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A MODEL FOR THE JOB DEMAND FORECASTING IN THE ARCTIC ZONE OF THE RUSSIAN FEDERATION BASED ON TIME SERIES

Zhanna Petukhova (), Mikhail Petukhov (), Igor Belyaev () and Lyudmila Bodryakova ()
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Zhanna Petukhova: Professor, Department of Economics, Management and Organization of Production, Norilsk State Industrial Institute
Mikhail Petukhov: Associate Professor, Department of Information Systems and Technologies, Norilsk State Industrial Institute
Igor Belyaev: Senior Lecturer, Department of Information Systems and Technologies, Norilsk State Industrial Institute
Lyudmila Bodryakova: Associate Professor, Department of Information Systems and Technologies, Norilsk State Industrial Institute

Regional Science Inquiry, 2021, vol. XIII, issue 2, 291-298

Abstract: The Russian Federation is the largest country in the world, whose territory includes the Arctic regions. The area of the land territories of the Arctic Zone of the Russian Federation (AZRF) is approximately 3.700,000 km2. The population of the Arctic Zone of Russia is approximately 7 million people, which is equal to 5% of the population of the entire Russian Federation. The purpose of this study is to investigate and analyse regression models for predicting the time series of the number of jobs in the labour market of the Russian Federation, to select an adequate model characterised by a minimum average relative error and a maximum lead time, or to select several adequate models for different forecasting periods: short-term, medium-term and long-term. The study examines the possibilities of predicting the situation in the labour market of the Arctic Zone of the Russian Federation, the demand for specialists in various industries using regression models for forecasting a time series. The simulation was performed using the Statistica software. As a result of the conducted studies, adequate forecasting models were obtained in the time period from 01.01.2020 to 01.01.2021, taking into account the epidemiological situation in the country. Thus, the best model with the smallest error was determined.

Keywords: labour market; regression models; education; autocorrelation function; autoregression. (search for similar items in EconPapers)
JEL-codes: I15 J01 J11 (search for similar items in EconPapers)
Date: 2021
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