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Electricity Demand Analysis Using Cointegration and Error-Correction Models with Time Varying Parameters: The Mexican Case

Author

Listed:
  • Chang, Yoosoon

    (Rice U)

  • Martinez-Chombo, Eduardo

    (Banco de Mexico)

Abstract

We specify and estimate a double-log functional form of the demand equation, using monthly Mexican electricity data for residential, commercial and industrial sectors. Income, prices and a nonparametric temperature measure are used as explanatory variables, and the income elasticity is allowed to evolve slowly over time by employing the time varying coefficient (TVC) cointegrating model. The specification of the proposed TVC cointegrating model is justified by testing it against the spurious regression and the usual fixed coefficient (FC) cointegration regression. The estimated coefficients suggest that the income elasticity has followed a predominantly increasing path for all sectors during the entire sample period, and that electricity prices do not significantly affect in the long-run the residential and commercial demand for electricity in Mexico.

Suggested Citation

  • Chang, Yoosoon & Martinez-Chombo, Eduardo, 2003. "Electricity Demand Analysis Using Cointegration and Error-Correction Models with Time Varying Parameters: The Mexican Case," Working Papers 2003-08, Rice University, Department of Economics.
  • Handle: RePEc:ecl:riceco:2003-08
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    File URL: http://www.ruf.rice.edu/~econ/papers/2003papers/08Chang.pdf
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Cai, Zongwu, 2007. "Trending time-varying coefficient time series models with serially correlated errors," Journal of Econometrics, Elsevier, vol. 136(1), pages 163-188, January.
    2. Cai, Zongwu & Li, Qi & Park, Joon Y., 2009. "Functional-coefficient models for nonstationary time series data," Journal of Econometrics, Elsevier, vol. 148(2), pages 101-113, February.
    3. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2016. "A new approach to modeling the effects of temperature fluctuations on monthly electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 206-216.
    4. David C Broadstock & Lester C Hunt, 2013. "Tying up loose ends: A note on the impact of omitting MA residuals from panel energy demand models based on the Koyck lag transformation," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 140, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    5. repec:eee:enepol:v:113:y:2018:i:c:p:663-672 is not listed on IDEAS
    6. Dagoumas, A.S. & Panapakidis, I.P. & Papagiannis, G.K. & Dokopoulos, P.S., 2008. "Post-Kyoto energy consumption strategies for the Greek interconnected electric system," Energy Policy, Elsevier, vol. 36(6), pages 1980-1999, June.
    7. repec:kap:empiri:v:45:y:2018:i:1:d:10.1007_s10663-016-9355-1 is not listed on IDEAS
    8. repec:gam:jeners:v:10:y:2017:i:11:p:1918-:d:119727 is not listed on IDEAS
    9. repec:pje:journl:article11ii is not listed on IDEAS
    10. Atakhanova, Zauresh & Howie, Peter, 2007. "Electricity demand in Kazakhstan," Energy Policy, Elsevier, vol. 35(7), pages 3729-3743, July.
    11. Eshita Gupta, 2016. "The Effect Of Development On The Climate Sensitivity Of Electricity Demand In India," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 1-49, May.
    12. Zuo, Haomiao & Park, Sung Y., 2011. "Money demand in China and time-varying cointegration," China Economic Review, Elsevier, vol. 22(3), pages 330-343, September.
    13. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    14. Jeyhun I. Mikayilov & Fakhri J. Hasanov & Marzio Galeotti, 2018. "Decoupling of C02 Emissions and GDP: A Time-Varying Cointegration Approach," IEFE Working Papers 101, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.

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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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