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Stochastic population forecasts using functional data models for mortality, fertility and migration

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Author Info
Rob J Hyndman ()
Heather Booth

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Abstract

Age-sex-specific population forecasts are derived through stochastic population renewal using forecasts of mortality, fertility and net migration. Functional data models with time series coefficients are used to model age-specific mortality and fertility rates. As detailed migration data are lacking, net migration by age and sex is estimated as the difference between historic annual population data and successive populations one year ahead derived from a projection using fertility and mortality data. This estimate, which includes error, is also modeled using a functional data model. The three models involve different strengths of the general Box-Cox transformation chosen to minimise out-of-sample forecast error. Uncertainty is estimated from the model, with an adjustment to ensure the one-step-forecast variances are equal to those obtained with historical data. The three models are then used in the Monte Carlo simulation of future fertility, mortality and net migration, which are combined using the cohort-component method to obtain age-specific forecasts of the population by sex. The distribution of forecasts provides probabilistic prediction intervals. The method is demonstrated by making 20-year forecasts using Australian data for the period 1921-2003.

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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 14/06.

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Length: 34 pages
Date of creation: May 2006
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Handle: RePEc:msh:ebswps:2006-14

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Related research
Keywords: Fertility forecasting; functional data; mortality forecasting; net migration; nonparametric smoothing; population forecasting; principal components; simulation.;

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Find related papers by JEL classification:
J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends and Forecasts
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Ortega, Jose Antonio & Poncela, Pilar, 2005. "Joint forecasts of Southern European fertility rates with non-stationary dynamic factor models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 539-550. [Downloadable!] (restricted)
  2. Renshaw, A. E. & Haberman, S., 2003. "Lee-Carter mortality forecasting with age-specific enhancement," Insurance: Mathematics and Economics, Elsevier, vol. 33(2), pages 255-272, October. [Downloadable!] (restricted)
  3. Hyndman, Rob J. & Koehler, Anne B. & Snyder, Ralph D. & Grose, Simone, 2002. "A state space framework for automatic forecasting using exponential smoothing methods," International Journal of Forecasting, Elsevier, vol. 18(3), pages 439-454. [Downloadable!] (restricted)
    Other versions:
  4. Rob J. Hyndman & Md. Shahid Ullah, 2005. "Robust forecasting of mortality and fertility rates: a functional data approach," Monash Econometrics and Business Statistics Working Papers 2/05, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
    Other versions:
  5. Bircan Erbas & Rob J. Hyndman & Dorota M. Gertig, 2005. "Forecasting age-specific breast cancer mortality using functional data models," Monash Econometrics and Business Statistics Working Papers 3/05, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
  6. Brouhns, Natacha & Denuit, Michel & Vermunt, Jeroen K., 2002. "A Poisson log-bilinear regression approach to the construction of projected lifetables," Insurance: Mathematics and Economics, Elsevier, vol. 31(3), pages 373-393, December. [Downloadable!] (restricted)
  7. Renshaw, A. E. & Haberman, S., 2003. "On the forecasting of mortality reduction factors," Insurance: Mathematics and Economics, Elsevier, vol. 32(3), pages 379-401, July. [Downloadable!] (restricted)
  8. Lee, Ronald D., 1992. "Stochastic demographic forecasting," International Journal of Forecasting, Elsevier, vol. 8(3), pages 315-327, November. [Downloadable!] (restricted)
  9. Miller, Robert B., 1986. "A bivariate model for total fertility rate and mean age of childbearing," Insurance: Mathematics and Economics, Elsevier, vol. 5(2), pages 133-140, April. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Shripad Tuljapurkar, 2006. "Population Forecasts, Fiscal Policy, and Risk," Economics Working Paper Archive wp_471, Levy Economics Institute, The. [Downloadable!]
  2. Han Lin Shang & Rob J Hyndman, 2009. "Nonparametric time series forecasting with dynamic updating," Monash Econometrics and Business Statistics Working Papers 8/09, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
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