IDEAS home Printed from https://ideas.repec.org/a/vrs/suvges/v33y2023i2p27-48n2.html
   My bibliography  Save this article

Analysis of the Nature and Determinants of Energy Price Dynamics in Sub-Saharan Africa (SSA)

Author

Listed:
  • Ifeacho Christopher I

    (School of Economic Sciences, Faculty of Economic and Management Sciences, North-West University, Vanderbijlpark, North West, South Africa, Christopher.ifeacho@gmail.com)

  • Choga Ireen

    (School of Economic Sciences, Faculty of Economic and Management Sciences, North-West University, Vanderbijlpark, North West, South Africa)

Abstract

Energy is one of the most important resources needed for growth, and consumption is an indicator to measure the development of a country. Sub-Saharan Africa (SSA) is among the sub-regions in the world with the lowest energy use per capita and one of the reasons for this is the energy price dynamics that have affected energy policy that can engender sustainable economic growth. The main objective of the study is to assess the nature and determinants of energy price dynamics in SSA using 21 countries with a complete dataset between 1980 and 2017 on variables such as energy consumption, exchange rate, and inflation rate, while energy price index and federal fund rate are also included as exogenous variables. EGARCH is used to derive the nature of energy dynamics, while panel-ARDL is used to investigate the determinants of energy price dynamics. The results show that energy price dynamics are asymmetric in nature, while the federal fund rate and exchange rate remain the most important factors influencing energy price dynamics in the sub-region. The finding is contrary to the symmetric energy price obtained by some previous authors who used oil price to proxy energy price. This study used aggregated values of energy prices, which include renewable and non-renewable energy. The implication of the findings is that currency devaluation and rise in federal fund rate aggravate the dynamics in energy piece and this causes much more macroeconomic instabilities in SSA. It is recommended that SSA countries should be cautious to embrace currency devaluation policy, and should reduce dependency on the importation of renewable energy products.

Suggested Citation

  • Ifeacho Christopher I & Choga Ireen, 2023. "Analysis of the Nature and Determinants of Energy Price Dynamics in Sub-Saharan Africa (SSA)," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 33(2), pages 27-48, June.
  • Handle: RePEc:vrs:suvges:v:33:y:2023:i:2:p:27-48:n:2
    DOI: 10.2478/sues-2023-0007
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/sues-2023-0007
    Download Restriction: no

    File URL: https://libkey.io/10.2478/sues-2023-0007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507, Elsevier.
    2. Mulder, Peter & de Groot, Henri L.F. & Pfeiffer, Birte, 2014. "Dynamics and determinants of energy intensity in the service sector: A cross-country analysis, 1980–2005," Ecological Economics, Elsevier, vol. 100(C), pages 1-15.
    3. Demachi, Kazue, 2012. "The effect of crude oil price change and volatility on Nigerian economy," MPRA Paper 41413, University Library of Munich, Germany.
    4. Wu, Jianxin & Ma, Chunbo & Tang, Kai, 2019. "The static and dynamic heterogeneity and determinants of marginal abatement cost of CO2 emissions in Chinese cities," Energy, Elsevier, vol. 178(C), pages 685-694.
    5. Mr. Ruy Lama & Juan Pablo Medina Guzman, 2015. "Fiscal Consolidation During Times of High Unemployment: The Role of Productivity Gains and Wage Restraint," IMF Working Papers 2015/262, International Monetary Fund.
    6. Obinna Ubani, 2013. "Determinants of the dynamics of electricity consumption in Nigeria," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 37(2), pages 149-161, June.
    7. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    8. Zarnikau, J. & Tsai, C.H. & Woo, C.K., 2020. "Determinants of the wholesale prices of energy and ancillary services in the U.S. Midcontinent electricity market," Energy, Elsevier, vol. 195(C).
    9. Mosquera-López, Stephanía & Nursimulu, Anjali, 2019. "Drivers of electricity price dynamics: Comparative analysis of spot and futures markets," Energy Policy, Elsevier, vol. 126(C), pages 76-87.
    10. Wang, TianTian & Zhang, Dayong & Clive Broadstock, David, 2019. "Financialization, fundamentals, and the time-varying determinants of US natural gas prices," Energy Economics, Elsevier, vol. 80(C), pages 707-719.
    11. Shiferaw, Yegnanew A., 2019. "Time-varying correlation between agricultural commodity and energy price dynamics with Bayesian multivariate DCC-GARCH models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    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. Díaz Antonia & Puch Luis A., 2019. "Investment, technological progress and energy efficiency," The B.E. Journal of Macroeconomics, De Gruyter, vol. 19(2), pages 1-28, June.
    2. Gupta, Aparna & Palepu, Sai, 2024. "Designing risk-free service for renewable wind and solar resources," European Journal of Operational Research, Elsevier, vol. 315(2), pages 715-728.
    3. Abate, Megersa, 2014. "Does fuel price affect trucking industry’s network characteristics?: evidence from Denmark," Working papers in Transport Economics 2014:26, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    4. Mejia, Paula & Meléndez Arjona, Marcela, 2012. "Middle-Class Entrepreneurs and Social Mobility through Entrepreneurship in Colombia," IDB Publications (Working Papers) 4082, Inter-American Development Bank.
    5. Inmaculada Garc�a-Mainar & V�ctor M. Montuenga-G�mez, 2017. "Subjective educational mismatch and signalling in Spain," Documentos de Trabajo dt2017-03, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
    6. Vincent Brémond & Emmanuel Hache & Tovonony Razafindrabe, 2016. "The Oil Price and Exchange Rate Relationship Revisited: A time-varying VAR parameter approach," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 97-131, June.
    7. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
    8. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    9. Xuejun Wang & Aiting Shen & Zhiyong Chen & Shuhe Hu, 2015. "Complete convergence for weighted sums of NSD random variables and its application in the EV regression model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 166-184, March.
    10. Maïlys Korber, 2019. "Does Vocational Education Give a Labour Market Advantage over the Whole Career? A Comparison of the United Kingdom and Switzerland," Social Inclusion, Cogitatio Press, vol. 7(3), pages 202-223.
    11. Duc Huynh, Toan Luu & Burggraf, Tobias & Nasir, Muhammad Ali, 2020. "Financialisation of natural resources & instability caused by risk transfer in commodity markets," Resources Policy, Elsevier, vol. 66(C).
    12. Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2014. "Are there gains from pooling real-time oil price forecasts?," Energy Economics, Elsevier, vol. 46(S1), pages 33-43.
    13. Jacks, David S. & Stuermer, Martin, 2020. "What drives commodity price booms and busts?," Energy Economics, Elsevier, vol. 85(C).
    14. Jing Bai & Chuang Tu & Jiming Bai, 2024. "Measuring and decomposing Beijing’s energy performance: an energy- and exergy-based perspective," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(7), pages 17617-17633, July.
    15. Uddin, Gazi Salah & Tang, Ou & Sahamkhadam, Maziar & Taghizadeh-Hesary, Farhad & Yahya, Muhammad & Cerin, Pontus & Rehme, Jakob, 2021. "Analysis of Forecasting Models in an Electricity Market under Volatility," ADBI Working Papers 1212, Asian Development Bank Institute.
    16. Verbeek, M.J.C.M. & Nijman, T.E., 1990. "Can cohort data be treated as genuine panel data?," Other publications TiSEM 17fd5894-9eef-426e-b402-0, Tilburg University, School of Economics and Management.
    17. Andrzej Cieślik & Bartłomiej Rokicki, 2016. "Individual wages and regional market potential," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 24(4), pages 661-682, October.
    18. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
    19. Ferrari, Davide & Ravazzolo, Francesco & Vespignani, Joaquin, 2021. "Forecasting energy commodity prices: A large global dataset sparse approach," Energy Economics, Elsevier, vol. 98(C).
    20. Tullio Jappelli & Marco Pagano, 1994. "Personal Saving in Italy," NBER Chapters, in: International Comparisons of Household Saving, pages 237-268, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    Energy price dynamics; asymmetric; determinants; Sub Saharan Africa (SSA);
    All these keywords.

    JEL classification:

    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    Statistics

    Access and download statistics

    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:vrs:suvges:v:33:y:2023:i:2:p:27-48:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.