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[Predictability of demographic changes in the short run]
Maandstatistiek Van De Bevolking (Hague, Netherlands : 1982)
|November 1, 1985
Summary
Univariate time series models effectively assess Dutch population forecast accuracy. Methods like exponential smoothing and ARIMA models were applied to demographic data, showing their value in evaluating short-term predictions.
Area of Science:
- Demography
- Statistical Modeling
- Time Series Analysis
Context:
- Official short-term population forecasts in the Netherlands require accurate assessment.
- Demographic data including live births, deaths, marriages, immigrants, and emigrants from 1979-1984 were analyzed.
- Comparative analysis included data from an earlier period (1970-1975).
Purpose:
- To evaluate the accuracy of official short-term population forecasts in the Netherlands.
- To assess the utility of univariate time series models for forecast evaluation.
- To compare the performance of exponential smoothing, ARIMA, and structural time series models.
Summary:
- Three univariate time series methods were applied to Dutch demographic data (births, deaths, migration) for 1979-1984.
- The models included exponential smoothing, Autoregressive Integrated Moving Average (ARIMA), and structural time series models.
- The study aimed to determine the value of these models in assessing forecast accuracy.
Impact:
- Provides insights into the accuracy of Dutch population forecasts.
- Demonstrates the applicability and value of specific time series models in demographic forecasting evaluation.
- Offers a methodological approach for assessing the reliability of short-term population predictions.