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Published online by Cambridge University Press: 11 August 2014
This paper describes the use of time series analysis in the solution of a problem arising in social insurance. As part of a model which estimates the future cost of unemployment benefit the Government Actuary's Department (GAD) is required to forecast the proportion of the unemployed in future calendar quarters, who are male. The format of the paper is to describe forecasting in general terms in §1 and the particular problem under consideration in §2. In subsequent sections, the data available (§ 3), the existing forecasting model (§ 4) and alternative time series models (§§ 5–8) are described.
The everyday job of the actuary involves the estimation of a future series of events. Examples include the estimation of future streams of liability outgo and asset income in life assurance, the run-off of outstanding claims in nonlife insurance, and the future numbers of persons in a subgroup of the total population. This estimation can be qualitative or quantitative, short-term or long-term, deterministic or stochastic and will involve the establishment of a mathematical-statistical model, and the determination of the relevant parameters by an analysis of the data available.