Vector Model of Autoregression of Indicators of Industrial Activity of a Construction Enterprise
DOI:
https://doi.org/10.14529/cmse180302Keywords:
economic-mathematical model, vector autoregression, VAR-model, management, system, econometrics, production functionAbstract
The article analyzes the existing economic-mathematical models: correlation-regression analysis, production functions, systems of econometric equations; their general form, calculation formulas are shown, their strengths and weaknesses are revealed, a vector model of autoregression of the main indices of the production activity of the construction enterprise is proposed (labor productivity, product profitability, mechanical strength (technical level of construction machines and equipment), relative strength of the management team, timeliness of implementation works, discreteness of resource use, product cost, product quality) on the basis of the VAR model construction. As a basis for constructing a VAR-model of autoregressive indicators of the production activity of a construction enterprise, the authors suggest using a system of three interrelated equations. The advantages and disadvantages of the vector model of autoregression are presented, as well as the results of estimating the coefficients in the VAR model. The resulting values of the coefficients were analyzed using Granger's causality test, based on the analysis of the cause-effect relationship between time series. The article defines the impulse response function that describes the response of a dynamic series in response to some external shocks. The graphs of the responses of the main resultant indicators of the activity of the construction enterprise are constructed. The hypotheses put forward in the article are checked based on the use of the F-test and the LM-test. The authors analyze in detail the results of calculations and convincingly prove the relevance of the methodology proposed in the article.
References
Bannikov V.A. Vector Models of Autoregressive and Correction of Regression Residues (Eviews). Prikladnaya ekonomika [Applied Econometrics]. 2006. no. 3. pp. 96–129. (in Russian)
Gelrud Y.D. Loginovskiy O.V. The Information Analytical System of Project Management Based on the Use of Complex Mathematical Models of the Functioning of the Stakeholders. Vestnik Yuzho-Uralskogo gosudarstvennogo universiteta. Seriya: Kompyuternye tekhnologii, upravlenie, radioehlektronika [Bulletin of the South UralState University. Ser. Computer Technologies, Automatic Control, Radio Electronics]. 2015, vol. 15, no. 3, pp. 133–141. (in Russian) DOI: 10.14529/ctcr150316
Gusev E.V., Ugryumov E.A., Shepelev I.G. Organizational and Economic Bases of Competitiveness of Construction Enterprises. Vestnik Yuzho-Uralskogo gosudarstvennogo universiteta. Seriya: Ekonomika i menedzhment [Bulletin of the South Ural State University. Economy and Management series]. 2013. vol. 7, no. 1. pp. 107–110. (in Russian)
Klimov G.P. Teoriya veroyatnostey i matematicheskaya statistika. [Theory of Probability and Mathematical Statistics]. Moscow, MSU, 2011. 368 p.
Litvak B.G. Ekspertnaya informatsiya: metody polucheniya i analiza. [Expert Information: Methods of Receiving and Analysis]. Мoscow, Radio and communication, 2008. 184 p.
Kantorovich G.G. Analysis of time series. Ehkonomicheskij zhurnal Vysshej shkoly ehkonomiki [The Economic Journal of the Higher School of Economics]. 2003. vol. 7, no. 1. pp. 79–103. (in Russian)
Akhtulov A.L., Akhtulova L.N., Leonova A.V., Ovsyannikov A.V. Economicmathematical model of decision-making in resource management of organizations. Omskij nauchnyj vestnik [Omsk Scientific Bulletin]. 2015. no. 1(135). pp. 168–172. (in Russian)
Tuktamysheva L.M. Approach to Mathematical Modeling of Multidimensional Time Series. Universitetskij kompleks kak regionalnyj centr obrazovaniya nauki i kultury: materialy Vseros nauch.-metod konf. 29–31 yanv 2014, g. Orenburg [University Complex as a Regional Center of Education, Science and Culture: Materials All-Russ. scientificmethod. Conf., January 2–31. 2014, Orenburg]. FGBOU HPE "Orenburg State University". Orenburg, 2014. pp. 126–131. (in Russian)
James D. Hamilton. Time Series Analysis. Library of Congress-In-Publication Data. Princeton University Press, New Jersey, 1994. 154 p.
Ugryumov E.A., Shindina Т.А. Intellectual Data Analysis of Production Profitability Influence on the Competitiveness of Construction Enterprises. Journal of Applied Economic Sciences. 2016. vol. 11, no. 8(46). pp. 112–118.


