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Electricity rationing and public response

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  • Rocha Souza, Leonardo
  • Jorge Soares, Lacir

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  • Rocha Souza, Leonardo & Jorge Soares, Lacir, 2007. "Electricity rationing and public response," Energy Economics, Elsevier, vol. 29(2), pages 296-311, March.
    • Handle: RePEc:eee:eneeco:v:29:y:2007:i:2:p:296-311
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    References listed on IDEAS

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    1. Soares, Lacir Jorge & Souza, Leonardo Rocha, 2006. "Forecasting electricity demand using generalized long memory," International Journal of Forecasting, Elsevier, vol. 22(1), pages 17-28.
    2. Arteche, Josu & Robinson, Peter M., 1998. "Seasonal and cyclical long memory," LSE Research Online Documents on Economics 2241, London School of Economics and Political Science, LSE Library.
    3. Ferrara, Laurent & Guegan, Dominique, 2001. "Forecasting with k-Factor Gegenbauer Processes: Theory and Applications," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(8), pages 581-601, December.
    4. Ramanathan, Ramu & Engle, Robert & Granger, Clive W. J. & Vahid-Araghi, Farshid & Brace, Casey, 1997. "Shorte-run forecasts of electricity loads and peaks," International Journal of Forecasting, Elsevier, vol. 13(2), pages 161-174, June.
    5. Laurent Ferrara & Dominique Guegan, 2000. "Forecasting financial time series with generalized long memory processes," Post-Print halshs-00199126, HAL.
    6. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    7. Henry L. Gray & Nien‐Fan Zhang & Wayne A. Woodward, 1989. "On Generalized Fractional Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 10(3), pages 233-257, May.
    8. Chung, Ching-Fan, 1996. "Estimating a generalized long memory process," Journal of Econometrics, Elsevier, vol. 73(1), pages 237-259, July.
    9. 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.
    10. Josu Arteche, 2002. "Semiparametric robust tests on seasonal or cyclical long memory time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(3), pages 251-285, May.
    11. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    12. 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.
    13. Ray, Bonnie K., 1993. "Long-range forecasting of IBM product revenues using a seasonal fractionally differenced ARMA model," International Journal of Forecasting, Elsevier, vol. 9(2), pages 255-269, August.
    14. Moral-Carcedo, Julian & Vicens-Otero, Jose, 2005. "Modelling the non-linear response of Spanish electricity demand to temperature variations," Energy Economics, Elsevier, vol. 27(3), pages 477-494, May.
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    Cited by:

    1. Xu, Shuling & Yang, Zihan & Deng, Nana & Wang, Bo, 2024. "Residents' willingness to be compensated for power rationing during peak hours based on choice experiment," Applied Energy, Elsevier, vol. 367(C).
    2. Arthur Charpentier, 2011. "On the return period of the 2003 heat wave," Climatic Change, Springer, vol. 109(3), pages 245-260, December.
    3. Hunt., Julian David & Stilpen, Daniel & de Freitas, Marcos Aurélio Vasconcelos, 2018. "A review of the causes, impacts and solutions for electricity supply crises in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 208-222.
    4. Oskar Lindgren & Erik Elwing & Mikael Karlsson & Sverker C. Jagers, 2024. "Public acceptability of climate-motivated rationing," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-9, December.

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