Some Aspects of Forecasting and Evaluating the Effectiveness of Investments in the System of Management of Oil Production and Refining Industry in the Region

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Abstract

The purpose of this work is quantifying the real volume of capital investment, which provides the required increase in production of crude oil. For the authors of particular interest is the analysis of the dynamics of total oil production spending by individual years or even quarters. This probabilistic analysis can show trends of this important process for the region’s budget. Usually one uses data on direct and complete oil exploration and production costs derived from balance sheet models to estimate the necessary investments. Such data are very approximate and do not provide an indication of the evolution of real costs of oil production in recent years or quarters, which is especially important in assessing the necessary investments. In the present paper, as a methodological basis for solving this problem, the authors propose to apply a well-developed apparatus of models (infinite) distributed lag and use the lag models of Koyck, Solow, Lew, Jorgenson. The result of the work is the construction of the mathematical model of capital investments in fixed assets of the oil-producing and oil-refining industry. Using the proposed model, it is shown how the efficiency of investments increases depending on the accuracy of estimates of capital investment lag and its structure. The conclusion indicates the possibilities of increasing the efficiency of the investment process by using of the capital investment lag model. The authors propose to synthesize the method of global optimization with the included distributed lag model, which is used according to the method proposed in the article.

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Silaev, A. A., Kuternin, M. I., Parshikova, G. Y., & Perfilyev, A. A. (2020). Some Aspects of Forecasting and Evaluating the Effectiveness of Investments in the System of Management of Oil Production and Refining Industry in the Region. In Lecture Notes in Networks and Systems (Vol. 129 LNNS, pp. 1653–1663). Springer. https://doi.org/10.1007/978-3-030-47945-9_176

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