Structural Breaks in Mortality Models and their Consequences

In recent years, the issue of life expectancy has become of upmost importance to pension providers, insurance companies and the government bodies in the developed world. Significant and consistent improvements in mortality rates and, hence, life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data in order to anticipate future life expectancy and, hence, quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age and cohort, and forecast these trends into the future using standard statistical methods. The modeling approaches used failed to capture the effects of any structural change in the trend and, thus, potentially produced incorrect forecasts of future mortality rates. In this paper, we look at a range of leading stochastic models of mortality and test for structural breaks in the trend time series.

Identifying Structural Breaks in Stochastic Mortality Models

In recent years, the issue of life expectancy has become of utmost importance to pension providers, insurance companies, and government bodies in the developed world. Significant and consistent improvements in mortality rates and hence life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data to anticipate future life expectancy and hence quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age, and cohort and forecast these trends into the future by using standard statistical methods. These approaches rely on the assumption that structural breaks in the trend do not exist or do not have a significant impact on the mortality forecasts. Recent literature has started to question this assumption. In this paper, we carry out a comprehensive investigation of the presence or of structural breaks in a selection of leading mortality models. We find that structural breaks are present in the majority of cases. In particular, we find that allowing for structural break, where present, improves the forecast result significantly.

Trends and Determinants of Work-Retirement Transitions under Changing Institutional Conditions: Germany, England and Japan compared

Many governments world-wide are promoting longer working life due to the social and economic repercussions of demographic change. However, not all workers are equally able to extend their employment careers. Thus, while national policies raise the overall level of labour market participation, they might create new social and labour market inequalities. This paper explores how institutional differences in the United Kingdom, Germany and Japan affect individual retirement decisions on the aggregate level, and variations in individuals’ degree of choice within and across countries. We investigate which groups of workers are disproportionately at risk of being ‘pushed’ out of employment, and how such inequalities have changed over time. We use comparable national longitudinal survey datasets focusing on the older population in England, Germany and Japan. Results point to cross-national differences in retirement transitions. Retirement transitions in Germany have occurred at an earlier age than in England and Japan. In Japan, the incidence of involuntary retirement is the lowest, reflecting an institutional context prescribing that employers provide employment until pension age, while Germany and England display substantial proportions of involuntary exits triggered by organisational-level redundancies, persistent early retirement plans or individual ill-health.

Trade union responses to ageing workforces in the UK and Germany

Ageing workforces are placing conflicting pressures on European trade unions in order to, on the one hand, protect pensions and early retirement routes, and, on the other, promote human resource management (HRM) policies geared towards enabling their older members to extend working life. Using interviews from German and United Kingdom (UK) trade unions, we discuss how unions are both constrained and enabled by pre-existing institutional structures in advocating approaches to age management. In Germany, some unions use their strong institutional role to affect public policy and industrial change at national and sectoral levels. UK unions have taken a more defensive approach, focused on protecting pension rights. The contrasting varieties of capitalism, welfare systems and trade unions’ own orientations are creating different pressures and
mechanisms to which unions need to respond. While the German inclusive system is providing unions with mechanisms for negotiating collectively at the national level, UK unions’ activism remains localized.

Modelling mortality: Are we heading in the right direction?

Predicting life expectancy has become of upmost importance in society. Pension providers, insurance companies, government bodies and individuals in the developed world have a vested interest in understanding how long people will live for. This desire to better understand life expectancy has resulted in an explosion of stochastic mortality models many of which identify linear trends in mortality rates by time. In making use of such models for forecasting purposes we rely on the assumption that the direction of the linear trend (determined from the data used for fitting purposes) will not change in the future, recent literature has started to question this assumption. In this paper we carry out a comprehensive investigation of these types of models using male and female data from 30 countries and using the theory of structural breaks to identify changes in the extracted trends by time. We find that structural breaks are present in a substantial number of cases, that they are more prevalent in male data than in female data, that the introduction of additional period factors into the model reduces their presence, and that allowing for changes in the trend improves the fit and forecast substantially.