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Computer Research and Modeling, 2021, Volume 13, Issue 1, Pages 235–250
DOI: https://doi.org/10.20537/2076-7633-2021-13-1-235-250
(Mi crm880)
 

This article is cited in 1 scientific paper (total in 1 paper)

MODELS OF ECONOMIC AND SOCIAL SYSTEMS

Forecasting the labor force dynamics in a multisectoral labor market

M. I. Drobotenko, A. P. Nevecherya

Kuban State University, 149 Stavropolskaya st., Krasnodar, 350040, Russia
Full-text PDF (220 kB) Citations (1)
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Abstract: The article considers the problem of forecasting the number of employed and unemployed persons in a multisectoral labor market using a balance mathematical model of labor force intersectoral dynamics.
The balance mathematical model makes it possible to calculate the values of intersectoral dynamics indicators using only statistical data on sectoral employment and unemployment provided by the Federal State Statistics Service. Intersectoral dynamics indicators of labor force calculated for several years in a row are used to build trends for each of these indicators. The found trends are used to calculation of forecasted intersectoraldynamics indicators of labor force. The sectoral employment and unemployment of researched multisectorallabor market is forecasted based on values these forecasted indicators.
The proposed approach was applied to forecast the employed persons in the economic sectors of the Russian Federation in 2011–2016. The following types of trends were used to describe changes of intersectoral dynamics indicators values: linear, non-linear, constant. The procedure for selecting trends is clearly demonstrated by the example of indicators that determine the labor force movements from the “Transport and communications” sector to the “Healthcare and social services” sector, as well as from the “Public administration and military security, social security” sector to the “Education” sector.
Several approaches to forecasting was compared: a) naive forecast, within which the labor market indicators was forecasted only using a constant trend; b) forecasting based on a balance model using only a constant trendfor all intersectoral dynamics indicators of labor force; c) forecasting directly by the number employed persons in economic sectors using the types of trends considered in the article; d) forecasting based on a balance model with the trends choice for each intersectoral dynamics indicators of labor force. The article shows that the use of a balance model provides a better forecast quality compared to forecasting directly by the number of employed persons. The use of trends in intersectoral dynamics indicators improves the quality of the forecast.
The article also provides analysis examples of the multisectoral labor market in the Russian Federation. Using the balance model, the following information was obtained: the labor force flows distribution outgoing from concrete sectors by sectors of the economy; the sectoral structure of the labor force flows ingoing inconcrete sectors. This information is not directly contained in the data provided by the Federal State Statistics Service.
Keywords: multisectoral balance model, labor force dynamics, intersectoral dynamics, labor market, forecasting.
Received: 25.11.2020
Revised: 17.12.2020
Accepted: 26.01.2021
Document Type: Article
UDC: 519.862.3, 331.554
Language: Russian
Citation: M. I. Drobotenko, A. P. Nevecherya, “Forecasting the labor force dynamics in a multisectoral labor market”, Computer Research and Modeling, 13:1 (2021), 235–250
Citation in format AMSBIB
\Bibitem{DroNev21}
\by M.~I.~Drobotenko, A.~P.~Nevecherya
\paper Forecasting the labor force dynamics in a multisectoral labor market
\jour Computer Research and Modeling
\yr 2021
\vol 13
\issue 1
\pages 235--250
\mathnet{http://mi.mathnet.ru/crm880}
\crossref{https://doi.org/10.20537/2076-7633-2021-13-1-235-250}
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  • https://www.mathnet.ru/eng/crm/v13/i1/p235
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Research and Modeling
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    Abstract page:318
    Full-text PDF :198
    References:33
     
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