National Interests: Priorities and Security

Econometric modeling and forecasting of economic security of the cross-sectoral complex

Vol. 14, Iss. 6, JUNE 2018

Received: 28 February 2018

Received in revised form: 18 March 2018

Accepted: 6 April 2018

Available online: 15 June 2018


JEL Classification: F52

Pages: 1020–1033

Akberdina V.V. Institute of Economics, Ural Branch of Russian Academy of Sciences, Yekaterinburg, Russian Federation

Smirnova O.P. Institute of Economics, Ural Branch of Russian Academy of Sciences, Yekaterinburg, Russian Federation

Importance The article unfolds capabilities of econometric models to forecast the economic security of a cross-sectoral complex.
Objectives We formulate the definition of cross-sectoral complex, overview the principal methods of econometric modeling and forecasting of trends in regional sectoral markets. The article indicates the main components of the economic security in the cross-sectoral complex and analyzes how economic security constituents influence the integral indicator.
Methods The research is based on the methodology for forecasting structural, spatial and timing trends in cross-sectoral complexes, including new and specified modeling and forecasting methods.
Results The article defines the terms cross-sectoral complex, economic security of the Russian cross-sectoral complex. We prove the economic security level of certain enterprises depends on changes in the network chain. We assess the effect of networked production enterprises on the construction sector.
Conclusions and Relevance Setting up a large-scale simulation model is the most complicated approach to forecasting the economic security of the cross-sectoral complex. Econometric modeling and forecasting procedures help construct, assess and make decisions with big non-linear data. The system of non-linear equations can be simultaneous, while containing dynamic and lagging data. Econometric modeling facilitate automated computations of any derivatives needed for assessment and modeling purposes.

Keywords: cross-sectoral complex, econometric model, forecasting, economic security


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