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An econometric approach on production, costs and profit in Romanian coal mining enterprises

Author

Listed:
  • Ioan Batrancea
  • Larissa Batrancea
  • Anca Nichita
  • Lucian Gaban
  • Ema Masca
  • Ioan-Dan Morar
  • Gheorghe Fatacean
  • Andrei Moscviciov

Abstract

Global economic growth is based on increased consumption of electricity both from renewable resources, such as water and wind and non-renewable resources, such as coal (lignite), natural gas or petroleum. Coal continues to represent an important energy source in the European Union, particularly in Germany, France and Spain, where it accounts for 15% of the primary energy, out of which 80% is used in electricity supply. The coal (lignite) mines from the Oltenia region contribute significantly to generating power in Romania. The study aims to show that an increase in production within the coal (lignite) mining industry can be determined by increasing direct and indirect costs or by increasing variable costs and profit. We also examine the non-linear relation between variable costs and production on the one hand and between profit and production on the other hand. Our results show that there is a concave relationship between variable costs and production, and also a concave relationship between profit and production, which indicate that Romanian coal enterprises have an optimal production level that maximises both variable costs and their profitability. In addition, a robustness check of our results confirms that variable costs and profitability decrease as they move away from their optimal level.

Suggested Citation

  • Ioan Batrancea & Larissa Batrancea & Anca Nichita & Lucian Gaban & Ema Masca & Ioan-Dan Morar & Gheorghe Fatacean & Andrei Moscviciov, 2019. "An econometric approach on production, costs and profit in Romanian coal mining enterprises," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 32(1), pages 1019-1036, January.
  • Handle: RePEc:taf:reroxx:v:32:y:2019:i:1:p:1019-1036
    DOI: 10.1080/1331677X.2019.1595080
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    Cited by:

    1. Izabela Zoltowska, 2024. "Risk Preferences of EV Fleet Aggregators in Day-Ahead Market Bidding: Mean-CVaR Linear Programming Model," Energies, MDPI, vol. 18(1), pages 1-19, December.

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