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Stability over time in the distribution of population forecast errors.

S K Smith¹, T Sincich

¹College of Business Administration, University of Florida 32611.

|August 1, 1988

Summary

Forecast error distributions for population projections are stable over time. Past forecast errors can reliably predict future errors, validating empirical confidence intervals for demographic forecasting.

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Area of Science:

Demography
Statistical Modeling

Background:

Empirical methods for confidence intervals in population projections are increasingly studied.
A key assumption is the temporal stability of forecast error distributions.

Purpose of the Study:

To evaluate the stability of forecast error distributions over time.
To test the utility of past forecast errors for predicting future errors.
To assess the validity of empirical confidence limits for population projections.

Main Methods:

Generated population projections for U.S. states across multiple 20th-century periods.
Compared projections with subsequent census data to calculate forecast errors.
Analyzed the temporal stability of absolute percentage error distributions.

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Main Results:

The distribution of absolute percentage errors in population projections demonstrated relative stability over time.
Historical forecast error data proved effective in predicting future forecast errors.

Conclusions:

The assumption of stable forecast error distributions is supported by this analysis.
Empirical confidence limits derived from past errors are valuable for demographic forecasting.