Department of Economics and Business Economics

Forecasting Causes of Death using Compositional Data Analysis: the Case of Cancer Deaths

Research output: Working paperResearch

Documents

  • rp19_07

    Final published version, 714 KB, PDF document

  • Søren Kjærgaard, Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, Denmark
  • Yunus Emre Ergemen
  • Malene Kallestrup-Lamb
  • Jim Oeppen, Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, Denmark
  • Rune Lindahl-Jacobsen, Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, Denmark
Cause-specific mortality forecasting is often based on predicting cause-specific death rates independently. Only a few methods have been suggested that incorporate dependence among causes. An attractive alternative is to model and forecast cause-specific death distributions, rather than mortality rates, as dependence among the causes can be incorporated directly. We follow this idea and propose two new models which extend the current research on mortality forecasting using death distributions. We find that adding age, time, and cause-specific weights and decomposing both joint and individual variation among different causes of death increased the forecast accuracy of cancer deaths using data for French and Dutch populations
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages31
Publication statusPublished - 9 May 2019
SeriesCREATES Research Papers
Number2019-07

See relations at Aarhus University Citationformats

Download statistics

No data available

ID: 152571985