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Performance of combined double seasonal univariate time series models for forecasting water demand

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  • Jorge Caiado

    (CEMAPRE, School of Economics and Management (ISEG), Technical University of Lisbon)

Abstract

In this article, we examine the daily water demand forecasting performance of double seasonal univariate time series models (Holt-Winters, ARIMA and GARCH) based on multi-step ahead forecast mean squared errors. A within-week seasonal cycle and a within-year seasonal cycle are accommodated in the various model specifications to capture both seasonalities. We investigate whether combining forecasts from different methods for different origins and horizons could improve forecast accuracy. The analysis is made with daily data for water consumption in Granada, Spain.

Suggested Citation

  • Jorge Caiado, 2009. "Performance of combined double seasonal univariate time series models for forecasting water demand," CEMAPRE Working Papers 0903, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  • Handle: RePEc:cma:wpaper:0903
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    File URL: http://cemapre.iseg.utl.pt/archive/preprints/286.pdf
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    References listed on IDEAS

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    1. Sean D. Campbell & Francis X. Diebold, 2005. "Weather Forecasting for Weather Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 6-16, March.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Xiao-jun Wang & Jian-yun Zhang & Shamsuddin Shahid & En-hong Guan & Yong-xiang Wu & Juan Gao & Rui-min He, 2016. "Adaptation to climate change impacts on water demand," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 21(1), pages 81-99, January.
    2. Xiao-jun Wang & Jian-yun Zhang & Shamsuddin Shahid & En-hong Guan & Yong-xiang Wu & Juan Gao & Rui-min He, 2016. "Adaptation to climate change impacts on water demand," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 21(1), pages 81-99, January.
    3. Xiao-jun Wang & Jian-yun Zhang & Shahid Shamsuddin & Ru-lin Oyang & Tie-sheng Guan & Jian-guo Xue & Xu Zhang, 2017. "Impacts of climate variability and changes on domestic water use in the Yellow River Basin of China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(4), pages 595-608, April.

    More about this item

    Keywords

    ARIMA; Combined forecasts; Double seasonality; Exponential Smoothing; Forecasting; GARCH; Water demand;

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