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Structural Analysis of High Frequency Electricity Demand and Supply Interactions


Carlo Fezzi


University of East Anglia (UEA) - School of Environmental Sciences

Derek W. Bunn


London Business School

October 1, 2006


Abstract:     
A dynamic, structural asymmetric vector-error correction model is used to identify and estimate the demand and the supply functions for hourly, day-ahead electricity wholesale markets. The analysis provides new insights on a well-established but unresolved aspect concerning the extent of demand elasticity to price. We argue that the conventional meanreverting,stationarity assumption for electricity prices raises subtle issues of specification and must be carefully evaluated. We present evidence for adopting a non-stationary specification in the short-window, high-frequency context, and thereby estimate a cointegrating system. This allows us to distinguish between long run and short run effects, and to estimate an error-correction term embedded in a simultaneous equation model. We show that, whilst demand appears to be inelastic in the short run, the quantity traded on the market reacts significantly to previous disequilibria in the supply curve through an asymmetric error-correction mechanism, and does in fact adjust to positive changes in the price level, but not to negative ones.

Number of Pages in PDF File: 35

Keywords: Electricity Markets, Demand Elasticity, Simultaneous Equations, Asymmetric Vector Error-Correction

JEL Classification: C32, Q41, L94

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Date posted: August 21, 2008  

Suggested Citation

Fezzi, Carlo and Bunn, Derek W., Structural Analysis of High Frequency Electricity Demand and Supply Interactions (October 1, 2006). Available at SSRN: http://ssrn.com/abstract=1241703 or http://dx.doi.org/10.2139/ssrn.1241703

Contact Information

Carlo Fezzi (Contact Author)
University of East Anglia (UEA) - School of Environmental Sciences ( email )
Norwich, Norfolk
United Kingdom
Derek W. Bunn
London Business School ( email )
Sussex Place
Regent's Park
London NW1 4SA
United Kingdom
0207 000 8000 (Phone)
Feedback to SSRN (Beta)


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