Model for labour productivity management in the economy of RussiaPavel A. Mikhnenko
Journal of New Economy, 2019, vol. 20, issue 5, 42-60 Abstract: Improving labour productivity is one of the key challenges faced by the Russian economy. Since 2018, Russia has been implementing the national project “Labour Productivity and Employment Support”. There are reasons to believe that the task of ensuring the required dynamics of productivity growth within the project needs further theoretical grounding. The scientific problem is that the change in the uncertainty of the project environment significantly affects the productivity growth. The optimal amounts of funding allocated at each of the project stages depend on the random factors, which makes it crucially important to take into account their intensity when planning the dynamics of productivity. The paper develops a stochastic mathematical economic model for managing the growth of labour productivity and substantiates its uses as a tool to solve the scientific problem. The author sets the scientific task to determine the intensity values of random factors, which make it possible to reach the project targets with the planned amount of funding. The methodological basis of the study rests on the concepts of economic growth, optimal control, and stochastic dynamic systems. The article assesses risks of irrational spending, presents scenarios of changing the project environment, and gives recommendations for adjusting the funding. The theoretical and practical significance of the study lies in the justification of the need for additional control over the expenditure of financial resources in order to avoid their irrational use under growing uncertainty. The research shows that reducing uncertainty through institutional changes will increase the intensity of funding without compromising the dynamic characteristics of the project. The author justifies the limitations and ways of using the developed model. Keywords: economic growth; labour productivity; mathematical economic model; scenario modelling; national project; funding, random factors; dynamics. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:url:izvest:v:20:y:2019:i:5:p:42-60 DOI: 10.29141/2073-1019-2019-20-5-3 Access Statistics for this article Journal of New Economy is currently edited by Yelizaveta A. Belousova More articles in Journal of New Economy from Ural State University of Economics Contact information at EDIRC. |
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