Evaluation of the best M4 competition methods for small area population forecasting

Tom Wilson, Irina Grossman and Jeromey Temple

International Journal of Forecasting, 2023, vol. 39, issue 1, 110-122

Abstract: The ‘M4’ forecasting competition results were featured recently in a special issue of the International Journal of Forecasting and included projections for demographic time series. We sought to investigate whether the best M4 methods could improve the accuracy of small area population forecasts, which generally suffer from much higher forecast errors than regions with larger populations. The aim of this study was to apply the top ten M4 forecasting methods to produce 5- and 10-year forecasts of small area total populations using historical datasets from Australia and New Zealand. Forecasts were compared against the actual population numbers and forecasts from two simple benchmark models. The M4 methods were found to perform relatively well compared to our benchmarks. In the light of these findings, we discuss possible future directions for small area population forecasting research.

Keywords: Population forecast; Forecast error; Small area; M4 competition; Australia; New Zealand (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:39:y:2023:i:1:p:110-122

DOI: 10.1016/j.ijforecast.2021.09.005

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