IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2021-01-30.html
   My bibliography  Save this article

The Determinants and Forecasting of Electricity Consumption in Pakistan

Author

Listed:
  • Fazle Wahid

    (Department of Economics, Islamia College, Peshawar,)

  • Hamid Ullah

    (Department of Management Science, Islamia College, Peshawar,)

  • Sher Ali

    (Department of Economics, Islamia College, Peshawar)

  • Sajjad Ahmad Jan

    (Department of Economics, University of Peshawar,)

  • Abid Ali

    (Department of Economics, Islamia College, Peshawar)

  • Azhar Khan

    (Department of Business Administration Northern University, Nowshera)

  • Imran Ali Khan

    (Department of Business Administration Northern University, Nowshera)

  • Maryam Bibi

    (Department of Management Sciences, Abasyn University, Peshawar.)

Abstract

The current study examined the determinants of electricity consumption and also intends to forecast the electricity consumption in Pakistan. The study has used time series data analysis, applied Johansen Cointegration Test, error correction mechanisms and regression for examining determinants and autoregressive integrated moving average model is used for forecasting. The study has used times series secondary annual data on different variables for the period ranging from 1970 to 2018. The results of the study showed that gross domestic product and population have positive impact on electricity consumption. Whereas, National output (GDP) is statistically significant in the determination of total electricity consumption. The results also indicated that increase in the real economic activities has increases the total electricity consumption. Furthermore, the results of electricity consumption model also suggest that electricity price have negative impact on total electricity consumption. As electricity demand is inelastic to electricity price and income, it indicates that fewer substitutes of electricity are available in the market. Hence electricity is essential component of energy for economy. The results of the current study can be useful for the policymakers and government regulatory bodies relating to electricity.

Suggested Citation

  • Fazle Wahid & Hamid Ullah & Sher Ali & Sajjad Ahmad Jan & Abid Ali & Azhar Khan & Imran Ali Khan & Maryam Bibi, 2021. "The Determinants and Forecasting of Electricity Consumption in Pakistan," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 241-248.
    • Handle: RePEc:eco:journ2:2021-01-30
    as

    Download full text from publisher

    File URL: https://www.econjournals.com/index.php/ijeep/article/download/10646/5584
    Download Restriction: no
    File URL: https://www.econjournals.com/index.php/ijeep/article/view/10646/5584
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Muhammad Arshad Khan & Usman Ahmad, 2008. "Energy Demand in Pakistan: A Disaggregate Analysis," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 47(4), pages 437-455.
    2. Sher Ali & Fazle Wahid & Abid Ali, 2019. "Role of Energy in Economic Growth of Pakistan (1972-2015)," Global Social Sciences Review, Humanity Only, vol. 4(2), pages 221-230, June.
    3. Sahir, Mukhtar H. & Qureshi, Arshad H., 2007. "Specific concerns of Pakistan in the context of energy security issues and geopolitics of the region," Energy Policy, Elsevier, vol. 35(4), pages 2031-2037, April.
    4. Kankal, Murat & AkpInar, Adem & Kömürcü, Murat Ihsan & Özsahin, Talat Sükrü, 2011. "Modeling and forecasting of Turkey's energy consumption using socio-economic and demographic variables," Applied Energy, Elsevier, vol. 88(5), pages 1927-1939, May.
    5. Geem, Zong Woo, 2011. "Transport energy demand modeling of South Korea using artificial neural network," Energy Policy, Elsevier, vol. 39(8), pages 4644-4650, August.
    6. Halvorsen, Robert, 1975. "Residential Demand for Electric Energy," The Review of Economics and Statistics, MIT Press, vol. 57(1), pages 12-18, February.
    7. Sailor, David J. & Rosen, Jesse N. & Muñoz, J.Ricardo, 1998. "Natural gas consumption and climate: a comprehensive set of predictive state-level models for the United States," Energy, Elsevier, vol. 23(2), pages 91-103.
    8. Nasr, G. E. & Badr, E. A. & Dibeh, G., 2000. "Econometric modeling of electricity consumption in post-war Lebanon," Energy Economics, Elsevier, vol. 22(6), pages 627-640, December.
    9. Erdogdu, Erkan, 2007. "Electricity demand analysis using cointegration and ARIMA modelling: A case study of Turkey," Energy Policy, Elsevier, vol. 35(2), pages 1129-1146, February.
    10. De Vita, G. & Endresen, K. & Hunt, L.C., 2006. "An empirical analysis of energy demand in Namibia," Energy Policy, Elsevier, vol. 34(18), pages 3447-3463, December.
    11. Filippini, Massimo & Pachauri, Shonali, 2004. "Elasticities of electricity demand in urban Indian households," Energy Policy, Elsevier, vol. 32(3), pages 429-436, February.
    12. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    13. Narayan, Paresh Kumar & Wong, Philip, 2009. "A panel data analysis of the determinants of oil consumption: The case of Australia," Applied Energy, Elsevier, vol. 86(12), pages 2771-2775, December.
    14. Greene, David L. & Meddeb, Nabil & Liu, Jin-Tan, 1986. "Vehicle stock modelling of highway energy use : Tunisian and US applications," Energy Policy, Elsevier, vol. 14(5), pages 437-446, October.
    15. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio, 2009. "Electricity consumption forecasting in Italy using linear regression models," Energy, Elsevier, vol. 34(9), pages 1413-1421.
    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. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    2. Noel Alter & Shabib Haider Syed, 2011. "An Empirical Analysis of Electricity Demand in Pakistan," International Journal of Energy Economics and Policy, Econjournals, vol. 1(4), pages 116-139.
    3. Syed Aziz Ur Rehman & Yanpeng Cai & Rizwan Fazal & Gordhan Das Walasai & Nayyar Hussain Mirjat, 2017. "An Integrated Modeling Approach for Forecasting Long-Term Energy Demand in Pakistan," Energies, MDPI, vol. 10(11), pages 1-23, November.
    4. World Bank, 2011. "A New Slant on Slopes : Measuring the Benefits of Increased Electricity Access in Developing Countries," World Bank Publications - Reports 2742, The World Bank Group.
    5. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    6. Ziramba, Emmanuel, 2008. "The demand for residential electricity in South Africa," Energy Policy, Elsevier, vol. 36(9), pages 3460-3466, September.
    7. Irfan, Muhammad & Cameron, Michael P. & Hassan, Gazi, 2018. "Household energy elasticities and policy implications for Pakistan," Energy Policy, Elsevier, vol. 113(C), pages 633-642.
    8. Claudio Agostini & M. Cecilia Plottier & Eduardo Saavedra, 2012. "Residential Demand for Electric Energy in Chile," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(3), pages 64-83, December.
    9. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio & Minea, Alina A., 2010. "Analysis and forecasting of nonresidential electricity consumption in Romania," Applied Energy, Elsevier, vol. 87(11), pages 3584-3590, November.
    10. Kaytez, Fazil, 2020. "A hybrid approach based on autoregressive integrated moving average and least-square support vector machine for long-term forecasting of net electricity consumption," Energy, Elsevier, vol. 197(C).
    11. Günay, M. Erdem, 2016. "Forecasting annual gross electricity demand by artificial neural networks using predicted values of socio-economic indicators and climatic conditions: Case of Turkey," Energy Policy, Elsevier, vol. 90(C), pages 92-101.
    12. Tiwari, Aviral Kumar & Menegaki, Angeliki N., 2019. "A time varying approach on the price elasticity of electricity in India during 1975–2013," Energy, Elsevier, vol. 183(C), pages 385-397.
    13. Khan, Muhammad Arshad & Abbas, Faisal, 2016. "The dynamics of electricity demand in Pakistan: A panel cointegration analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1159-1178.
    14. Adewuyi, Adeolu O., 2016. "Determinants of import demand for non-renewable energy (petroleum) products: Empirical evidence from Nigeria," Energy Policy, Elsevier, vol. 95(C), pages 73-93.
    15. Halicioglu, Ferda, 2007. "Residential electricity demand dynamics in Turkey," Energy Economics, Elsevier, vol. 29(2), pages 199-210, March.
    16. Angelopoulos, Dimitrios & Siskos, Yannis & Psarras, John, 2019. "Disaggregating time series on multiple criteria for robust forecasting: The case of long-term electricity demand in Greece," European Journal of Operational Research, Elsevier, vol. 275(1), pages 252-265.
    17. Habeebur Rahman & Iniyan Selvarasan & Jahitha Begum A, 2018. "Short-Term Forecasting of Total Energy Consumption for India-A Black Box Based Approach," Energies, MDPI, vol. 11(12), pages 1-21, December.
    18. Adom, Philip Kofi & Bekoe, William, 2012. "Conditional dynamic forecast of electrical energy consumption requirements in Ghana by 2020: A comparison of ARDL and PAM," Energy, Elsevier, vol. 44(1), pages 367-380.
    19. Eric Fosu Oteng-Abayie & Prosper Awuni Ayinbilla & Maame Esi Eshun, 2018. "Macroeconomic Determinants of Crude Oil Demand in Ghana," Global Business Review, International Management Institute, vol. 19(4), pages 873-888, August.
    20. Paul Adjei Kwakwa & Solomon Aboagye, 2014. "Energy consumption in Ghana and the story of economic growth, industrialization, trade openness and urbanization," Asian Bulletin of Energy Economics and Technology, Asian Online Journal Publishing Group, vol. 1(1), pages 1-6.

    More about this item

    Keywords

    Determinants ; Electricity Consumptions; ARIMA; Pakistan;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • M53 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Training
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

    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:eco:journ2:2021-01-30. 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: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.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.