals is primarily due to several factors, such as socioeconomic, medical improvements, lifestyle, living environment, climate change, and many others (Cairns, Kallestrup-Lamb, Rosenskjold, Blake, & Dowd, 2016;French & O'Hare, 2013Hanewald, 2011;Niu & Melenberg, 2014;Seklecka et al, 2017;Tapia Granados, 2008.…”

Section: Extrapolative Mortality Modelingmentioning

confidence: 99%

“…Then, Brouhns, Denuit, and Vermunt (2002) improved the fitting of the LC model by describing the number of deaths D x,t as a Poisson distribution with parameter (E x,t m x,t ). Indeed, their method has been well adopted by many other authors (Cairns et al, 2009;Plat, 2009;O'Hare & Li, 2012;Renshaw & Haberman, 2006;Seklecka et al, 2017). Indeed, their method has been well adopted by many other authors (Cairns et al, 2009;Plat, 2009;O'Hare & Li, 2012;Renshaw & Haberman, 2006;Seklecka et al, 2017).…”

Section: Estimation and Quality Of Fittingmentioning

confidence: 99%

“…As in previous studies (e.g., Niu & Melenberg, 2014;Seklecka, Pantelous, & O'Hare, 2017, 2018, our forecasting methodology is a combination of explanation and extrapolation methods (Booth & Tickle, 2008; see Section 2 for more details). As in previous studies (e.g., Niu & Melenberg, 2014;Seklecka, Pantelous, & O'Hare, 2017, 2018, our forecasting methodology is a combination of explanation and extrapolation methods (Booth & Tickle, 2008; see Section 2 for more details).…”

Section: Introductionmentioning

confidence: 99%

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Mortality effects of economic fluctuations in selected eurozone countries

Seklecka¹,

Lazam

Pantelous

et al. 2018

Journal of Forecasting

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Socioeconomic status is commonly conceptualized as the social standing or well‐being of an individual or society. Higher socioeconomic status has long been identified as a contributing factor for mortality improvement. This paper studies the impact of macroeconomic fluctuations (having gross domestic product (GDP) as a proxy) on mortality for the nine most populous eurozone countries. Based on the statistical analysis between the time‐dependent indicator of the Lee and Carter (Journal of the American Statistical Association, 1992, 87(419), 659–671) model and GDP, and adaptation of the good features of the O'Hare and Li (Insurance: Mathematics and Economics, 2012, 50, 12–25) model, a new mortality model including this additional economic‐related factor is proposed. Results for male and female from ages between 0 and 89, and similar for unisex data, are provided. This new model shows a better fitting and more plausible forecast among a significant number of eurozone countries. An in‐depth analysis of our findings is provided to give a better understanding of the relationship between mortality and GDP fluctuations.

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Mortality Effects of Temperature Changes in the United Kingdom

Cited by 2 publications

References 48 publications

The impact of parameter uncertainty in insurance pricing and reserve with the temperature‐related mortality model

The impact of parameter uncertainty in insurance pricing and reserve with the temperature‐related mortality model

Mortality effects of economic fluctuations in selected eurozone countries

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