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Regional labour market: A method for research

Author

Listed:
  • Ekaterina S. Dashkova

    (Voronezh State University, Voronezh, Russia)

  • Natalia V. Dorokhova

    (Voronezh State University, Voronezh, Russia)

Abstract

Turbulent socioeconomic environment significantly affects the state and dynamics of the regional labour market. The paper develops and tests a methodological toolkit for assessing the state of a regional labour market allowing for the main socioeconomic trends – digitalisation and innovative development of the economy. Labour economics constitutes the methodological basis of the research. Methods of economic statistical and content analysis were used. The evidence is the 2021 data of the Federal State Statistics Service of the Russian Federation concerning the labour markets of the Central Black Earth economic region of Russia, which comprises Belgorod, Voronezh, Kursk, Lipetsk and Tambov oblasts. The suggested method for investigating the state of the regional labour market takes into account the impact of digitalisation and innovative development processes on the latter. Testing the method at the case of the Central Black Earth economic region revealed that the regions’ labour markets appreciably lag behind other subjects of the Russian Federation in terms of wages and encounter labour shortages against rather low rates of digital transformation and innovative development in their economies. The paper formulates recommendations for all parties of the social partnership, which suggest boosting the investment attractiveness of regions; creating high-productive jobs; spurring the activities of trade unions and associations; retaining the youth in the regions; increasing the efficiency of career guidance; attracting labour migrants, first and foremost, from other Russian regions due to improvements in economic, social and household infrastructure; promoting competencies of citizens of pre-retirement age and retired citizens; creating conditions for acceleration of digital transformation as well as expanding regions’ innovation activities.

Suggested Citation

  • Ekaterina S. Dashkova & Natalia V. Dorokhova, 2023. "Regional labour market: A method for research," Journal of New Economy, Ural State University of Economics, vol. 24(3), pages 119-135, October.
  • Handle: RePEc:url:izvest:v:24:y:2023:i:3:p:119-135
    DOI: 10.29141/2658-5081-2023-24-3-6
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    References listed on IDEAS

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    1. Işgın, Ebru & Sopher, Barry, 2015. "Information transparency, fairness and labor market efficiency," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 58(C), pages 33-39.
    2. David Card & Ana Rute Cardoso & Joerg Heining & Patrick Kline, 2018. "Firms and Labor Market Inequality: Evidence and Some Theory," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 13-70.
    3. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    4. Nicole M. Fortin & Thomas Lemieux & Neil Lloyd, 2021. "Labor Market Institutions and the Distribution of Wages: The Role of Spillover Effects," Journal of Labor Economics, University of Chicago Press, vol. 39(S2), pages 369-412.
    5. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    6. Frank Fossen & Alina Sorgner, 2019. "Mapping the Future of Occupations: Transformative and Destructive Effects of New Digital Technologies on Jobs," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 13(2), pages 10-18.
    7. John M. Abowd & Kevin L. McKinney & Nellie L. Zhao, 2018. "Earnings Inequality and Mobility Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 183-300.
    8. Okudaira, Hiroko & Takizawa, Miho & Yamanouchi, Kenta, 2019. "Minimum wage effects across heterogeneous markets," Labour Economics, Elsevier, vol. 59(C), pages 110-122.
    9. Korovkin, A., 2018. "Current Status and Prospects of Employment Sphere and Labor Market Developments in Russia: Macroeconomic Estimates," Journal of the New Economic Association, New Economic Association, vol. 37(1), pages 168-176.
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    More about this item

    Keywords

    labour market; socioeconomic environment; regions; regional economy; labour economics; Central Black Earth economic region of Russia;
    All these keywords.

    JEL classification:

    • J20 - Labor and Demographic Economics - - Demand and Supply of Labor - - - General
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand

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