IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v135y2006i1-2p349-376.html
   My bibliography  Save this article

A regime switching long memory model for electricity prices

Author

Listed:
  • Haldrup, Niels
  • Nielsen, Morten Orregaard

Abstract

In this paper we develop a regime switching model which can generate long memory (fractional integration) in each of the regime states. This property is relevant in a number of cases. For instance, the deregulated market for electricity power in the Nordic countries is characterized by electricity spot prices with a high degree of long memory. It occurs that in some time periods bilateral prices are identical whereas in other periods the prices differ. The latter occurs when a capacity congestion exists across regions and multiple price areas will result. If the price series are fractionally integrated this means that in some regimes, an extreme form of fractional cointegration amongst prices will exist. We define a Markov switching fractional integration model from which the fractional orders of integration in separate states can be estimated using Maximum Likelihood techniques. The model is adapted to data for the Nordic electricity spot market, and we find that regime swithing and long memory are empirically relevant to co-exist. In particular, we find that the price behaviour for single markets can be very different depending upon the presence or absence of bottlenecks in electricity transmission. Using Monte Carlo forecasting we find that the regime switching model appears to be especially attractive in forecasting relative prices.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Haldrup, Niels & Nielsen, Morten Orregaard, 2006. "A regime switching long memory model for electricity prices," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 349-376.
  • Handle: RePEc:eee:econom:v:135:y:2006:i:1-2:p:349-376
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(05)00171-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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:

    References listed on IDEAS

    as
    1. Hansen, Bruce E. & Seo, Byeongseon, 2002. "Testing for two-regime threshold cointegration in vector error-correction models," Journal of Econometrics, Elsevier, vol. 110(2), pages 293-318, October.
    2. Nielsen, Morten Ørregaard, 2004. "Efficient Likelihood Inference In Nonstationary Univariate Models," Econometric Theory, Cambridge University Press, vol. 20(1), pages 116-146, February.
    3. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute.
    4. Motta,Massimo, 2004. "Competition Policy," Cambridge Books, Cambridge University Press, number 9780521016919, September.
    5. Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
    6. Philip Hans Franses & Marius Ooms & Charles S. Bos, 1999. "Long memory and level shifts: Re-analyzing inflation rates," Empirical Economics, Springer, vol. 24(3), pages 427-449.
    7. Davidson, James, 2004. "Forecasting Markov-switching dynamic, conditionally heteroscedastic processes," Statistics & Probability Letters, Elsevier, vol. 68(2), pages 137-147, June.
    8. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    9. Ramanathan, Ramu & Engle, Robert & Granger, Clive W. J. & Vahid-Araghi, Farshid & Brace, Casey, 1997. "Shorte-run forecasts of electricity loads and peaks," International Journal of Forecasting, Elsevier, vol. 13(2), pages 161-174, June.
    10. Granger, Clive W. J. & Hyung, Namwon, 2004. "Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 399-421, June.
    11. Fabra, Natalia & Toro, Juan, 2005. "Price wars and collusion in the Spanish electricity market," International Journal of Industrial Organization, Elsevier, vol. 23(3-4), pages 155-181, April.
    12. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    13. Haldrup, Niels & Nielsen, Morten Orregaard, 2007. "Estimation of fractional integration in the presence of data noise," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3100-3114, March.
    14. Granger, Clive W. J. & Ding, Zhuanxin, 1996. "Varieties of long memory models," Journal of Econometrics, Elsevier, vol. 73(1), pages 61-77, July.
    15. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
    16. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    17. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    18. Kleindorfer, Paul R & Fernando, Chitru S, 1993. "Peak-Load Pricing and Reliability under Uncertainty," Journal of Regulatory Economics, Springer, vol. 5(1), pages 5-23, March.
    19. Phillips, Peter C. B. & Jin, Sainan, 2002. "The KPSS test with seasonal dummies," Economics Letters, Elsevier, vol. 77(2), pages 239-243, October.
    20. Massimiliano Marcellino & Grayham E. Mizon & Hans-Martin Krolzig, 2002. "A Markov-switching vector equilibrium correction model of the UK labour market," Empirical Economics, Springer, vol. 27(2), pages 233-254.
    21. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    22. Tanaka, Katsuto, 1999. "The Nonstationary Fractional Unit Root," Econometric Theory, Cambridge University Press, vol. 15(4), pages 549-582, August.
    23. 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.
    24. Crew, Michael A & Fernando, Chitru S & Kleindorfer, Paul R, 1995. "The Theory of Peak-Load Pricing: A Survey," Journal of Regulatory Economics, Springer, vol. 8(3), pages 215-248, November.
    25. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    26. Peter O. Steiner, 1957. "Peak Loads and Efficient Pricing," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 71(4), pages 585-610.
    27. Lee, Dongin & Schmidt, Peter, 1996. "On the power of the KPSS test of stationarity against fractionally-integrated alternatives," Journal of Econometrics, Elsevier, vol. 73(1), pages 285-302, July.
    28. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    29. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    30. Clive W.J. Granger & Namwon Hyung, 2013. "Occasional Structural Breaks and Long Memory," Annals of Economics and Finance, Society for AEF, vol. 14(2), pages 739-764, November.
    31. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    32. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    33. Kramer, Walter, 1998. "Fractional integration and the augmented Dickey-Fuller Test," Economics Letters, Elsevier, vol. 61(3), pages 269-272, December.
    34. Sherman,Roger, 1989. "The Regulation of Monopoly," Cambridge Books, Cambridge University Press, number 9780521368629, September.
    35. Michael A. Crew & Paul R. Kleindorfer, 1976. "Peak Load Pricing with a Diverse Technology," Bell Journal of Economics, The RAND Corporation, vol. 7(1), pages 207-231, Spring.
    36. Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haldrup Niels & Nielsen Morten Ø., 2006. "Directional Congestion and Regime Switching in a Long Memory Model for Electricity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-24, September.
    2. Haldrup, Niels & Nielsen, Frank S. & Nielsen, Morten Ørregaard, 2010. "A vector autoregressive model for electricity prices subject to long memory and regime switching," Energy Economics, Elsevier, vol. 32(5), pages 1044-1058, September.
    3. Javier Hualde & Morten {O}rregaard Nielsen, 2022. "Fractional integration and cointegration," Papers 2211.10235, arXiv.org.
    4. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    5. Guglielmo Maria Caporale & Luis Gil‐Alana, 2014. "Long‐Run and Cyclical Dynamics in the US Stock Market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(2), pages 147-161, March.
    6. repec:got:cegedp:76 is not listed on IDEAS
    7. Michael KUEHL, 2008. "Strong Comovements of Exchange Rates: Theoretical and Empirical Cases when Currencies Become the Same Asset," EcoMod2008 23800071, EcoMod.
    8. Pierre Perron & Zhongjun Qu, 2006. "An Analytical Evaluation of the Log-periodogram Estimate in the Presence of Level Shifts and its Implications for Stock Returns Volatility," Boston University - Department of Economics - Working Papers Series WP2006-016, Boston University - Department of Economics.
    9. Gary Biglaiser & Ching-to Albert Ma, 2007. "Moonlighting: public service and private practice," RAND Journal of Economics, RAND Corporation, vol. 38(4), pages 1113-1133, December.
    10. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
    11. Laura Mayoral, 2006. "Further Evidence on the Statistical Properties of Real GNP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 901-920, December.
    12. Lu, Yang K. & Perron, Pierre, 2010. "Modeling and forecasting stock return volatility using a random level shift model," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 138-156, January.
    13. Gadea, Maria Dolores & Sabate, Marcela & Serrano, Jose Maria, 2004. "Structural breaks and their trace in the memory: Inflation rate series in the long-run," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 117-134, April.
    14. Christian Fischer & Luis Alberiko Gil-Alana, 2005. "The Nature of the Relationship between International Tourism and International Trade: The Case of Ge," Faculty Working Papers 15/05, School of Economics and Business Administration, University of Navarra.
    15. Guglielmo Maria Caporale & Luis A. Gil‐Alana & James C. Orlando, 2016. "Linkages Between the US and European Stock Markets: A Fractional Cointegration Approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 143-153, April.
    16. Monge, Manuel & Gil-Alana, Luis A. & Pérez de Gracia, Fernando, 2017. "Crude oil price behaviour before and after military conflicts and geopolitical events," Energy, Elsevier, vol. 120(C), pages 79-91.
    17. Juan Carlos Cuestas & Luis A. Gil-Alana & Laura Sauci, 2020. "Public finances in the EU-27: Are they sustainable?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(1), pages 181-204, February.
    18. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.
    19. Pierre Perron & Zhongjun Qu, 2007. "An Analytical Evaluation of the Log-periodogram Estimate in the Presence of Level Shifts," Boston University - Department of Economics - Working Papers Series wp2007-044, Boston University - Department of Economics.
    20. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2008. "Modelling the US, UK and Japanese unemployment rates: Fractional integration and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 4998-5013, July.
    21. Emma Iglesias & Garry Phillips, 2005. "Analysing one-month Euro-market interest rates by fractionally integrated models," Applied Financial Economics, Taylor & Francis Journals, vol. 15(2), pages 95-106.

    More about this item

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    Statistics

    Access and download statistics

    Corrections

    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:econom:v:135:y:2006:i:1-2:p:349-376. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.