Demographic forecasting using functional data analysis

7 September 2010

  • University of Wollongong, 8 September 2010.
  • Statistical Society of Australia, Victorian Branch, 28 September 2010.
  • Updated version. September 2012.

Abstract:

Functional time series are curves that are observed sequentially in time. In demography, such data arise as the curves formed by annual death rates as a function of age or annual fertility rates as a function of age. I will discuss methods for describing, modelling and forecasting such functional time series data. Challenges include:

  • developing useful graphical tools (I will illustrate a functional version of the boxplot);
  • dealing with outliers (e.g., death rates have outliers in years of wars or epidemics);
  • cohort effects (how can we identify and allow for these in the forecasts);
  • synergy between groups (e.g, we expect male and female mortality rates to evolve in a similar way in the future);
  • deriving prediction intervals for forecasts;
  • how to combine the mortality and fertility forecasts to obtain forecasts of the total population.

I will illustrate the ideas using data from Australia and France.

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