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The sensitivity of the Scaled Model of Error with respect to the choice of the correlation parameters: A Simulation Study

Author

Listed:
  • Graziani, Rebecca

    (Department of Decision Sciences, Bocconi University, Milano)

  • Keilman, Nico

    (Dept. of Economics, University of Oslo)

Abstract

The Scaled Model of Error has gained considerable popularity during the past ten years as a device for computing probabilistic population forecasts of the cohort-component type. In this report we investigate how sensitive probabilistic population forecasts produced by means of the Scaled Model of Error are for small changes in the correlation parameters. We consider changes in the correlation of the age-specific fertility forecast error increments across time and age, and changes in the correlation of the age-specific mortality forecast error increments across time, age and sex. Next we analyse the impact of such changes on the forecasts of the Total Fertility Rate and of the Male and Female Life Expectancies respectively. For age specific fertility we find that the correlation across ages has only limited impact on the uncertainty in the Total Fertility Rate. As a consequence, annual numbers of births will be little affected. The autocorrelation in error increments is an important parameter, in particular in the long run. Also, the autocorrelation in error increments for age specific mortality is important. It has a large effect on long run uncertainty in life expectancy values, and hence on the uncertainty around the elderly population in the future. In empirical applications of the Scaled Model of Error, one should give due attention to a correct estimation of these two parameters.

Suggested Citation

  • Graziani, Rebecca & Keilman, Nico, 2010. "The sensitivity of the Scaled Model of Error with respect to the choice of the correlation parameters: A Simulation Study," Memorandum 22/2010, Oslo University, Department of Economics.
    • Handle: RePEc:hhs:osloec:2010_022
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    File URL: https://www.sv.uio.no/econ/english/research/unpublished-works/working-papers/pdf-files/2010/Memo-22-2010.pdf
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    Cited by:

    1. Gianni Corsetti & Marco Marsili, 2013. "Previsioni stocastiche della popolazione nell’ottica di un Istituto Nazionale di Statistica," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 15(2-3), pages 5-29.

    More about this item

    Keywords

    Scaled model of error; Stochastic population forecast; Probabilistic cohort component model; Sensitivity; Correlation;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • J40 - Labor and Demographic Economics - - Particular Labor Markets - - - General

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