DOI: http://doi.org/10.15350/2409-7616.2020.4.40

Stanislav S. Alkhasov –Cand. of Eng. Sc., junior researcher, Department of Geo-urban Studies and Spatial Demography, Institute for Demographic Research – Branch of the Federal Center of Theoretical and Applied Sociology of the Russian Academy of Sciences (IDR FCTAS RAS), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-8051-6423, E-mail: stanislav.alkhasov@gmail.com

Sergey V. Ryazantsev – Corresponding Member of RAS, Dr. Sci. (Econ.), Prof., director, Institute for Demographic Research – Branch of the Federal Center of Theoretical and Applied Sociology of the Russian Academy of Sciences (IDR FCTAS RAS), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0001-5306-8875, E-mail: riazan@mail.ru

Abstract. The published by Russian Federal State Statistics Service (also named as Rosstat) data sometimes are insufficient in the context of research on migration mobility and labor market. The way they are placed and their structure does not comply with Open Data standards. With the development of Internet technologies, job seeking and search for employees by employers take on new forms: online recruitment portals appear. In the course of filling these Internet portals with personal user content, Big Data are generated. Collected and processed using modern data mining and programming tools (language Python 3.7, libraries: requests, BeautifulSoup, Selenium, etc.), these arrays are becoming a valuable new source of information about age, family status, education, work experience, salary expectations, as well as readiness for labor migration. This quantitative study allows us to answer the question about the age-gender structure and professional experience of potential labor migrants. For example, middle-aged men who are involved in construction and fossil foels are extremely inclined to leave their place of residence. Women are less inclined to out-migrate: in a number of industries the share of women who ready for labor migration is 1.5…2 times lower compared to the same indicators for men. The only industry where both women and men are approximately equally ready to out-migrate is information and telecommunication technologies. Men tend to leave to earn higher salaries, while women are often ready to outflow even for salaries about average regional level. There is reason to believe that with an increase in human prosperity, the propensity to out-migrate will only rise to a certain limit, because many potential migrants are in a poverty trap at the time of our study and do not have the opportunity to leave their place of residence. For both men and women who live in Rostov Region, the most attractive destinations for labor migration within Russia are Moscow, Krasnodar Region, and St. Petersburg. The potential for intraregional migration (according to curricula vitarum with the indicated assesible directions for migration) is inferior to the above three regions. Among the rest of the federal subjects of Russia, the regions of Siberia and the Far East prevail for men, while for women the set of regions that are attractive for labor migration is more diverse.

Keywords: labor migration, migration mobility, population outflow, Internet recruitment, labor market, Rostov region.

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For citation:

Alkhasov S.S., Ryazantsev S.V. Potential labor migration mobility in a frontier region of the south of Russia according to data of internet recruitment (the example of Rostov region). CITISE, 2020, no. 4, pp.465-481. DOI: http://doi.org/10.15350/2409-7616.2020.4.40