Correlation Analysis of Gross Regional Product and Industries of Regional Economy
https://doi.org/10.21686/2413-2829-2022-3-109-118
Abstract
The article carried out correlation analysis of gross regional product and figures of regional economy industries, including analysis of correlation with the time lag. The authors found out that there is a correlation between separate industries of regional economy and gross regional product, however, it is not statistically important for the majority of indicators. The Granger causation test did not show a stable interconnection between the said indicators either. According to the authors, the mentioned correlation can be explained by the Geks – Krevosier matrix. A conclusion was drawn that in the current situation caused by different factors, including COVID-19 pandemic, it is more reasonable to re-orient regional economy to local people needs and the development of service sectors. Disclosed low rates of convergence in regions, which are members of the Central Federal Area of Russia, can be useful for reorientation of macro-economic policy to partial autonomization of regional economy.
About the Authors
M. V. Dubovik
Plekhanov Russian University of Economics
Russian Federation
Mayya V. Dubovik Doctor of Economics, Assistant Professor, Professor of the Department for Economic Theory
Russian Federation
Mayya V. Dubovik Doctor of Economics, Assistant Professor, Professor of the Department for Economic Theory
36 Stremyanny Lane, Moscow, 117997
S. G. Dmitriev
Bryansk branch of the Plekhanov Russian University of Economics
Russian Federation
Sergey G. Dmitriev PhD, Assistant Professor of the Department for Economics, Customs, Information Technology and Disciplines of the Natural Science Cycle
Russian Federation
Sergey G. Dmitriev PhD, Assistant Professor of the Department for Economics, Customs, Information Technology and Disciplines of the Natural Science Cycle
8 Bezhitskaya Str., Bryansk, Bryansk Region, 241050
References
1. Azam A., Rafiq M., Shafique M., Zhang H., Yuan J. Analyzing the Effect of natural Gas, Nuclear Energy and Renewable Energy on GDP and Carbon Emissions: a Multi-Variate Panel Data Analysis. Energy, 2021, Vol. 219, No. 119592.
2. Bizikova L., Smith R., Zoundi Z. Measuring Wealth to Promote Sustainable Development, 2021. Available at: https://www.iisd.org/projects/measuring-wealth-promote-sustainabledevelopment (accessed 02.02.2022).
3. Bolt J., Inklaar R., de Jong H., van Zanden J. L. Rebasing Maddison. VOX, CEPR Policy Portal, 2018, January 25. Available at: https://voxeu.org/article/rebasing-maddison (accessed 17.01.2022).
4. Camagni R., Capello R., Caragliu A. Static vs. Dynamic Agglomeration Economies. Spatial Context and Structural Evolution Behind Urban Growth. Papers in Regional Science, 2016, Vol. 95, No. 1, pp. 133–158.
5. Crevoisier O. Territorial Value in a Postindustrial Society: Towards Valuation Policies. With inputs from H. Jeannerat, C. Livi, D. Guex, A. Huguenin, Research Group in Territorial Economy (GRET), University of Neuchâtel (Switzerland). Birmingham Business School, 2016.
6. Crowley P. M., Hallett A. H. The Evolution of US and UK Real GDP Components in the Time‑Frequency Domain: A Continuous Wavelet Analysis. Journal of Business Cycle Research, 2021, No. 17, pp. 233–261.
7. Divya K. H., Rama Devi V. A Study on Predictors of GDP: Early Signals. Procedia Economics and Finance, 2014, Vol. 11, pp. 375–382.
8. Faisal F., Rahman S. U., Chander R., Ali A., Ramakrishnan S., Ozatac N., Ullah M. N., Tursoy T. Investigating the Nexus Between GDP, Oil Prices, FDI, and Tourism for Emerging Economy: Empirical Evidence from the Novel Fourier ARDL and Hidden Cointegration. Resources Policy, 2021, Vol. 74, No. 102368.
9. Fezzi C., Fanghella V. (2021) Tracking GDP in Real-Time Using Electricity Market Data: Insights from the First Wave of COVID-19 ACROSS EUROPE. European Economic Review, 2021, Vol. 139, No. 103907.
10. Granger C. W. J. Investigating Causal Relations by Econometric Models and CrossSpectral Methods. Econometrica, 1969, No. 37 (3), pp. 424–438.
11. Guex D., Crevoisier O. A Comprehensive Socio-Economic Model of the Experience Economy: the Territorial Stage, edited by Lorentzen L. Schrøder, K. Topsø Larsen, Spatial Dynamics in the Experience Economy. Abingdon, Routledge, 2015.
12. Guex D., Crevoisier O. Post-Industrial Globalization and Local Milieus: A typology. CRED Research Paper, 2017, No. 15.
13. Jayadevan C. M. A Canonical Correlation Analysis of Sectoral Composition of GDP and Development in Asia. Modern Economy, 2018, No. 9, pp. 379–392.
14. Kwark N.-S., Lee C. Asymmetric Effects of Financial Conditions on GDP Growth in Korea: A Quantile Regression Analysis. Economic Modelling, 2021, Vol. 94, pp. 351–369.
15. Marcu M., Carstina S.-V., Marian S. GDP Correlation Analysis with Structural Elements of Added Value. Procedia Economics and Finance, 2015, Vol. 22, pp. 282–286.
16. Stiglitz J. It's Time to Retire Metrics Like GDP. They Don't Measure Everything That Matters, 2019. Available at: https://www.theguardian.com/commentisfree/2019/nov/24/ metrics-gdp-economic-performance-social-progress (accessed 28.12.2021).
Review
For citations:
Dubovik M.V., Dmitriev S.G. Correlation Analysis of Gross Regional Product and Industries of Regional Economy. Vestnik of the Plekhanov Russian University of Economics. 2022;(3):109-118. (In Russ.) https://doi.org/10.21686/2413-2829-2022-3-109-118
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