Vol. 54 No. 1 (2026): Published March 30, 2025
DOI https://doi.org/10.18799/26584956/2026/1/2070
Methodological approaches to forecasting labor force dynamics in territorial systems
Abstract. In modern conditions, the increasing concentration of the economically active population in major cities and their satellite cities and its decline in peripheral areas pose a threat to the balanced socioeconomic development of these territories. This increases the relevance of the research on assessing and forecasting labor force dynamics in territorial socioeconomic systems. Aim. To carry out a review of methodological approaches to forecasting the dynamics of labor force movement, taking into account the spatial features of placement, and identifying their advantages and disadvantages. Methods. Comparative and retrospective analysis, generalization. Results. It was revealed that when constructing forecasts of labor force dynamics in territorial systems, three groups of methods are mainly used: autoregressive modeling of time series, regression modeling with an assessment of the impact of various factors, and spatial autoregressive modeling taking into account the effect of surrounding territories. Conclusions. When constructing spatial autoregressive models, researchers mainly used the maximum likelihood method, which has a higher level of errors and biases in the case of spatial heterogeneity of data compared to the generalized moments method, and one specific matrix of spatial weights without evaluating alternatives. Forming predictive spatial models requires a preliminary analysis of the spatial interactions of territorial systems based on the assessed indicator and the selection of territories with strong spatial autocorrelation. The use of spatial modeling methods demonstrates high predictive capabilities, as they take into account the spatial heterogeneity of labor force distribution.
For citation: Naumov I.V., Nikulina N.L. Methodological approaches to forecasting labor force dynamics in territorial systems. Journal of Wellbeing Technologies, 2026, vol. 54, no. 1, pp. 113–хх. https://doi.org/10.18799/26584956/2026/1/2070
Keywords:
labor force, territorial systems, theoretical review, forecasting methods, autoregressive modeling, regression modeling, spatial autoregressive modeling
References:
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