Torben M. Andersen, Aarhus University
“Adjusting Retirement Ages to Longevity: Health, Incentives and Flexibility”
As a response to increasing longevity, retirement ages are increased to ensure fiscal sustainability and intergenerational balance in net-contributions to the welfare state. In Denmark, and many other countries, retirement ages are explicitly linked to longevity. Since longevity increases are associated with so-called healthy ageing for the majority of the population this is a viable policy option. However, heterogeneity in morbidity and mortality raise questions on the distributional implications of such a policy. The possibilities of differentiating retirement ages based on health, work capability, working life careers are discussed. The main question is whether early or flexible retirement should be based on simple rules related to observable characteristics or screening based on test in each individual case. The implications of these different approaches are discussed in terms of targeting, incentives, insurance and distribution.
David Blake, Cass Business School
“Still Living with Mortality: The Longevity Risk Transfer Marker after One Decade”
This presentation updates Living with Mortality published in 2006. It describes how the longevity risk transfer market has developed over the intervening period, and, in particular, how insurance-based solutions – buy-outs, buy-ins and longevity insurance – have triumphed over capital markets solutions that were expected to dominate at the time. Some capital markets solutions – longevity-spread bonds, longevity swaps, q-forwards, and tail-risk protection – have come to market, but the volume of business has been disappointingly low. The reason for this is that when market participants compare the index-based solutions of the capital markets with the customized solutions of insurance companies in terms of basis risk, credit risk, regulatory capital, collateral, and liquidity, the former perform on balance less favourably despite a lower potential cost. We discuss the importance of stochastic mortality models for forecasting future longevity and examine some applications of these models, e.g., determining the longevity risk premium and estimating regulatory capital relief. The longevity risk transfer market is now beginning to recognize that there is insufficient capacity in the insurance and reinsurance industries to deal fully with demand and new solutions for attracting capital markets investors are now being examined – such as longevity-linked securities and reinsurance sidecars.
Andrew J.G. Cairns, Heriot-Watt University
“Forecasting Socio-Economic Differences in the Mortality of Danish Males”
We investigate and model how the mortality of Danish males aged 55-94 has changed over the period 1985-2012. We divide the population into ten socio-economic subgroups using a new measure of affluence that combines wealth and income reported on the Statistics Denmark national register database. The affluence index, in combination with sub-group lockdown at age 67, is shown to provide consistent sub-group rankings based on crude death rates across all ages and over all years in a way that improves significantly on previous studies that have focused on life expectancy. The gap between the most and least affluent is confirmed to be widest at younger ages and has widened over time.
We introduce a new multi-population mortality model that fits the historical mortality data well and generates smoothed death rates that capture the essential character of the raw data. The model produces bio-demographically-reasonable forecasts of mortality rates that preserve the sub-group rankings at all ages. It also satisfies reasonableness criteria related to the term structure of correlations across ages and over time through consideration of future death and survival rates.
David Laibson, Harvard University
“Behavioral Finance and Pension Economics”
Research in behavioral economics has provided support for the hypothesis that some households need help accumulating adequate retirement savings. However, the nature of that support remains an open question, with some behavioral economists advocating soft paternalism (e.g., auto-enrollment in voluntary savings systems) and other advocating a hybrid of hard paternalism (e.g., mandatory retirement savings) and soft paternalism. In this talk I discuss the evidence that argues that households left on their own will not save enough. I go on to explain why soft paternalism is not sufficient on its own to solve these savings problems.
Katja Mann, Copenhagen Business School
“External Asset Positions, Demography and Life-cycle Portfolio Choice”
How do demographic differences between regions affect external positions in safe and risky assets? We answer this question focusing on the US vis-à-vis 15 European Union member states. The US bilateral position is characterized by risky assets alongside safe liabilities. At the same time, the US population is relatively younger. We present a structural model of two fully integrated regions, which differ by the age structure of their populations. There are multiple overlapping generations of agents, who choose a portfolio of safe and risky assets over the life-cycle. We show that the younger region has a higher relative demand for risky assets, which induces international asset trades. In a simulation starting in 1990, we replicate the observed positions between the US and the European countries both in sign and in magnitude. We predict the risk asymmetry to persist until the end of the century, whereas both safe and risky returns decline persistently.
Claus Munk, Copenhagen Business School
“Designing mandatory pension plans”
In Denmark and several other countries, workers must participate in a defined contribution pension plan primarily characterized by a predetermined contribution rate, investment strategy, and retirement payout policy. In a life-cycle utility maximization model, we determine the individual's maximum utility for any predetermined characteristics of the pension scheme, taking into account that the individual can optimally manage liquid private investments alongside the mandatory and illiquid pension savings. Then we maximize again to find the optimal pension plan characteristics for the individual saver. We consider the case in which the individual is fully rational and has access to the same assets as the pension fund, but also cases in which the fund has access to superior investment opportunities, or the individual is subject to specific behavioral biases. We calculate the welfare gain the individual would obtain if an existing suboptimal pension plan was replaced by the derived optimal plan.
James Vaupel, University of Southern Denmark: “Demographic Changes: What Do We Know?”
“The Rise in Danish Life Expectancy and the Changing Inequalities in Pension Lifespans”
James Vaupel will summarize the rise in Danish life expectancy since 1850 and will then present various forecasts of the rise in the future. He will integrate the forecasts to produce a composite forecast, with uncertainty bands, of life expectancy at birth as well as the age when remaining life expectancy falls to 14.5 years, for males, females and the total population of Denmark. He will then present data on inequalities in pension lifespans, focusing first on the simple case when everyone retires at 65 so that a person’s pension lifespan is simply age at death minus 65. He will summarize the inequalities by various measures, including the Gini coefficient and the coefficient of variation. He will briefly describe how the simple case of retirement at 65 can be generalized to a more realistic analysis. Finally, he will propose a radically new pension policy to reduce inequalities in pension lifespans.