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Time series analysis and stochastic forecasting: An econometric study of mortality and life expectancy

Abstract

Methods for time series modeling of mortality and stochastic forecasting of life expectancies are explored, using Canadian data. Consideration is given first to alternative indexes of aggregate mortality. Age-sex group system models are then estimated. Issues in the forecasting of life expectancies are discussed and their quantitative implications investigated. Experimental stochastic forecasts are presented and discussed, based on nonparametric, partially parametric, and fully parametric methods, representing alternatives to the well known Lee-Carter method. Some thoughts are offered on the interpretation of historical data in generating future probability distributions, and on the treatment of demographic uncertainty in long-run policy planning.

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Correspondence to Frank T. Denton.

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All correspondence to Frank T. Denton. This paper is a revised version of one presented at the Annual Congress of the European Society for Population Economics, Athens, Greece, June 2001. The underlying work was carried out as part of the SEDAP (Social and Economic Dimensions of an Aging Population) Research Program supported by the Social Sciences and Humanities Research Council of Canada, Statistics Canada and the Canadian Institute for Health Information. Ronald Lee provided comments that were very helpful in revising an earlier version of the paper. We thank him and participants at the ESPE session at which that version was presented. We thank also the Journal's anonymous referees. Responsible editor: Junsen Zhang.

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Denton, F.T., Feaver, C.H. & Spencer, B.G. Time series analysis and stochastic forecasting: An econometric study of mortality and life expectancy. J Popul Econ 18, 203–227 (2005). https://doi.org/10.1007/s00148-005-0229-2

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  • DOI: https://doi.org/10.1007/s00148-005-0229-2

JEL Classification

  • C43
  • C53
  • J10

Keywords

  • Mortality
  • life expectancy
  • stochastic forecasting