Abstract
In the last few years we have observed an increasing interest in deregulated electricity markets. Only few papers, to the authors’ knowledge, have considered the Italian Electricity Spot market since it has been deregulated recently. This contribution is an investigation with emphasis on price dynamics accounting for technologies, market concentration, and congestions as well as extreme spiky behavior. We aim to understand how technologies, concentration, and congestions affect the zonal prices since all these combine to bring about the single national price (prezzo unico d’acquisto, PUN). Implementing Reg–ARFIMA–GARCH models, we draw policy indications based on the empirical evidence that technologies, concentration, and congestions do affect Italian electricity prices.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The shares are defined by considering the volumes sold and/or offered (including those covered by Bilateral Contracts) by individual market participants aggregated on the basis of the group to which they belong.
- 2.
The delivery periods for the Italian market refer to the following groups of hours: off peak 1 from 00.00 to 06.00 until the end of 2005 then from 2006 to 07.00; peak is from 07.00 (08.00 from 2006) to 22.00 (to 20.00 from 2006); off peak 2 from 23.00 (or 21.00 from 2006) to 24.00.
- 3.
Similar dynamics are observed on other zones and are not reported for lack of space.
- 4.
Contrary on expectations from Table 39.2, HHI is found to be significant and positive only in CSouth.
- 5.
It is significant (with a negative sign) in some zones but it turns to be insignificant in some others, whereas it should always have a positive sign: when the HHI increases then the price increases as result of exercise of market power. These results are available on request.
- 6.
This could be due to the presence of limited production poles which only inject electricity into the system then providing the necessary supply: Brindisi in the Southern zone and Rossano in Calabria.
References
Battaglia, F., Orfei, L.: Outlier detection and estimation in nonlinear time series. J. Time Series Anal. 26(1), 107–121 (2005)
Bisaglia, L., Gerolimetto, M.: Testing structural breaks vs. long memory with the Box-Pierce statistics: a Monte Carlo study. Stat. Method Appl. 18, 543–553 (2009)
Bosco, B., Parisio, L., Pelagatti, M.: Deregulated wholesale electricity prices in Italy: An empirical analysis. Int. Adv. Econ. Res. 13, 415–432 (2007)
Fridolfsson, S., Tangeras, T.: Market power in the Nordic electricity wholesale market: a survey of the empirical evidence. Energ Pol. 37, 3681–3692 (2009)
Furió, D., Lucia, J.J.: Congestion management rules and trading strategies in the Spanish electricity market. Energ Econ. 31, 48–60 (2009)
Gianfreda, A., Bunn, D.: Integration and shock transmissions across European electricity forward markets. Energ Econ. 32(2), 278–291 (2010)
Gianfreda, A., Grossi, L.: Zonal Price Analysis of the Italian Wholesale Electricity Market. In: IEEE CNF Conference Proceedings of the European Energy Markets Conference (EEM09). Available on IEEE Xplore, 2009
Giulietti, M., Grossi, L., Waterson, M.: Price transmission in the UK electricity market: Was NETA beneficial? Energ Econ. 32, 1165–1174 (2010)
GME: Technical Report 2008, available at http://www.mercatoelettrico.org
Haldrup, N., Nielsen, M.O.: A regime switching long memory model for electricity prices. J. Econometrics 135(1–2), 349–376 (2006)
Karakatsani, N., Bunn, D.W.: Forecasting electricity prices: The impact of fundamentals and time-varying coefficients. Int. J. Forecast. 24(4), 764–785 (2008)
Koopman, S.J., Oooms, M., Carnero, M.A.: Periodic seasonal Reg-ARFIMA-GARCH models for daily electricity spot prices. J. Am. Stat. Assoc. 102(477), 16–27 (2007)
Manuhutu, C., Owen, A.D.: Gas-on-gas competition in Shangai. Energ Pol. 38(5), 2101–2106 (2010)
Olbermann, B.P., Lopes, S.R.C., Reisen, V.A.: Invariance of the first difference in ARFIMA models. Comput. Stat. 21, 445-461 (2006)
Rahimi, A.F., Sheffrin, A.Y.: Effective market monitoring in deregulated electricity markets. IEEE Trans. Power Syst. 18(2), 486–493 (2003)
Weron, R.: Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach. Wiley, New York (2006)
Acknowledgements
We would like to thank the book’s editors and two anonymous referees for their valuable comments on a previous version of the paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Gianfreda, A., Grossi, L. (2013). Fractional Integration Models for Italian Electricity Zonal Prices. In: Torelli, N., Pesarin, F., Bar-Hen, A. (eds) Advances in Theoretical and Applied Statistics. Studies in Theoretical and Applied Statistics(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35588-2_39
Download citation
DOI: https://doi.org/10.1007/978-3-642-35588-2_39
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35587-5
Online ISBN: 978-3-642-35588-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)