Abstract

AbstractThe purpose of this paper is to investigate the applicability of a contemporary time series forecasting technique, transfer function modeling, to the problem of forecasting sectoral employment levels in small regional economies. The specific sectoral employment levels to be forecast are manufacturing, durable manufacturing, non‐durable manufacturing and non‐manufacturing employment. Due to data constraints at the small region level, construction of traditional causal econometric models is often very difficult; thus time series approaches become particularly attractive. The results suggest that transfer function models using readily available national indicator series as drivers can provide more accurate forecasts of small region sectoral employment levels than univariate time series models.

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