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Forecasting Australian marriage rates.

J Mcdonald, P Morgan

    The Economic Record
    |January 1, 1981
    PubMed
    Summary
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    Forecasting demographic variables like Australian marriage rates can be challenging. Autoregressive Moving Average (ARMA) models were found to be superior for forecasting marriage rates compared to regression-based methods.

    Area of Science:

    • Demography
    • Econometrics
    • Time Series Analysis

    Background:

    • Accurate demographic forecasting is crucial for policy and planning.
    • Modelling demographic variables requires careful selection of forecasting equations.
    • Previous studies have utilized regression methods for demographic forecasting.

    Purpose of the Study:

    • To evaluate empirical model selection procedures for demographic forecasting.
    • To compare the forecasting performance of final equation models with ARMA models for Australian marriage rates.
    • To examine the properties of ARMA model forecasts in a demographic context.

    Main Methods:

    • Application of two empirical model selection procedures.
    • Development of final form forecasting equations for Australian marriage rates.
    Keywords:
    AustraliaDeveloped CountriesDivorceEstimation TechnicsMarital StatusMarriageMarriage PatternsModels, TheoreticalNuptialityOceaniaPopulation ForecastPopulation ProjectionResearch Methodology

    Related Experiment Videos

  • Comparison of post-sample forecast performance against univariate ARMA-type models.
  • Examination of ARMA model forecast properties.

    • Main Results:

    • The study identified final form forecasting equations for Australian marriage rates.
    • Autoregressive Moving Average (ARMA) models demonstrated superior post-sample forecast performance.
    • ARMA models were preferred over regression-based approaches for forecasting marriage rates in this instance.

    Conclusions:

    • ARMA models are recommended for forecasting Australian marriage rates.
    • The findings suggest a preference for time series models over traditional regression methods for this demographic variable.
    • Further examination of ARMA model properties provides insights into demographic forecasting strategies.