A new approach to modeling the effects of temperature fluctuations on monthly electricity demand
Download full text from publisher
As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.
Other versions of this item:
- Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2015. "A New Approach to Modeling the Effects of Temperature Fluctuations on Monthly Electricity Demand," Working Papers 2015-12, Department of Economics, University of Missouri.
References listed on IDEAS
- Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003.
"Underlying trends and seasonality in UK energy demand: a sectoral analysis,"
Elsevier, vol. 25(1), pages 93-118, January.
- Hunt, L.C. & Judge, G. & Ninomiya, Y., 2000. "Underlying Trends and Seasonality in UK Energy Demands: A Sectorial Analysis," Papers 134, Portsmouth University - Department of Economics.
- Jones, Clifton T, 1994. "Accounting for technical progress in aggregate energy demand," Energy Economics, Elsevier, vol. 16(4), pages 245-252, October.
- Fan, Shu & Hyndman, Rob J., 2011.
"The price elasticity of electricity demand in South Australia,"
Elsevier, vol. 39(6), pages 3709-3719, June.
- Shu Fan & Rob Hyndman, 2010. "The price elasticity of electricity demand in South Australia," Monash Econometrics and Business Statistics Working Papers 16/10, Monash University, Department of Econometrics and Business Statistics.
- Pardo, Angel & Meneu, Vicente & Valor, Enric, 2002. "Temperature and seasonality influences on Spanish electricity load," Energy Economics, Elsevier, vol. 24(1), pages 55-70, January.
- Henley, Andrew & Peirson, John, 1998. "Residential energy demand and the interaction of price and temperature: British experimental evidence," Energy Economics, Elsevier, vol. 20(2), pages 157-171, April.
- 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.
- 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.
- 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.
- Halicioglu, Ferda, 2007. "Residential electricity demand dynamics in Turkey," Energy Economics, Elsevier, vol. 29(2), pages 199-210, March.
- Serletis, Apostolos & Shahmoradi, Asghar, 2008. "Semi-nonparametric estimates of interfuel substitution in U.S. energy demand," Energy Economics, Elsevier, vol. 30(5), pages 2123-2133, September.
- Cheolbeom Park, 2011.
"How does changing age distribution impact stock prices? a nonparametric approach,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 26(5), pages 886-887, August.
- Cheolbeom Park, 2010. "How does changing age distribution impact stock prices? A nonparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(7), pages 1155-1178, November/.
- Train, Kenneth & Ignelzi, Patrice & Engle, Robert & Granger, Clive & Ramanathan, Ramu, 1984. "The billing cycle and weather variables in models of electricity sales," Energy, Elsevier, vol. 9(11), pages 1041-1047.
- Beenstock, Michael & Goldin, Ephraim & Nabot, Dan, 1999. "The demand for electricity in Israel," Energy Economics, Elsevier, vol. 21(2), pages 168-183, April.
- Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
- Sailor, David J. & Muñoz, J.Ricardo, 1997. "Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—Methodology and results for eight states," Energy, Elsevier, vol. 22(10), pages 987-998.
- Filippini, Massimo, 1995. "Swiss residential demand for electricity by time-of-use," Resource and Energy Economics, Elsevier, vol. 17(3), pages 281-290, November.
- 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.
- Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand with an Application to Korea," Energy Economics, Elsevier, vol. 46(C), pages 334-347.
- Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355.
- Park, Sung Y. & Zhao, Guochang, 2010. "An estimation of U.S. gasoline demand: A smooth time-varying cointegration approach," Energy Economics, Elsevier, vol. 32(1), pages 110-120, January.
- Watts, Geof & Quiggin, John C., 1984. "A Note on the Use of a Logarithmic Time Trend," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 0(Number 02), pages 1-9, August.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- repec:eee:enepol:v:118:y:2018:i:c:p:257-269 is not listed on IDEAS
- repec:eee:energy:v:127:y:2017:i:c:p:534-543 is not listed on IDEAS
- repec:eee:appene:v:209:y:2018:i:c:p:167-179 is not listed on IDEAS
More about this item
KeywordsElectricity demand; Temperature effect; Temperature response function; Cross temperature response function; Electricity demand in Korea;
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
StatisticsAccess and download statistics
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:eneeco:v:60:y:2016:i:c:p:206-216. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/eneco .
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 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.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.