IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i10p2271-d1390656.html
   My bibliography  Save this article

Global Energy Transition and the Efficiency of the Largest Oil and Gas Companies

Author

Listed:
  • Sami Jarboui

    (Department of Business Administration, Shaqra University, Al Quwaiiyah 19248, Saudi Arabia
    Department of Economics, Faculty of Economics and Management, University of Sfax, Sfax 3018, Tunisia)

  • Hind Alofaysan

    (Department of Economics, College of Business Administration, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia)

Abstract

The challenges posed by climate change and global warming loom large, necessitating a critical initial step towards the long-term growth and the enhancement of both environmental and operational efficiency. Within the energy sector, renewable energy sources are gaining increasing prominence. Consequently, traditional oil and gas companies (OGC) are undergoing a gradual transformation into comprehensive energy corporations, aligning themselves with energy transition policies. This paper examines two types of efficiency measures—operational and environmental—for the 20 largest OGC during the period of 2010–2019. Secondly, this research aims to explore the effect of the global energy transition on both environmental and operational efficiency. Based on three estimation methods, two estimation steps are used in this research. In the first step, the True Fixed Effect (TFE) model and the Battese and coelli (1995) SFA model are applied to evaluate, measure and compare the environmental and operational efficiency scores. In the second step, the TFE model and GMM approach for the dynamic panel data model are used to explore, evaluate and verify the effect of global energy transition on the environmental and operational efficiency of the largest 20 OGC in the world. The results reveal that the average operational efficiency of major OGC measured using the BC.95 model and TFE model is 66% and 85%, respectively, and the overall average level of environmental efficiency for OGC over a 10-year period is 31% (based to B.C.95 model) and 13% (based to TFE model). Our findings reveal that biofuels, solar and hydropower contribute to promote the operational and environmental efficiency of the largest 20 OGC. However, the analysis suggests that while the global energy transition significantly influences and bolsters environmental efficiency, its effect on operational efficiency among these major OGC remains less pronounced and insufficient.

Suggested Citation

  • Sami Jarboui & Hind Alofaysan, 2024. "Global Energy Transition and the Efficiency of the Largest Oil and Gas Companies," Energies, MDPI, vol. 17(10), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:10:p:2271-:d:1390656
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/10/2271/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/10/2271/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sami Jarboui, 2021. "Renewable energies and operational and environmental efficiencies of the US oil and gas companies: A True Fixed Effect model," Post-Print halshs-04233615, HAL.
    2. Al-Mana, Ali A. & Nawaz, Waqas & Kamal, Athar & Koҫ, Muammer, 2020. "Financial and operational efficiencies of national and international oil companies: An empirical investigation," Resources Policy, Elsevier, vol. 68(C).
    3. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    4. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LP, vol. 13(4), pages 718-758, December.
    5. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    6. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980, October.
    7. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    8. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    9. Atris, Amani Mohammed & Goto, Mika, 2019. "Vertical structure and efficiency assessment of the US oil and gas companies," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    10. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    11. Mehdi Farsi & Massimo Filippini & Michael Kuenzle, 2005. "Unobserved heterogeneity in stochastic cost frontier models: an application to Swiss nursing homes," Applied Economics, Taylor & Francis Journals, vol. 37(18), pages 2127-2141.
    12. Abir Mrabet & Sami Jarboui, 2017. "Do institutional factors affect the efficiency of GDP and CO 2 emission? Evidence from Gulf and Maghreb countries," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 40(5), pages 259-276.
    13. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    14. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sami Jarboui, 2022. "Operational and environmental efficiency of U.S. oil and gas companies towards energy transition policies: A comparative empirical analysis," Australian Economic Papers, Wiley Blackwell, vol. 61(2), pages 234-257, June.
    2. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    3. Hailu, Kidanemariam Berhe & Tanaka, Makoto, 2015. "A “true” random effects stochastic frontier analysis for technical efficiency and heterogeneity: Evidence from manufacturing firms in Ethiopia," Economic Modelling, Elsevier, vol. 50(C), pages 179-192.
    4. Massimo Filippini & William Greene, 2016. "Persistent and transient productive inefficiency: a maximum simulated likelihood approach," Journal of Productivity Analysis, Springer, vol. 45(2), pages 187-196, April.
    5. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    6. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    7. Cazals Catherine & Dudley Paul & Florens Jean-Pierre & Jones Michael, 2011. "The Effect of Unobserved Heterogeneity in Stochastic Frontier Estimation: Comparison of Cross Section and Panel with Simulated Data for the Postal Sector," Review of Network Economics, De Gruyter, vol. 10(3), pages 1-22, September.
    8. Keller, Michael, 2020. "Wasted windfalls: Inefficiencies in health care spending in oil rich countries," Resources Policy, Elsevier, vol. 66(C).
    9. Russ Kashian & Nicholas Lovett & Yuhan Xue, 2020. "Has the affordable care act affected health care efficiency?," Journal of Regulatory Economics, Springer, vol. 58(2), pages 193-233, December.
    10. Idaira Cabrera‐Suárez & Jorge V. Pérez‐Rodríguez, 2021. "Bank branch performance and cost efficiency: A stochastic frontier panel data approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5850-5863, October.
    11. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    12. Mehdi Farsi & Massimo Filippini & William Greene, 2005. "Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies," Journal of Regulatory Economics, Springer, vol. 28(1), pages 69-90, July.
    13. Catherine Cazals & Paul Dudley & Jean-Pierre Florens & Michael Jones, 2012. "A Panel Data Analysis of Inefficiency and Heterogeneity in the Postal Sector," Chapters, in: Michael A. Crew & Paul R. Kleindorfer (ed.), Multi-Modal Competition and the Future of Mail, chapter 8, Edward Elgar Publishing.
    14. Sebastian Linde, 2023. "Hospital cost efficiency: an examination of US acute care inpatient hospitals," International Journal of Health Economics and Management, Springer, vol. 23(3), pages 325-344, September.
    15. Hind Alofaysan & Sami Jarboui & Jawaher Binsuwadan, 2024. "Corporate Sustainability, Sustainable Governance, and Firm Value Efficiency: Evidence from Saudi Listed Companies," Sustainability, MDPI, vol. 16(13), pages 1-17, June.
    16. Alejandro Arvelo-Martín & Juan José Díaz-Hernández & Ignacio Abásolo-Alessón, 2019. "Hospital productivity bias when not adjusting for cost heterogeneity: The case of Spain," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-17, June.
    17. Laureti, Tiziana & Secondi, Luca & Biggeri, Luigi, 2014. "Measuring the efficiency of teaching activities in Italian universities: An information theoretic approach," Economics of Education Review, Elsevier, vol. 42(C), pages 147-164.
    18. Marta Zieba, 2011. "An Analysis of Technical Efficiency and Efficiency Factors for Austrian and Swiss Non-Profit Theatres," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 147(II), pages 233-274, June.
    19. Ben Amor, Tawfik & Mellah, Thuraya, 2023. "Cost efficiency of Tunisian water utility districts: Does heterogeneity matter?," Utilities Policy, Elsevier, vol. 84(C).
    20. Li, Hong-Zhou & Kopsakangas-Savolainen, Maria & Xiao, Xing-Zhi & Tian, Zhen-Zhen & Yang, Xiao-Yuan & Wang, Jian-Lin, 2016. "Cost efficiency of electric grid utilities in China: A comparison of estimates from SFA–MLE, SFA–Bayes and StoNED–CNLS," Energy Economics, Elsevier, vol. 55(C), pages 272-283.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:10:p:2271-:d:1390656. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.