Optimisation of the relationship between structural parameters of the processing industry as a way to increase its efficiency

Ishchuk Svitlana, Sozanskyy Luybomyr and Pukała Ryszard ()
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Ishchuk Svitlana: Institute of Regional Research named after M.I. Dolishniy of the NAS of Ukraine, Ukraine
Sozanskyy Luybomyr: Institute of Regional Research named after M.I. Dolishniy of the NAS of Ukraine, Ukraine
Pukała Ryszard: Bronislaw Markiewicz State Higher School of Technology and Economics, Poland

Engineering Management in Production and Services, 2020, vol. 12, issue 2, 7-20

Abstract: Industry, which on average accounts for about 60% of commodity exports in the EU-28, with over 58% resulting from the processing industry, plays a key role in ensuring the competitiveness of EU countries. The article aims to simulate the influence of structural processing industry parameters on the industry's efficiency. Correlation methods and the regression analysis were used to substantiate the hypotheses regarding the effect that the share comprised of high-tech and medium-high-tech industries has on the output structure, and the impact made by the share of imports in the intermediate consumption of those industries on the efficiency (the share of gross value added (GVA) in output) of the processing industry. Based on the criteria indicating the increased technological level and reduced import dependence, economic and mathematical models of optimisation were created for the output structure and intermediate consumption of the processing industry, which were then solved using the linear programming method. The authors present the mathematical proof of the relationship between the change in structural parameters (shares of high-tech and medium-tech industries and the share of imports in the structure of their intermediate consumption) of the processing industry and the ratio of the gross value added/output. The results of the simulation, which were based on data from the European Statistical Office and the Organization for Economic Cooperation and Development, provide an analytical basis for selecting industrial policy benchmarks.

Keywords: processing industry structure; efficiency; gross value added; share of output; share of imports; intermediate consumption; optimisation (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:ecoman:v:12:y:2020:i:2:p:7-20:n:1

DOI: 10.2478/emj-2020-0008

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