IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v31y2006i12p2129-2141.html
   My bibliography  Save this article

Comparing linear and nonlinear forecasts for Taiwan's electricity consumption

Author

Listed:
  • Pao, Hsiao-Tien

Abstract

This paper uses linear and nonlinear statistical models, including artificial neural network (ANN) methods, to investigate the influence of the four economic factors, which are the national income (NI), population (POP), gross of domestic production (GDP), and consumer price index (CPI) on the electricity consumption in Taiwan and then to develop an economic forecasting model. Both methods agree that POP and NI influence electricity consumption the most, whereas GDP the least. The results of comparing the out-of-sample forecasting capabilities of the two methods indicate the following. (1) If given a large amount of historical data, the forecasts of ARMAX are better than the other linear models. (2) The linear model is weaker on foretelling peaks and bottoms regardless the amount of historical data. (3) The forecasting performance of ANN is higher than the other linear models based on two sets of historical data considered in the paper. This is probably due to the fact that the ANN model is capable of catching sophisticated nonlinear integrating effects through a learning process. To sum up, the ANN method is more appropriate than the linear method for developing a forecasting model of electricity consumption. Moreover, researchers can employ either ANN or linear model to extract the important economic factors of the electricity consumption in Taiwan.

Suggested Citation

  • Pao, Hsiao-Tien, 2006. "Comparing linear and nonlinear forecasts for Taiwan's electricity consumption," Energy, Elsevier, vol. 31(12), pages 2129-2141.
    • Handle: RePEc:eee:energy:v:31:y:2006:i:12:p:2129-2141
    DOI: 10.1016/j.energy.2005.08.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544205001775
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2005.08.010?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Egelioglu, F. & Mohamad, A.A. & Guven, H., 2001. "Economic variables and electricity consumption in Northern Cyprus," Energy, Elsevier, vol. 26(4), pages 355-362.
    2. Yang, Hao-Yen, 2000. "A note on the causal relationship between energy and GDP in Taiwan," Energy Economics, Elsevier, vol. 22(3), pages 309-317, June.
    3. Ranjan, Manish & Jain, V.K., 1999. "Modelling of electrical energy consumption in Delhi," Energy, Elsevier, vol. 24(4), pages 351-361.
    4. Koli Fatai & Les Oxley & Frank G. Scrimgeour, 2003. "Modeling and Forecasting the Demand for Electricity in New Zealand: A Comparison of Alternative Approaches," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 75-102.
    5. Shiu, Alice & Lam, Pun-Lee, 2004. "Electricity consumption and economic growth in China," Energy Policy, Elsevier, vol. 32(1), pages 47-54, January.
    6. Yee Yan, Yuk, 1998. "Climate and residential electricity consumption in Hong Kong," Energy, Elsevier, vol. 23(1), pages 17-20.
    7. Soytas, Ugur & Sari, Ramazan, 2003. "Energy consumption and GDP: causality relationship in G-7 countries and emerging markets," Energy Economics, Elsevier, vol. 25(1), pages 33-37, January.
    8. Darbellay, Georges A. & Slama, Marek, 2000. "Forecasting the short-term demand for electricity: Do neural networks stand a better chance?," International Journal of Forecasting, Elsevier, vol. 16(1), pages 71-83.
    9. 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.
    10. Won-Young Lee, 1997. "The Case of Korea," Palgrave Macmillan Books, in: Peter J. Buckley & Jaime Campos & Hafiz Mirza & Eduardo White (ed.), International Technology Transfer by Small and Medium-Sized Enterprises, chapter 14, pages 406-431, Palgrave Macmillan.
    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. 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.
    2. Lee, Chien-Chiang & Chien, Mei-Se, 2010. "Dynamic modelling of energy consumption, capital stock, and real income in G-7 countries," Energy Economics, Elsevier, vol. 32(3), pages 564-581, May.
    3. Odhiambo, Nicholas M., 2010. "Energy consumption, prices and economic growth in three SSA countries: A comparative study," Energy Policy, Elsevier, vol. 38(5), pages 2463-2469, May.
    4. Tiba, Sofien & Omri, Anis, 2017. "Literature survey on the relationships between energy, environment and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1129-1146.
    5. Zhang, Wenbin & Tian, Lixin & Wang, Minggang & Zhen, Zaili & Fang, Guochang, 2016. "The evolution model of electricity market on the stable development in China and its dynamic analysis," Energy, Elsevier, vol. 114(C), pages 344-359.
    6. Odhiambo, Nicholas M., 2009. "Electricity consumption and economic growth in South Africa: A trivariate causality test," Energy Economics, Elsevier, vol. 31(5), pages 635-640, September.
    7. Sofien, Tiba & Omri, Anis, 2016. "Literature survey on the relationships between energy variables, environment and economic growth," MPRA Paper 82555, University Library of Munich, Germany, revised 14 Sep 2016.
    8. Chen, Pei-Fen & Lee, Chien-Chiang, 2007. "Is energy consumption per capita broken stationary? New evidence from regional-based panels," Energy Policy, Elsevier, vol. 35(6), pages 3526-3540, June.
    9. Chor Foon Tang and Eu Chye Tan, 2012. "Electricity Consumption and Economic Growth in Portugal: Evidence from a Multivariate Framework Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    10. Lee, Chien-Chiang & Chang, Chun-Ping, 2007. "The impact of energy consumption on economic growth: Evidence from linear and nonlinear models in Taiwan," Energy, Elsevier, vol. 32(12), pages 2282-2294.
    11. Lai, T.M. & To, W.M. & Lo, W.C. & Choy, Y.S., 2008. "Modeling of electricity consumption in the Asian gaming and tourism center—Macao SAR, People's Republic of China," Energy, Elsevier, vol. 33(5), pages 679-688.
    12. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio, 2009. "Electricity consumption forecasting in Italy using linear regression models," Energy, Elsevier, vol. 34(9), pages 1413-1421.
    13. Paul, Biru Paksha & Uddin, Gazi Salah, 2011. "Energy and output dynamics in Bangladesh," Energy Economics, Elsevier, vol. 33(3), pages 480-487, May.
    14. Belloumi, Mounir, 2009. "Energy consumption and GDP in Tunisia: Cointegration and causality analysis," Energy Policy, Elsevier, vol. 37(7), pages 2745-2753, July.
    15. Akinlo, A.E., 2009. "Electricity consumption and economic growth in Nigeria: Evidence from cointegration and co-feature analysis," Journal of Policy Modeling, Elsevier, vol. 31(5), pages 681-693, September.
    16. Hatemi-J, Abdulnasser & Uddin, Gazi Salah, 2012. "Is the causal nexus of energy utilization and economic growth asymmetric in the US?," Economic Systems, Elsevier, vol. 36(3), pages 461-469.
    17. Cheratian, Iman & Goltabar, Saleh, 2017. "Energy Consumption and Regional Economic Growth: The Case of Iranian Manufacturing Sector," MPRA Paper 78315, University Library of Munich, Germany.
    18. Ozturk, Ilhan, 2010. "A literature survey on energy-growth nexus," Energy Policy, Elsevier, vol. 38(1), pages 340-349, January.
    19. Lai, T.M. & To, W.M. & Lo, W.C. & Choy, Y.S. & Lam, K.H., 2011. "The causal relationship between electricity consumption and economic growth in a Gaming and Tourism Center: The case of Macao SAR, the People’s Republic of China," Energy, Elsevier, vol. 36(2), pages 1134-1142.
    20. Akkemik, K. Ali & Göksal, Koray, 2012. "Energy consumption-GDP nexus: Heterogeneous panel causality analysis," Energy Economics, Elsevier, vol. 34(4), pages 865-873.

    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:eee:energy:v:31:y:2006:i:12:p:2129-2141. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.