Economics and management of national economy

Assessment of the impact of socio-economic factors on productivity increase

Economic Annals-XXI

Economic Annals-ХХI: Volume 177, Issue 5-6, Pages: 70-81

Citation information:
Steshenko, Ju., Artemyev, A., Myktybaev, T., Khavanova, I., Masterov, A., & Ponomareva, M. (2019). Assessment of the impact of socio-economic factors on productivity increase. Economic Annals-XXI, 177(5-6), 70-81. doi: https://doi.org/10.21003/ea.V177-06

View Full-TextDownload PDF

Julia Steshenko
Junior Researcher,
Laboratory for Research on Organizational and Economic Problems in the Field of Physical Culture and Sports,
Federal Research Center of Physical Culture and Sports
10 Elizavetinsky Ln., building 1, Moscow, 105005, Russian Federation
Julia11st@vniifk.ru
ORCID ID: https://orcid.org/0000-0002-6511-6026

Aleksei Artemyev
PhD (Economics),
Associate Professor,
Financial University under the Government of the Russian Federation
4, 4th Veshnyakovsky passage, office 313 Moscow, 109456, Russian Federation
AArtemjev@fa.ru
ORCIDID: https://orcid.org/0000-0002-4320-317X 

Inna Khavanova
D.Sc. (Legal Sciences),
Financial University under the Government of the Russian Federation
49 Leningradsky Ave., Moscow, 125993 (GSP-3), Russian Federation
iakhavanova@fa.ru
ORCID ID: https://orcid.org/0000-0003-3722-5089 

Andrei Masterov
PhD (Economics),
Leading Researcher,
Center for Financial Policy, Department of Public Finance,
Financial University under the Government of the Russian Federation
49 Leningradsky Ave., Moscow, 125993 (GSP-3), Russian Federation
AIMasterov@fa.ru
ORCID ID: https://orcid.org/0000-0002-5531-1047 

Marina Ponomareva
PhD (Economics),
Associate Professor,
Department of Tax Policy and Customs Tariff Regulation,
Financial University under the Government of the Russian Federation
49 Leningradsky Ave., Moscow, 125993 (GSP-3), Russian Federation
MAPonomareva@fa.ru
ORCID ID: https://orcid.org/0000-0002-3064-3926 

Assessment of the impact of socio-economic factors on productivity increase

Abstract. Stimulation of productivity increase is a key task at the present stage of development of the economies of both Russia and Eurasian countries. The purpose of this article is to identify quantitative assessments of how various factors impact productivity increase and conduct a cluster analysis of the regions, based on the considered indicators that evaluate the impact of relevant factors on productivity. The authors use general scientific methods such as analysis and synthesis, econometric analysis and multidimensional statistics. To build the model, the authors of the article used statistical data relating to socio-economic development indicators for 85 Russian regions. As a result of the correlation and regression analysis, the following factors were identified: the average monthly wage, consumption of fixed capital, internal R&D costs, innovative activity of organisations, and tax burden. These factors have both positive and negative impacts on productivity. A cluster analysis was also conducted. It enabled to group the regions in terms of their productivity. Based on the analysis, the authors proposed the directions of improving the policy to increase productivity for each of the three clusters. For the regions included in the first cluster, it is necessary to apply methods of direct state regulation, for the regions of the second cluster – to pursue a policy of improvement of tax incentive mechanisms through the application of regional tax benefits and the use of special tax regimes, for the third cluster – to implement a supportive productivity policy for maintaining stable indicator values. The study highlights the key areas of tax incentives, the use of which will increase productivity and achieve the goals of economic development – stimulation of human capital development, support of R&D and development of infrastructure.

It has been concluded that the tax burden negatively affects the growth of productivity. Therefore, the use of the mechanism of tax tools, such as tax benefits and preferences, can contribute to the achievement of goals of economic growth. The current economic policy should be focused on increasing the efficiency of all productive sectors, namely supporting the deployment of innovations, removing barriers to raising investment, and stimulating human capital and labour force by using the tax incentives.

Keywords: Productivity; Tax Burden; Tax Incentives; Econometric Model; R&D; Gross Domestic Product (GDP); Russia; EAEU

JEL Classification: E24; E62; C13

Acknowledgements and Funding: This work was financially supported by the RFFR (Project 18-010-00527 «Harmonization of the system of taxation of foreign trade in the Eurasian space at the present stage of global development»), 2019.

Contribution: The authors contributed equally to this work.

DOI: https://doi.org/10.21003/ea.V177-06

References

  1. Djido, A. I., & Shiferaw, B. A. (2018). Patterns of labor productivity and income diversification – Empirical evidence from Uganda and Nigeria. World Development, 105, 416-427.
    doi: https://doi.org/10.1016/j.worlddev.2017.12.026
  2. Anisimov, S. A. (2012). Modeling of influence of taxes on economic growth. Finansovyi Zhurnal (Financial Journal), 14(4), 65-74.
    Retrieved from http://old.nifi.ru/images/FILES/Journal/Archive/2012/4/fm_2012_4.pdf (in Russ.)
  3. Balk, B. M. (2014). Dissecting aggregate output and labour productivity change. Journal of Productivity Analysis, 42(1), 35-43.
    doi: https://doi.org/10.1007/s11123-013-0359-6
  4. Bjuggren, C. M. (2018). Employment protection and labor productivity. Journal of Public Economics, 157, 138-157.
    doi: https://doi.org/10.1016/j.jpubeco.2017.11.007
  5. Chi Man Yip (2018). On the labor market consequences of environmental taxes. Journal of Environmental Economics and Management, 89, 136-152.
    doi: https://doi.org/10.1016/j.jeem.2018.03.004
  6. Mkhitaryan, V. S., Dubrova, T. A., Sirotin, V. P., Arkhipova, M. Y., & Mironkina, Y. N. (2016). Data analysis: textbook for academic undergraduate. Moscow: Publishing House Yurait.
    Retrieved from https://urait.ru/catalog/412967 (in Russ.)
  7. Diao, X., Kweka, J., & McMillan, M. (2018). Small firms, structural change and labor productivity growth in Africa: evidence from Tanzania. World Development, 105, 400-415.
    doi: https://doi.org/10.1016/j.worlddev.2017.12.016
  8. Dolgova, I. N. (2012). Analysis of the relationship of tax burden and labor productivity: regional breakdown. Nauchnye Trudy: Institut Narodnohoziajstvennogo prognozirovaniia Rossijskoj Akademii Nauk (Scientific works: Institute of National Economic Forecasting of the Russian Academy of Sciences), 10, 523-551.
    Retrieved from https://ideas.repec.org/a/scn/031151/14874292.html (in Russ.)
  9. Duernecker, G., & Herrendorf, B. (2018). On the allocation of time – a quantitative analysis of the roles of taxes and productivities. European Economic Review, 102, 169-187.
    doi: https://doi.org/10.1016/j.euroecorev.2017.10.025
  10. Yılmaz, G. (2016). Labor productivity in the middle income trap and the graduated countries. Central Bank Review, 16(2), 73-83.
    doi: https://doi.org/10.1016/j.cbrev.2016.05.004
  11. Gurvich, E. T., & Ivanova, M. A. (2018). Economic Effect of Population Ageing and Pension Reforms. Finansovyi Zhurnal (Financial Journal), 45(5), 9-22.
    doi: https://doi.org/10.31107/2075-1990-2018-5-9-22 (in Russ.)
  12. Gunina, I. A. (2018). The problems of labour productivity growth: theory, methodology, practice. Organizator proizvodstva (Organizer of Production), 26(4), 30-40.
    doi: https://doi.org/10.25987/VSTU.2018.10.81.003 (in Russ.)
  13. Kakaulina, M. O. (2014).The impact of tax burden on economic growth in the Russian Federation: a regional aspect. Regionalnaya Ekonomika: Teoriya i Praktika (Regional Economy: Theory and Practice), 17(12), 55-64 (in Russ.).
  14. Kinfemichael, B., & Morshed, A. K. M. M. (2019). Convergence of labor productivity across the US states. Economic Modelling, 76, 270-280.
    doi: https://doi.org/10.1016/j.econmod.2018.08.008
  15. Marattin, L., & Salotti, S. (2011). Productivity and per capita GDP growth: the role of the forgotten factors. Economic Modelling, 28(3), 1219-1225.
    doi: https://doi.org/10.1016/j.econmod.2011.01.004
  16. Tang, M.-Ch. (2017). Total factor productivity or labor productivity? Firm heterogeneity and location choice of multinationals. International Review of Economics & Finance, 49, 499-514.
    doi: https://doi.org/10.1016/j.iref.2017.03.016
  17. Popova, G. L. (2015). Analysis of the impact of tax burden on labor productivity growth. Ekonomicheskiy Analliz: Teoriya i Praktika (Economic analysis: theory and practice), 32(14), 60-72 (in Russ.).
  18. Prescott, E. C. (2004). Why do Americans work so much more than Europeans? Federal Reserve Bank of Minneapolis. Quarterly Review, 28(1), 2-13.
    Retrieved from https://www.minneapolisfed.org/research/qr/qr2811.pdf
  19. Rachek, S. V., & Miroshnik, A. V. (2013). Productivity as key performance indicators work. Sovremennye Problemy Nauki i Obrazovaniya (Modern Problems of Science and Education), 6, 1-8.
    Retrieved from http://www.science-education.ru/ru/article/view?id=11461 (in Russ.)
  20. Rausch, S., & Schwarz, G. A. (2016). Household heterogeneity, aggregation, and the distributional impacts of environmental taxes. Journal of Public Economics, 138, 43-57.
    doi: https://doi.org/10.1016/j.jpubeco.2016.04.004
  21. Khanna, R., & Sharma, C. (2018). Testing the effect of investments in IT and R&D on labour productivity: new method and evidence for Indian firms. Economics Letters, 173, 30-34.
    doi: https://doi.org/10.1016/j.econlet.2018.09.003
  22. Steshenko, Yu. A. (2018). Key areas of tax system reform to ensure economic growth. Innovatsyonnoe Razvitie Ekonomiky (Innovative Development of the Economy), 45(3), 210-218 (in Russ.).
  23. Suslina, А. L., & Leukhin, R. S. (2018). Do tax Incentives for innovation work? Evaluation of effectiveness in Russia and in the world. Finansovyi Zhurnal (Financial Journal), 45(5), 58-69.
    doi: https://doi.org/10.31107/2075-1990-2018-5-58-69 (in Russ.)
  24. Tarancón, M.-Á., Gutiérrez-Pedrero, M.-J., Callejas, F. E., & Martínez-Rodríguez, I. (2018). Verifying the relation between labor productivity and productive efficiency by means of the properties of the input-output matrices. The European case. International Journal of Production Economics, 195, 54-65.
    doi: https://doi.org/10.1016/j.ijpe.2017.10.004
  25. Walker, W. R. (2011). Environmental regulation and labor reallocation: evidence from the clean Air Act. American Economic Review, 101(3), 442-447.
    doi: https://doi.org/10.1257/aer.101.3.442

Received 18.07.2019
Received in revised form 24.07.2019
Accepted 30.08.2019
Available online 18.09.2019

View Full-TextDownload PDF
In, , , , , , , ,

More Papers