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

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  • 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.

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Bibliographic Info

Paper provided by Rice University, Department of Economics in its series Working Papers with number 2003-08.

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Date of creation: Jul 2003
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Handle: RePEc:ecl:riceco:2003-08

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  1. Halvorsen, Bente & Larsen, Bodil M., 2001. "The flexibility of household electricity demand over time," Resource and Energy Economics, Elsevier, vol. 23(1), pages 1-18, January.
  2. Park, Joon Y, 1992. "Canonical Cointegrating Regressions," Econometrica, Econometric Society, vol. 60(1), pages 119-43, January.
  3. Haas, Reinhard & Schipper, Lee, 1998. "Residential energy demand in OECD-countries and the role of irreversible efficiency improvements," Energy Economics, Elsevier, vol. 20(4), pages 421-442, September.
  4. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-58, May.
  5. Bentzen, Jan & Engsted, Tom, 1993. "Short- and long-run elasticities in energy demand : A cointegration approach," Energy Economics, Elsevier, vol. 15(1), pages 9-16, January.
  6. Beenstock, Michael & Goldin, Ephraim & Nabot, Dan, 1999. "The demand for electricity in Israel," Energy Economics, Elsevier, vol. 21(2), pages 168-183, April.
  7. Park, Joon Y. & Hahn, Sang B., 1999. "Cointegrating Regressions With Time Varying Coefficients," Econometric Theory, Cambridge University Press, vol. 15(05), pages 664-703, October.
  8. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
  9. Engle, R. F. & Granger, C. W. J. & Hallman, J. J., 1989. "Merging short-and long-run forecasts : An application of seasonal cointegration to monthly electricity sales forecasting," Journal of Econometrics, Elsevier, vol. 40(1), pages 45-62, January.
  10. Silk, Julian I. & Joutz, Frederick L., 1997. "Short and long-run elasticities in US residential electricity demand: a co-integration approach," Energy Economics, Elsevier, vol. 19(4), pages 493-513, October.
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Cited by:
  1. 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.
  2. 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.
  3. 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.
  4. Atakhanova, Zauresh & Howie, Peter, 2007. "Electricity demand in Kazakhstan," Energy Policy, Elsevier, vol. 35(7), pages 3729-3743, July.
  5. 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.
  6. 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.

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