№ 3/2017

№ 3/2017

Nauk. pr. NDFI 2017 (3): 21–35https://doi.org/10.33763/npndfi2017.03.021

FINANCIAL AND ECONOMIC REGULATION

YASTREMSKYI Olexandr ¹

¹SESE “The Academy of Financial Management”
OrcID ID : https://orcid.org/0000-0001-9900-3612

Uncertainty in input-output scheme: comparative inter-country analysis

An analysis of dynamics of inter-industry flows in the “input-output” schemes shows considerable volatility of the matrix of direct requirements, which gives grounds for assuming their random character. This leads to a change in the nature of the variables and provides a new vision of the input-output model. So, the balances of the industries (products) require that the vector of gross output is also random (ex post). The problem arises how the initial impulse of uncertainties, including the matrix of direct requirements, is spread in the industries. A standard basket of tools of the input-output scheme is complemented by new indicators, including the “chessboard” of uncertainty of inter-industrial flows, measures of uncertainty of gross output, total requirements. To assess the level of uncertainty, a "physical" approach is used, namely: the uncertainty of a parameter is estimated by its standard deviations. To normalize the level of uncertainty, relative uncertainty is used – the ratio of the standard deviation to the expected value. The paper presents results of the Monte Carlo statistical method of testing the influence of uncertainty on inter-industry flows of national economies of Poland, USA, and Ukraine. Experiments with other things being equal for the indicated countries show that the Ukrainian economy is more vulnerable to external and internal disturbances due to its greater material intensity.

Keywords:“input-output” scheme, uncertainty, matrix of direct requirements by industry, the Monte Carlo test method

JEL: D57, D81

Yastremskyi O. . Uncertainty in input-output scheme: comparative inter-country analysis / O. Yastremskyi // Наукові праці НДФІ. - 2017. - № 3. - C. 21-35.

Article original in Ukrainian (pp. 21 - 35)

Download

Downloads :930

1. Horowitz, K. J., Planting, M. A. (2006, updated 2009). Concepts and Methods of the Input-Output Account. Bureau of Economic Analysis (BEA), U.S. Department of Commerce.

2. NDFI. (2004). State financial policy and forecasting of budget revenues of Ukraine. Ky'yiv: Author [in Ukrainian].

3. Iefymenko, T. I. (2004). Dynamics of budget revenues and gross domestic product: methodology and methods of comparative analysis. RFI scientific papers, 1-2 (24-25), 11-21 [in Ukrainian].

4. Iefymenko, T. I., Yermoshenko, M. M. (Eds.). (2014). Finances of institutional sectors of the economy of Ukraine. Ky'yiv: DNNU "Akademiya finansovoho upravlinnya". Retrieved from afu.minfin.gov.ua/getfile.php?page_id=449&num=2 [in Ukraininan].

5. Gasanov, S. S. (2017). Structural reforms under institutional uncertainty and financial instability. RFI scientific papers, 1, 41-52.
doi.org/10.33763/npndfi2017.01.041

6. Gasanov, S. S. (2017). Structural policy and public finance under institutional uncertainty. Finance of Ukraine, 3, 7-18.
doi.org/10.33763/finukr2017.03.007

7. Ermol'ev, Yu. M., Yastremskij, A. I. (1979). Stochastic models and methods in economic planning. Moscow: Nauka [in Russian].

8. Yastrems'ky'j, O. I. (1992). Modeling of economic risk. Ky'yiv: Ly'bid' [in Ukrainian].

9. Gurgul, H. (2007). Stochastic input-output modeling. Ekonomia Menedzerska, 2, 57-70.

10. Gurgul, H. (1995). Recursive approach of updating input-output coefficients. In U. Derigs, A. Bachem, A. Drexl (Eds.). Operations Research Proceedings (pp. 370-375). Berlin.
doi.org/10.1007/978-3-642-79459-9_67

11. Rey, S. J., West, G. R., & Janikas, M. V. (2004). Uncertainty in Integrated Models. Economic System Research Journal of International Input-Output Association, 16, 259-277.
doi.org/10.1080/0953531042000239365

12. Girko, V. L. (1976). Random matrices. Kiev: Naukova dumka [in Russian].

13. Yastremskij, A. I. (1992). Modeling of probabilistic and adaptive properties of the static interindustry balance using stochastic models and methods. Economics and mathematical methods, Vol. 28, No. 4, 612-624 [in Russian].

14. Gurgul, H., Majdosz, P. (2005). Key Sector Analysis: A Case of the Transited Polish Economy. Retrieved from www.fm-kp.si/zalozba/ISSN/1581-6311/3_095-111.pdf.

15. Yastremskii, O. (2013). Price of uncertainty in economic policy and entrepreneurship. In R. Motoryn, E. Nowak (Eds.). Quantitative methods in accounting and finance (pp. 229-233). Kyiv: Ukrainian State University of Finance and International Trade.

16. State Statistics Service of Ukraine. (2014). Tables "input-output of Ukraine in basic prices". Retrieved from www.ukrstat.gov.ua [in Ukrainian].

17. BEA. (n. d.). Use Tables /After Redefinitions / Producer Value - Use of commodities by industry after reallocation of inputs associated with redefined secondary production 1997-2015: 15 Industries. Retrieved from www.bea.gov/industry/io_annual.htm.

18. State Statistics Service of Ukraine. (2009). Table "input-output" for 2005 under the expanded program. Analytical materials. Retrieved from www.ukrstat.gov.ua [in Ukrainian].

19. Central Statistical Office of Poland. (2012). Poland Statistics Yearbook 2012. Retrieved from www.stat.gov.pl.

20. Yastrems'ky'j, O. (2014). Comparative analysis of the structure of national economies: Ukraine (2005, 2011 years) - Poland (2005 year). Foreign trade: economics, finance, law, 1, 112-119 [in Ukrainian].

21. Yastremskij, A. I. (1972). Some properties of the stochastic analogue of the Leontief model. Cybernetics, 4 [in Russian]. (Yastremskii, A. I. (1972). Some properties of the stochastic analog of Leont'ev's model. Cybernetics and System Analysis, 8 (4), 689-691).
doi.org/10.1007/BF01068294