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Why do electricity prices jump? Empirical evidence from the Nordic electricity market

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  • Hellström, Jörgen
  • Lundgren, Jens
  • Yu, Haishan

Abstract

The paper empirically explores the possible causes behind electricity price jumps in the Nordic electricity market, Nord Pool. A time-series model (a mixed GARCH–EARJI jump model) capturing the common statistical features of electricity prices is used to identify price jumps. By the model, a categorical variable is defined distinguishing no, positive and negative jumps. The causes for the jumps are then explored through the use of ordered probit models in a second stage. The empirical results indicate that the structure of the market plays an important role in whether shocks in the demand and supply for electricity translate into price jumps.

Suggested Citation

  • Hellström, Jörgen & Lundgren, Jens & Yu, Haishan, 2012. "Why do electricity prices jump? Empirical evidence from the Nordic electricity market," Energy Economics, Elsevier, vol. 34(6), pages 1774-1781.
  • Handle: RePEc:eee:eneeco:v:34:y:2012:i:6:p:1774-1781
    DOI: 10.1016/j.eneco.2012.07.006
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Escribano, Álvaro & Sucarrat, Genaro, 2016. "Equation-by-Equation Estimation of Multivariate Periodic Electricity Price Volatility," UC3M Working papers. Economics 23436, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Erdogdu, Erkan, 2016. "Asymmetric volatility in European day-ahead power markets: A comparative microeconomic analysis," Energy Economics, Elsevier, vol. 56(C), pages 398-409.
    3. Liu, Yuna, 2016. "Essays on Stock Market Integration - On Stock Market Efficiency, Price Jumps and Stock Market Correlations," Umeå Economic Studies 926, Umeå University, Department of Economics.
    4. Mattias Vesterberg and Chandra Kiran B. Krishnamurthy, 2016. "Residential End-use Electricity Demand: Implications for Real Time Pricing in Sweden," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    5. Tommaso Proietti & Niels Haldrup & Oskar Knapik, 1411. "Spikes and memory in (Nord Pool) electricity price spot prices," CREATES Research Papers 2017-39, Department of Economics and Business Economics, Aarhus University.
    6. Liu, Yuna, 2016. "Stock exchange integration and price jump risks - The case of the OMX Nordic exchange mergers," Umeå Economic Studies 925, Umeå University, Department of Economics.
    7. Ballester, Cristina & Furió, Dolores, 2015. "Effects of renewables on the stylized facts of electricity prices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1596-1609.
    8. Bigerna, Simona & Bollino, Carlo Andrea & Ciferri, Davide & Polinori, Paolo, 2017. "Renewables diffusion and contagion effect in Italian regional electricity markets: Assessment and policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 199-211.
    9. repec:eee:rensus:v:74:y:2017:i:c:p:1379-1393 is not listed on IDEAS
    10. Lisi, Francesco & Nan, Fany, 2014. "Component estimation for electricity prices: Procedures and comparisons," Energy Economics, Elsevier, vol. 44(C), pages 143-159.
    11. HFrance Krizanic & Zan Jan Oplotnik, 2013. "Market Changes, Business Cycles and Fluctuations in Electricity Prices - EU Evidence from Germany and Slovenia," International Journal of Energy Economics and Policy, Econjournals, vol. 3(2), pages 118-126.
    12. Zafirakis, Dimitrios & Chalvatzis, Konstantinos J. & Baiocchi, Giovanni & Daskalakis, Georgios, 2016. "The value of arbitrage for energy storage: Evidence from European electricity markets," Applied Energy, Elsevier, vol. 184(C), pages 971-986.
    13. France Krizanic & Zan Jan Oplotnik, 2014. "Analysis of the Energy Market Operator Activity in Eight European Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 4(4), pages 716-725.
    14. Sapio, Alessandro & Spagnolo, Nicola, 2016. "Price regimes in an energy island: Tacit collusion vs. cost and network explanations," Energy Economics, Elsevier, vol. 55(C), pages 157-172.

    More about this item

    Keywords

    Electricity price; Price jumps;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L69 - Industrial Organization - - Industry Studies: Manufacturing - - - Other
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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