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Economic Analysis: Theory and Practice
 

Using econometric models to make management decisions at oil and gas enterprises

Vol. 21, Iss. 4, APRIL 2022

Received: 27 March 2022

Received in revised form: 6 April 2022

Accepted: 17 April 2022

Available online: 28 April 2022

Subject Heading: MATHEMATICAL METHODS AND MODELS

JEL Classification: C53, F47

Pages: 765–779

https://doi.org/10.24891/ea.21.4.765

Tat'yana Yu. KUDRYAVTSEVA Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation
tankud28@mail.ru

https://orcid.org/0000-0003-1403-3447

Evgeniya A. KOZLOVA Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation
kozlovaevgeiya@list.ru

ORCID id: not available

Subject. At present, there is a need to increase the flexibility of exporting companies and gas traders to ensure the stability and continuity of supplies in the European gas market. The specialized literature does not fully present scientifically based methods and algorithms, according to which a management decision can be made on the problem.
Objectives. Our aim is to develop a methodology enabling to qualitatively and quantitatively substantiate the feasibility of building a certain portfolio of capacities, and to evaluate the effects of its implementation.
Methods. The study draws on general scientific research methods.
Results. We developed and tested a model that allows modeling and forecasting of high-frequency time series, using VARMA and ARIMA econometric models, to make accurate and reasonable short- and medium-term decisions, and to generate a growth strategy for enterprises operating in the oil and gas industry.
Conclusions. Our findings correspond to the qualitative and quantitative assessment of the International Energy Agency, thus confirming that the model is relevant for use in the oil and gas industry. The findings can be applied in educational process in the field of ‘macroeconomics’, ‘econometrics’, in the implementation of operational and strategic planning at enterprises. They also can be useful for research and development, including testing at enterprises of other sectors and industries.

Keywords: VARMA model, demand modeling, demand forecasting, high-frequency data, management decision

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