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Forecasting electricity consumption in Pakistan: the way forward

Author

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  • Hussain, Anwar
  • Rahman, Muhammad
  • Memon, Junaid Alam

Abstract

Growing shortfall of electricity in Pakistan affects almost all sectors of its economy. For proper policy formulation, it is imperative to have reliable forecasts of electricity consumption. This paper applies Holt-Winter and Autoregressive Integrated Moving Average (ARIMA) models on time series secondary data from 1980 to 2011 to forecast total and component wise electricity consumption in Pakistan. Results reveal that Holt-Winter is the appropriate model for forecasting electricity consumption in Pakistan. It also suggests that electricity consumption would continue to increase throughout the projected period and widen the consumption-production gap in case of failure to respond the issue appropriately. It further reveals that demand would be highest in the household sector as compared to all other sectors and the increase in the energy generation would be less than the increase in total electricity consumption throughout the projected period. The study discuss various options to reduce the demand-supply gap and provide reliable electricity to different sectors of the economy.

Suggested Citation

  • Hussain, Anwar & Rahman, Muhammad & Memon, Junaid Alam, 2016. "Forecasting electricity consumption in Pakistan: the way forward," Energy Policy, Elsevier, vol. 90(C), pages 73-80.
  • Handle: RePEc:eee:enepol:v:90:y:2016:i:c:p:73-80
    DOI: 10.1016/j.enpol.2015.11.028
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    as
    1. Hamzacebi, Coskun, 2007. "Forecasting of Turkey's net electricity energy consumption on sectoral bases," Energy Policy, Elsevier, vol. 35(3), pages 2009-2016, March.
    2. Ediger, Volkan S. & Akar, Sertac, 2007. "ARIMA forecasting of primary energy demand by fuel in Turkey," Energy Policy, Elsevier, vol. 35(3), pages 1701-1708, March.
    3. Peter R. Winters, 1960. "Forecasting Sales by Exponentially Weighted Moving Averages," Management Science, INFORMS, vol. 6(3), pages 324-342, April.
    4. Christopher A. Sims, 1986. "Are forecasting models usable for policy analysis?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 10(Win), pages 2-16.
    5. Nawaz, Saima & Iqbal, Nasir & Anwar, Saba, 2014. "Modelling electricity demand using the STAR (Smooth Transition Auto-Regressive) model in Pakistan," Energy, Elsevier, vol. 78(C), pages 535-542.
    6. Asad Zaman, 2012. "Methodological Mistakes and Econometric Consequences," International Econometric Review (IER), Econometric Research Association, vol. 4(2), pages 99-122, September.
    7. Stekler, H. O., 1991. "Macroeconomic forecast evaluation techniques," International Journal of Forecasting, Elsevier, vol. 7(3), pages 375-384, November.
    8. Taylor, James W., 2008. "An evaluation of methods for very short-term load forecasting using minute-by-minute British data," International Journal of Forecasting, Elsevier, vol. 24(4), pages 645-658.
    9. 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.
    10. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
    11. repec:pid:wpaper:2012:4 is not listed on IDEAS
    12. Mohammadi, Hassan & Su, Lixian, 2010. "International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models," Energy Economics, Elsevier, vol. 32(5), pages 1001-1008, September.
    13. Kavasseri, Rajesh G. & Seetharaman, Krithika, 2009. "Day-ahead wind speed forecasting using f-ARIMA models," Renewable Energy, Elsevier, vol. 34(5), pages 1388-1393.
    14. Muhammad Nasir & Muhammad Salman Tariq & Ankasha Arif, 2008. "Residential Demand for Electricity in Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 47(4), pages 457-467.
    15. Saima Nawaz & Nasir Iqbal & Saba Anwar, 2013. "Electricity Demand in Pakistan: A Nonlinear Estimation," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 52(4), pages 479-492.
    16. Rashid Amjad & Musleh Ud Din & Idrees Khawaja & Nasir Iqbal & Ahmad Waqar Qasim, 2012. "Fiscal Federalism In Pakistan," PIDE Monograph Series 2012:4, Pakistan Institute of Development Economics.
    17. Afia Malik, 2012. "Power Crisis in Pakistan: A Crisis in Governance?," PIDE Monograph Series 2012:1, Pakistan Institute of Development Economics.
    18. S. A. Roberts, 1982. "A General Class of Holt-Winters Type Forecasting Models," Management Science, INFORMS, vol. 28(7), pages 808-820, July.
    19. Melvin J. Hinich, 1982. "Testing For Gaussianity And Linearity Of A Stationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(3), pages 169-176, May.
    20. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
    21. Brown, Ld & Rozeff, Ms, 1979. "Univariate Time-Series Models Of Quarterly Accounting Earnings Per Share - Proposed Model," Journal of Accounting Research, Wiley Blackwell, vol. 17(1), pages 179-189.
    22. Larson, Bruce A. & Bromley, Daniel W., 1990. "Property rights, externalities, and resource degradation : Locating the tragedy," Journal of Development Economics, Elsevier, vol. 33(2), pages 235-262, October.
    23. Sheikh, Munawar A., 2010. "Energy and renewable energy scenario of Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 354-363, January.
    24. J W Taylor, 2003. "Short-term electricity demand forecasting using double seasonal exponential smoothing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 799-805, August.
    25. Ramanathan, R., 1999. "Short- and long-run elasticities of gasoline demand in India: An empirical analysis using cointegration techniques," Energy Economics, Elsevier, vol. 21(4), pages 321-330, August.
    26. Tanvir Khan, 2011. "Identifying an appropriate forecasting model for forecasting total import of Bangladesh," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 12(1), pages 179-192, August.
    27. Saab, Samer & Badr, Elie & Nasr, George, 2001. "Univariate modeling and forecasting of energy consumption: the case of electricity in Lebanon," Energy, Elsevier, vol. 26(1), pages 1-14.
    28. Paul Goodwin, 2010. "The Holt-Winters Approach to Exponential Smoothing: 50 Years Old and Going Strong," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 19, pages 30-33, Fall.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Projections; Energy; Forecasting model; Forecast evaluation; Sectorial energy consumption;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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