The United Kingdom Examining the Switch from Low Public Pensions to High-Cost Private Pensions.
David Blake
Introduction
The United Kingdom is one of the few countries in Europe that is not facing a serious pensions crisis. The reasons for this are straightforward: Its state pensions (both in terms of the replacement ratio and as a proportion of average earnings) are among the lowest in Europe; it has a longstanding funded private pension sector; its population is aging less rapidly than elsewhere in Europe; and it governments have, since the beginning of the 1980s, taken measures to prevent the development of a pension crisis. These measures have involved making systematic cuts in unfunded state pension provisions and increasingly transferring the burden of providing pensions to the funded private sector. The United Kingdom is not entitled to be complacent, however, because there remain some serious and unresolved problems with private-sector provision.
This paper reviews the current system of pension provision in the United Kingdom, describes and analyzes defects in the Thatcher-Major governments’ reforms that brought us to the present system, examines and assesses the reforms of the Blair government, and then identifies the problems that remain unresolved and how those problems might be addressed.
The paper ends with an explanation of how the United Kingdom has been able to introduce changes relatively peacefully when attempts by continental European countries to reform their pension systems have frequently led to riots in the streets.
Longevity Risk and Capital Markets: The 2022-23 Update
David Blake and Johnny Li
Abstract
We discuss the papers presented at Longevity 17: The Seventeenth International Longevity Risk and Capital Markets Solutions Conference that was held online on 12-13 September 2022. We also discuss 1) the development of the longevity risk transfer market since it started in 2005-06 and 2) key factors that will affect the future of the market: peak cash flows; the volatility of life expectancy trends; population aging; the aging process and anti-aging treatments; preventative health care and later life wellness; artificial intelligence, machine learning, robotics, and quantum computing; the implications of global aging for financial markets and economic growth; and climate change and sustainable development.
Longevity Risk and Capital Markets: The 2021-2022 Update
David Blake, Malene Kallestrup-Lamb and Jesper Rangvid
Abstract
This Special Issue of the Journal of Demographic Economics contains 10 contributions to the academic literature all dealing with longevity risk and capital markets. Draft versions of the papers were presented at Longevity 16: The Sixteenth International Longevity Risk and Capital Markets Solutions Conference that was held in Helsingør near Copenhagen on 13-14 August 2021. It was hosted by PerCent at Copenhagen Business School and the Pensions Institute at
City, University of London. Longevity risk and related capital market solutions have grown increasingly important in recent years, both in academic research and in the markets we refer to as the Life Market, i.e., the capital market that trades longevity-linked assets and liabilities.1 Mortality improvements around the world are putting more and more pressure on governments, pension funds, life insurance companies, as well as individuals, to deal with the longevity risk they face. At the same time, capital markets can, in principle, provide vehicles to hedge longevity risk effectively and transfer the risk from those unwilling or unable to manage it to those willing to invest in this risk in exchange for appropriate risk-adjusted returns or to those who have a counterpoising risk that longevity risk can hedge, e.g., life offices and reinsurers with mortality risk on their books. Many new investment products have been created both by the
insurance/reinsurance industry and by the capital markets. Mortality catastrophe bonds are an early example of a successful insurance-linked security. Some new innovative capital market solutions for transferring longevity risk include longevity (or survivor) bonds, longevity (or survivor) swaps, mortality (or q-) forward contracts and reinsurance sidecars (also called strategic reinsurance vehicles). The aim of the International Longevity Risk and Capital Markets Solutions Conferences is to bring together academics and practitioners from all over the world to discuss and analyze these exciting new developments.
Nudges and Networks: How to use Behavioural Economics to Improve the Life Cycles Savings-Consumption Balance.
David Blake
Abstract:
Many people find it difficult to start and maintain a retirement savings plan. We show how nudges can be used both the encourage people to save enough to provide an acceptable standard of living in retirement and to draw down their accumulated pension fund to maximize retirement spending, without the risk of either running out of money or leaving unintended bequests. Networks can help too, particularly employer-based networks. However, the nudges and networks are more likely to be effective if they have legislative backing and support.
Keywords:
nudges; networks; behavioural economics; life cycle savings-consumption; Save More Tomorrow (SMART) plans; Spend Optimally Throughout Retirement (SPEEDOMETER) plans.
JEL Classification:
D91
Good Practice Principles in Modelling Defined Contribution Pension Plans.
Kevin Dowd & David Blake
Abstract
We establish 16 Good practice principles for modelling defined contribution pension plans. These principles cover the following issues: model specification and calibration; modelling quantifiable uncertainty; modelling member choices; modelling member characteristics, such as occupation and gender; modelling plan charges; modelling longevity risk; modelling the post retirement period; integrating the pre- and post-retirement periods; modelling additional sources of income, such as the state pension and equity release; modelling extraneous factors, such as unemployment risk, activity rates, taxes and welfare entitlements; scenario analysis and stress testing; periodic updating of the model and changing assumptions; and overall fitness for purpose.
Keywords:
defined contribution pension plans; PensionMetrics methodology; OECD Roadmap for the Good Design of Defined Contribution Pension Plans; EOPA Good practices on Information Provision for DC Schemes: Enabling Occupational DC Scheme Members to Plan for Retirement
JEL Classification:
C15; C18; C63; C68; D14; D91.
Projecting Mortality Rates to Extreme Old Age with the CBDX Model
Kevin Dowd and David Blake
Abstract
We introduce a simple extension to the CBDX model to project cohort mortality rates to extreme old age. The proposed approach fits a polynomial to a sample of age effects, uses the fitted polynomial to project the age effects to ages beyond the sample age range, then splices the sample and projected age effects, and uses the spliced age effects to obtain mortality rates for the higher ages. The proposed approach can be used to value financial instruments such as life annuities that depend on projections of extreme old age mortality rates.
Key Words:
mortality rates, Cairns-Blake-Dowd mortality model, CBDX mortality model, projection, extreme old age, life annuities
JEL Classification:
G22, G23, J11
Quantifying loss aversion: Evidence from a UK population survey
David Blake, Edmund Cannon & Douglas Wright.
Abstract
We quantify differences in attitudes to loss from individuals with different demographic, personal and socio-economic characteristics. Our data are based on responses from an online survey of a representative sample of over 4000 UK residents and allow us to produce the most comprehensive analysis of the heterogeneity of loss aversion measures to date. Using the canonical model proposed by Tversky and Kahneman (1992), we show that responses for the population as a whole differ substantially from those typically provided by students (who form the basis of many existing studies of loss aversion). The average aversion to a loss of £500 relative to a gain of the same amount is 2.41, but loss aversion correlates significantly with characteristics such as gender, age, education, financial knowledge, social class, employment status, management responsibility, income, savings and home ownership. Other related factors include marital status, number of children, ease of savings, rainy day fund, personality type, emotional state, newspaper and political party. However, once we condition on all the profiling characteristics of the respondents, some factors, in particular gender, cease to be significant, suggesting that gender differences in risk and loss attitudes might be due to other factors, such as income differences.
Keywords
Loss aversion · Gender effects · Expected utility · Risk attitudes · Survey
data
JEL Classification
G40 · D40 · C83 · C90
A General Framework for Analysing the Mortality Experience of a Large Portfolio of Lives: With an Application to the UK Universities Superannuation Scheme
Andrew Cairns, David Blake, Kevin Dowd, Guy Coughlan, Owen Jones, and Jeffrey Rowney, Universities
Abstract
We report the results of an in-depth analysis of the mortality of pensioners in the
Universities Superannuation Scheme (USS), the largest funded pension scheme in
the UK and one with a highly educated and very homogeneous membership. The
USS experience was compared with English mortality subdivided into deprivation deciles using the Index of Multiple Deprivation (IMD).
USS was found to have significantly lower mortality than even IMD-10 (the least
deprived of the English deciles), but with similar mortality improvement rates to
that decile over the period 2005-2016. Higher pensions were found to predict lower mortality, but only weakly so, and only for persons who retired on the first day ofa month (mostly from active service).
We found that other potential covariates derived from an individual’s postcode (geographical region and the IMD associated with their local area) typically had noexplanatory power, although there was some evidence of a north-south divide. This lack of dependence is an important conclusion of the study and contrasts with other that consider the mortality of more heterogeneous scheme memberships.
Keywords:
Longevity Risk, Pensioners’ Mortality, Index of Multiple Deprivation,
Age Standardised Mortality Rate, Occupation.
Smart defaults: Determining the number of default funds in a pension scheme
David Blake, Mel Duffield, Ian Tonks, Alistair Haig, Dean Blower & Laura MacPhee
Abstract
We propose a new methodology for the smart design of the default investment fund(s) in occupational defined contribution pension schemes based on the observable characteristics of scheme members. Using a unique dataset of member risk attitudes and characteristics from a survey of a large UK pension scheme, we apply factor analysis to identify single factors for risk aversion, risk
capacity and ethical investment preferences, and then apply cluster analysis to these factors to identify two distinct groups of members across age cohorts. We find membership of these clusters depends on a number of personal characteristics, with the principal differentiating feature being that one group had previously engaged with the pension scheme, while the other had not. These
identified characteristics can be utilised in the design of smart default funds, including appropriate engagement strategies.
Smart Defaults : Determining the number of default funds in a pension scheme.
David Blake, Mel Duffield, Ian Tonks, Alistair Haig, Dean Blower and Laura MacPhee.
Abstract
We propose a new methodology for the smart design of the default investment fund(s) in occupational defined contribution pension schemes based on the observable characteristics of scheme members. Using a unique dataset of member risk attitudes and characteristics from a survey of a large UK pension scheme, we apply factor analysis to identify single factors for risk aversion, risk capacity and ethical investment preferences, and then apply cluster analysis to these factors to identify two distinct groups of members across age cohorts. We find membership of these clusters depends on a number of personal characteristics, with the principal differentiating feature being that one group had previously engaged with the pension scheme, while the other had not. These identified characteristics can be utilised in the design of smart default funds, including appropriate engagement strategies.
Key words:
defined contribution pension schemes, investment choices, default
investment funds, cluster analysis, risk attitude, risk capacity.
JEL: G11, G41
