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№ 2020/2
YASTREMSKY Oleksandr Ivanovych1, KULYK Volodymyr Vasyl'ovych2
1State research and educational institution"Academy of Financial Management”
2State research and educational institution "Academy of Financial Management”
Volatility of the structure of intersectoral relations of Ukraine\'s economy
Economy and forecasting 2020; 2:45-58 | https://doi.org/10.15407/econforecast2020.02.045 |
ABSTRACT ▼
The article deals with the volatility of intersectoral flows in Ukrainian economy during 2000–2017. For this purpose, the authors construct a dynamic matrix series of direct cost coefficients in comparable detail (19 economic activities (EAs)); calculate statistical characteristics of 361 dynamics (19x19) and coefficients of direct expenses of Ukraine's intersectoral balance; and analyze the dynamics of cost indicators of Ukraine's economy (the ratio of GDP to total output, the Frobenius – Perron numbers) and those of economic activities (the Brauer – Perron numbers).
Construction of the historical series of the matrix of direct costs in comparable detail is achieved by aggregating the "input - output" tables.
Volatility is assessed using indicators of variation, relative variation, sample standard deviation, standard deviation per mean, historical volatility, and standard trend error (regression), i.e. trend volatility.
Volatility of intersectoral flows in Ukraine is significant. The maximum variation for the coefficients of direct costs for EA "Information ..." for all years of observation was 0.3144, for EA "Water Supply" - 0.3004, and for EA "Art" - 0.2673.
Derivative aggregates (Brauer-Solow numbers, relative EA cost) are also volatile. According to estimates of the standard deviation, the agrosector is the most stable, the most unstable - public administration.
Economy Ukraine has a significant margin of productivity. A sufficient Brauer-Solow condition for the productivity of the direct cost matrix is guaranteed to be satisfied for all years of observation.
Out of 361 coefficients of direct costs, time trends are recorded for 166. Among them, 91 have an upward trend, 65 - a downward trend. To fix the presence of the trend, the authors use the probability of deviation of the hypothesis about the significance of the linear dependence of the coefficients of direct costs on time.
The high cost intensity of the economy is a general economic problem of Ukraine. The ratio of GDP to total output in Ukraine is about 40%, while in developed countries, this figure is close to 60%. Reducing costs is a significant resource for economic growth in Ukraine.
Keywords:economy of Ukraine, "input - output"; tables, intersectoral balance, matrix of direct costs, volatility, the level of costs of economic activities and the national economy, Frobenius - Perron numbers
JEL: C67; C53, E 17
Article in English (pp. 45 - 58) | Download | Downloads :360 |
REFERENCES ▼
2. Glushkov, V.M. (1980). Dysplan is a new planning technology. Upravljajushie sistemy i mashiny – Control systems and machines, 6, 5-10 [in Russian].
3. Karpec, Je.P., Glushkova, V.V. (2017). On the possibility of using the DISPLAN system for balanced management of the economy. In Kravchuk A.V. (ed.) Cybernetics and democratic economic governance (p. 45-58). Kiev: Center for Social and Labor Studies [in Russian].
4. Matveev, M.T., Arhangel\'skij, Ju.S., Rybal\'chenko, V.P. et al (1988). Models of the automated system of planned calculations of Gosplan of the republic. Kiev: Naukova dumka [in Russian].
5. Economic modeling and forecasting - Ukraine: a guide to building a model (n.d.). The Conference Board of Canada. RC/Project 439/Z11109 Commitment 221460 – 2003 [in Ukrainian].
6. Pavel, F., Burakovsky, I., Selitska, N., Movchan, V. (2004). Economic Impact of Ukraine\'s WTO Accession. First results from a Computable General Equilibrium Model. The Institute for Economic Research and Police Consalting Working Paper, 43. Retrieved from www.ier.com.ua/en/publications/working_paper? pid=1547
7. Mihalevich, M.V., Sergienko, I.V. (2005).Modeling of transition economy: models, methods, information technologies. Kiev: Naukova dumka [in Russian].
8. Dovhyj, S.O., Bidiuk, P.I., Trofymchuk, O.M. (2014). Decision support systems based on statistical-probabilistic methods. Kyiv: Lohos [in Ukrainian].
9. Information and analytical support of the budget process (2013). NAS of Ukraine, Institute for Economics and Forecasting, V.M. Glushkov Institute of Cybernetics, Institute of Telecommunications and Global Information Space. Kyiv: Informatsijni systemy [in Ukrainian].
10. Arhangel\'skij, Ju.S. (1999). Forecasting production volumes based on mac-roeconomic models and intersectoral balance for the coming year. Ekonomika Ukrainy – Economy of Ukraine, 6, 20-31 [in Ukrainian].
11. Paskhaver, B.J. (2018).Agro-food complex of Ukraine in intersectoral pro-portions: state and dynamics. Ekon. prognozuvannâ – Economy and forecasting, 2, 151-159 [in Ukrainian].
12. Kudin, V.I., Onyshchenko, A.M. (2016). Modelling of technological changes in \"input-output\" balance model in terms of the Paris agreement. Ekonomichnyj analiz – Economic analysis, 25: 1, 37-44 [in Ukrainian].
13. Kudin, G.I., Kudin, V.I., Onyshchenko, A.M. (2014). Analysis of the mesoeconomic structure of production in terms of reducing greenhouse gas emissions. VII International School-Seminar \"Decision Theory\" (September 29 - October 4, 2014). Uzhhorod [in Ukrainian].
14. Yastremskii, O.I. (2019). Input-output chessboard of uncertainty and its application: forecasting, economic policy, fiscal risk, general equilibrium. Kibernetyka i systemnyj analiz – Cybernetics and systems analysis, 55: 3, 28-36. doi.org/10.1007/s10559-019-00143-6 [in Ukrainian].
15. Mirzoakhmedov, F., Nazrizoda, S., Yastremskii, O. (2017). Uncertainty estimations in input-output scheme of Republic of Tajikistan. Ekonomichnyj prostir – Economic space, 126, 15-23 [in Ukrainian].
16. Yastremskii, O.I. (2017). Uncertainty in input-output scheme: comparative inter-country analysis. Naukovi pratsi NDFI – RFI Scientific Paper, 3, 21-35. doi.org/10.33763/npndfi2017.03.021 [in Ukrainian].
17. Gurgul, H. (2007). Stochastic input-output modeling. Ekonomia Menedzerska, 2, 57-70.
18. Temurshoev, U. Uncertainty treatment in input-output analysis. Department of Economics Universidad Loyola Andalucía. Retrieved from www.loyolaandnews.es/loyolaecon/wp-content/uploads/2016/01/an--lisis-input-y-output.pdf
19. Ermol\'ev, Ju.M., Jastremskij, A.I. (1979). Stochastic models and methods in economic planning. Moscow: Nauka [in Russian].
20. Yastremskii, O.I. (1992). Economic risk modeling. Kyiv: Lybid\' [in Ukrainian].
21. Knopov, P.S., Sergienko, I.V. (2011). On scientific results of Yu.M. Ermoliev and his school in the modern stochastic optimization theory. Cybernetics and System Analysis, 47: 6, 835-853. doi.org/10.1007/s10559-011-9363-x
22. Table \"input - output\" of Ukraine for 2017 in basic prices (2019). State Statistics Service of Ukraine. Kyiv. Retrieved from www.ukrstat.gov.ua [in Ukrainian].
23. Methodological provisions for the organization of state statistical observation Table \"input - output\". State Statistics Service of Ukraine. Retrieved from www.ukrstat.gov.ua [in Ukrainian].
24. United Nations (2019). National accounts statistics: Main aggregates and detailed tables, 2018. Part I–V. (ST/ESA/STAT/SER.X/61). Department of Economic and Social Affairs Statistics Division. New York.
25. State classifier DK 009: 2005 \"Classification of economic activities\" (NACE- 2005). Approved by the order of Derzhspozhyvstandart of Ukraine dated December 26, 2005. № 375 (as amended). Retrieved from search.ligazakon.ua/l_doc2.nsf/link1/FIN19567.html [in Ukrainian].
26. Classification of economic activities. Correspondence tables of NACE-2010 – NACE-2005. Retrieved from www.ukrstat.gov.ua [in Ukrainian].
27. Piketty, Thomas (2014). Capital in the Twenty-First Century. Harvard University Press. doi.org/10.4159/9780674369542
28. Åslund, Anders. Kremlin aggression in Ukraine: the price tag. Retrieved from www.atlanticcouncil.org/images/publications/Cost_of_Kremlin_Aggression_ web.pdf
29. Pustoviit, R.F. (2016). Military expenditure and its impact on the domestic economy. Finansy Ukrainy – Finance of Ukraine, 11, 79-93 [in Ukrainian].
30. Nikaido, H. (1968). Convex Structures and Economic Theory. New York, London: Academic Press.
31. Yastremskii, O.I. (2019, February 22). Expert opinion: Working more sparingly is a resource for Ukraine\'s economic growth. Voice of America [in Ukrainian].
32. Kulyk, V.V., Kudin, G.I. (2018). Forecasting changes in intrabranch ties in the input-output model. Problemy ekonomiky – Problems of the economy, 3, 45-55 [in Ukrainian].
33. Uriasiev, S. (2017). Risk Management with POE, VaR, CVaR, and bPOE. Optimization Under Uncertainty and Data-Driven Science and Engineering. Duke University.
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