Journal of Applied Economic Research
ISSN 2712-7435
Forecasting The Prices For Ferrous Scrap As A Key Factor Of The Resourcing System Of Metallurgical Enterprise
Tikhonovskaya I.D.
Abstract
The article examines the aspect of the resourcing system, or more specifically the system of ferrous scrap provision at metallurgical enterprises that operate electric steel production facilities. It is determined that the primary goal of this system is to minimize the cost of resources. This is also a necessary precondition for enhancing the competitiveness of an enterprise as the impact of negative environmental factors on the steel industry is growing. Purchase prices for ferrous scrap that are set by metallurgical enterprises and that represent one of the target indicators of the resourcing system along with the scrap purchase volume essentially depend on market conditions. The price level for ferrous scrap in the Russian market is one of the key factors of the external environment, influencing resourcing and management decisions as to its target indicators. The aim of the article is to create high-quality econometric models of forecasting prices of Grade 3A scrap in the Russian market. The method of multiple regression is chosen among the statistics methods of forecasting that is commonly used for dealing with similar problems of an industrial nature. Considerable attention is paid to practical aspects of forecasting. Three types of up-to-date econometric models are proposed; the interpretation of parameters and the forecast for the period from January to September 2015 are done. A conclusion is drawn about the possibility of using the models in management in metallurgical enterprises. It is expected that the forecast results will contribute to improving the existing resourcing system, especially as regards the preparation of data for further use in the formation of an optimal schedule of scrap purchase volumes for a metallurgical company.
Keywords
Key words: resourcing; metallurgical enterprise; EAF production; ferrous scrap; competitiveness; system; indicator; environment; price; forecasting; factor; multiple regression; predictor; improvement; purchase volume.
About Authors
DOI: http://dx.doi.org/10.15826/vestnik.2016.15.1.06
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