Phantoms Never Die: Living with Unreliable Population Data

Journal of the Royal Statistical Society, 2016

31 Pages Posted: 22 Mar 2016

See all articles by Andrew J. G. Cairns

Andrew J. G. Cairns

Heriot-Watt University - Department of Actuarial Science & Statistics

David P. Blake

City University London - Cass Business School

Kevin Dowd

Nottingham University Business School (NUBS)

Amy R. Kessler

Prudential Retirement

Multiple version iconThere are 2 versions of this paper

Date Written: December 21, 2014

Abstract

The analysis of national mortality trends is critically dependent on the quality of the population, exposures and deaths data that underpin death rates.We develop a framework that allows us to assess data reliability and to identify anomalies, illustrated, by way of example, using England and Wales population data. First, we propose a set of graphical diagnostics that help to pinpoint anomalies. Second, we develop a simple Bayesian model that allows us to quantify objectively the size of any anomalies. Two-dimensional graphical diagnostics and modelling techniques are shown to improve significantly our ability to identify and quantify anomalies. An important conclusion is that significant anomalies in population data can often be linked to uneven patterns of births of people in cohorts born in the distant past. In the case of England and Wales, errors of more than 9% in the estimated size of some birth cohorts can be attributed to an uneven pattern of births.We propose methods that can use births data to improve estimates of the underlying population exposures. Finally, we consider the effect of anomalies on mortality forecasts and annuity values, and we find significant effects for some cohorts. Our methodology has general applicability to other sources of population data, such as the Human Mortality Database.

Keywords: Baby boom; Cohort–births–deaths exposures methodology; Convexity adjustment ratio; Deaths; Graphical diagnostics; Population data

Suggested Citation

Cairns, Andrew J. G. and Blake, David P. and Dowd, Kevin and Kessler, Amy R., Phantoms Never Die: Living with Unreliable Population Data (December 21, 2014). Journal of the Royal Statistical Society, 2016. Available at SSRN: https://ssrn.com/abstract=2752534

Andrew J. G. Cairns

Heriot-Watt University - Department of Actuarial Science & Statistics ( email )

Edinburgh, Scotland EH14 4AS
United Kingdom

David P. Blake (Contact Author)

City University London - Cass Business School ( email )

London, EC2Y 8HB
Great Britain
+44 (0) 20-7040-5143 (Phone)
+44 (0) 20-7040-8881 (Fax)

Kevin Dowd

Nottingham University Business School (NUBS) ( email )

Jubilee Campus
Wollaton Road
Nottingham, NG8 1BB
United Kingdom

Amy R. Kessler

Prudential Retirement ( email )

280 Trumbull Street
Hartford, CT
United States

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