Deriving trends in life expectancy by the National Statistics Socio‐economic Classification using the ONS Longitudinal Study

Johnson, Brian Alan

doi:10.1057/hsq.2011.2

Cited by 13 publications

(12 citation statements)

References 8 publications

(10 reference statements)

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“…For example, it is known that mortality rates differ between manual and non-manual workers (Johnson 2011), between different geographical regions (Office for National Statistics 2011), and between birth cohorts (Willetts 2004). There has been concern that companies' mortality assumptions may not be up-to-date, failing to reflect increases in life expectancy (Pensions Regulator 2006;Club Vita 2011).…”

Section: Regulatory Backgroundmentioning

confidence: 99%

Discretion in accounting for pensions under IAS 19: using the ‘magic telescope’?

Billings

O’Brien

Woods

et al. 2016

Accounting and Business Research

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We use a panel data set of UK-listed companies over the period 2005 to 2009 to analyse the actuarial assumptions used to value pension plan liabilities under IAS 19. The valuation process requires companies to make assumptions about financial and demographic variables, notably discount rate, price inflation, salary inflation, and mortality/life expectancy of plan members/beneficiaries.We use regression analysis to analyse the relationships between these key assumptions (except mortality, where disclosures are limited) and companyspecific factors such as the pension plan funding position and duration of pension liabilities. We find evidence of selective 'management' of the three assumptions investigated, although the nature of this appears to differ from the findings of US authors. We conclude that IAS 19 does not prevent the use of managerial discretion, particularly by companies whose pension plan funding positions are weak, thereby reducing the representational faithfulness of the reported pension figures. We also highlight that the degree of discretion used reflects the extent to which IAS 19 defines how the assumptions are to be determined. We therefore suggest that companies should be encouraged to justify more explicitly their choice of assumptions.

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Section: Regulatory Backgroundmentioning

confidence: 99%

Discretion in accounting for pensions under IAS 19: using the ‘magic telescope’?

Billings

O’Brien

Woods

et al. 2016

Accounting and Business Research

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“…In particular, there is a well established inverse relationship between socio-economic circumstances -whether measured by educational attainment, occupation, income or area deprivation -and mortality, with higher socio-economic subgroups having lower mortality rates and, in most cases, also experiencing faster mortality improvements than lower socioeconomic subgroups (see, e.g., Shkolnikov et al (2006); Johnson (2011);Tarkiainen et al (2012); Raleigh and Kiri (1997)). …”

Section: Introductionmentioning

confidence: 99%

On the Modeling and Forecasting of Socioeconomic Mortality Differentials: An Application to Deprivation and Mortality in England

Villegas

Haberman

2014

North American Actuarial Journal

105

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This is the submitted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractIn any country, mortality rates and indices such as life expectancy usually differ across subpopulations, for example, defined by gender, geographic area or socio-economic variables (e.g. occupation, level of education, income). These differentials, and in particular those related to socio-economic circumstances, pose important challenges for the design of public policies for tackling social inequalities, as well as for the design of pension systems and the management of longevity risk in pension funds and annuity portfolios. We discuss the suitability for the modelling and forecasting of socio-economic differences in mortality of several multiple population extensions of the Lee-Carter model, including a newly introduced relative model based on the modelling of the mortality in socio-economic subpopulations alongside the mortality of a reference population. Using England mortality data for socioeconomic subpopulations defined using a deprivation index, we show that this new relative model exhibits the best results in terms of goodness of fit and ex-post forecasting performance. We then use this model to derive projections of deprivation specific mortality rates and life expectancies at pensioner ages and analyse the impact of socio-economic differences in mortality on the valuation of annuities.

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“…This increase in deaths, particularly in the upper age groups of the range, remains unexplained. A general comparison with longer-term trends in female life expectancy, (Johnson, 2011) suggested that the pattern for the most advantaged classes (Higher managers and professionals and Lower managers and professionals) was reflected in the results of the current study, with these classes experiencing the greatest growth in life expectancy over twenty years and the greatest decline in mortality between 2001 and 2006. However, there is no indication in the life expectancy estimates to suggest a poor trend performance in mortality rate for Semi-routine occupations, nor is there evidence of a greater than average recent improvement in the mortality of the Routine class, as suggested by the results from the current study.…”

Section: Discussionmentioning

confidence: 51%

Trends in socio-economic inequalities in female mortality, 2001–08. Intercensal estimates for England and Wales

Johnson

Al-Hamad

2011

Health Stat Q

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Socio-economic inequalities in the mortality rates of women appeared to increase between 2001 and 2008. However, the results for women were not as clear as for men with four out of the seven analytic NS-SEC classes not having a statistically significant downward trend in mortality. The degree of annual volatility in the measures suggests that at the current low levels of mortality of working age women, the LFS could not be used to provide population denominators below the national level. Possibly, three-year moving averages would be better trend indicators, but this would reduce the timeliness of the data to some extent.

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Deriving trends in life expectancy by the National Statistics Socio‐economic Classification using the ONS Longitudinal Study

Abstract: Background

Cited by 13 publications

References 8 publications

Discretion in accounting for pensions under IAS 19: using the ‘magic telescope’?

Discretion in accounting for pensions under IAS 19: using the ‘magic telescope’?

On the Modeling and Forecasting of Socioeconomic Mortality Differentials: An Application to Deprivation and Mortality in England

Trends in socio-economic inequalities in female mortality, 2001–08. Intercensal estimates for England and Wales

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