MODELING THE INFLUENCE OF CAPITAL STRUCTURE ON THE EFFECTIVENESS IN THE COMMODITY ENTERPRISES

Analysis of the impact and the value of liabilities on the effectiveness of the company is one of the most important tasks of the financial management. From the approach, used when determining the structure of sources of financing for the company and its ongoing innovation projects, depends the level of profit, and hence the worth of business. This article is the first to present the analysis of the impact the capital structure has, on the efficiency of mining and processing of coal and oil in Russia. The share ofdebt capital in these companies is low, the cost of its use, on the contrary, is high, but it is due to the debt capital that development projects are financed, and it is important for companies to use these funds efficiently. In addition, the increase in the proportion of debt capital can ensure the growth of return on equity. As a measure of the efficient use of the borrowed funds the authors used the ROA (return on assets) indicator. As a result of the conducted research models of the statistical relationship between profitability and indicators were constructed, characterizing financial condition ofenterprises, in particular, long-term and short-term obligations. Negative impact on the efficiency of the value of obligations, regardless of their structure, was revealed. Additionally, the analysis proved a significant dependence of the efficiency of the use ofborrowed funds on the type ofcompanies (in accordance with the NACE codes), along with the negative impact of the tax burden. To solve this problem the authors used panel regression models with random effects. The selection of the type of model is explained by the occurrence of the number of independent variables, the value of which does not change over time.

модель статистической взаимосвязи, показатели прибыльности предприятия, финансовые обязательства (заемный капитал) предприятия, добыча и переработка угля и нефти, панельная регрессия, model of the statistical relationship, profitability of the enterprise, financial liabilities (borrowing) of enterprises, mining and processing of coal and oil, panel regression

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