Candidate of Economic Sciences, Associate Professor at the Department of Mathematical Methods and Models in Economics, Orenburg State University

Objective: to develop mathematical models for predicting the number of foreign workers in the region based on the vector-based error correction model. As a tool, the article used forecasting methods based on one-dimensional and multidimensional time series. The relevance of the study: The impact of migration on the economy and society is ambiguous. On the one hand, external labor migration contributes to population growth, covers labor shortages, replenishes the local budget. On the other hand, labor migration may have a negative impact, heightening tensions in the labor market and in the social sphere. An acute problem remains with foreign workers in the border regions, including the Orenburg region. This situation predetermines large volumes of migration flows to the region, which necessitates the use of mathematical tools for making effective management decisions. The existing models of analysis of migration flows do not take into account the short-term dynamics of the mutual influence of socio-economic factors and indicators of external labor migration based on the vector-based model of error correction. Based on the foregoing, the relevance of the study. The obtained results can be used both for an objective presentation of the state of migration processes in the region when developing regional migration programs by migration services authorities, and for state authorities in shaping the regional migration policy.

Keywords: number of foreign workers, forecasting methods, one-dimensional time series, multidimensional time series, error correction model.

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