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Price convergence and information efficiency in German natural gas markets

Author

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  • Growitsch, Christian

    () (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Stronzik, Marcus

    () (Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH)

  • Nepal, Rabindra

    () (Heriot-Watt University, Department of Economics)

Abstract

In 2007, Germany changed network access regulation in the natural gas sector and introduced a so-called entry-exit system. The re-regulation’s spot market effects remain to be examined. We use cointegration analysis and a state space model with time-varying coefficients to study the development of natural gas spot prices in the two major trading hubs in Germany and the interlinked Dutch spot market. To analyse information efficiency in more detail, the state space model is extended to an error correction model. Overall, our results suggest a reasonable degree of price convergence between the corresponding hubs. However, allowing for time-variant adjustment processes, the remaining price differentials are only partly explained by transportation costs, indicating capacity constraints. Nonetheless, market efficiency in terms of information processing has increased considerably among Germany and The Netherlands.

Suggested Citation

  • Growitsch, Christian & Stronzik, Marcus & Nepal, Rabindra, 2012. "Price convergence and information efficiency in German natural gas markets," EWI Working Papers 2012-5, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
  • Handle: RePEc:ris:ewikln:2012_005
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Kuper, Gerard & Mulder, Machiel, 2013. "Cross-border infrastructure constraints, regulatory measures and economic integration of the Dutch - German gas market," Research Report 13001-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    2. Kuper, Gerard H. & Mulder, Machiel, 2016. "Cross-border constraints, institutional changes and integration of the Dutch–German gas market," Energy Economics, Elsevier, vol. 53(C), pages 182-192.
    3. Nick, Sebastian, 2013. "Price Formation and Intertemporal Arbitrage within a Low-Liquidity Framework: Empirical Evidence from European Natural Gas Markets," EWI Working Papers 2013-14, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    4. Nick, Sebastian & Thoenes, Stefan, 2014. "What drives natural gas prices? — A structural VAR approach," Energy Economics, Elsevier, vol. 45(C), pages 517-527.
    5. Hulshof, Daan & van der Maat, Jan-Pieter & Mulder, Machiel, 2016. "Market fundamentals, competition and natural-gas prices," Energy Policy, Elsevier, vol. 94(C), pages 480-491.
    6. Klaus Gugler & Adhurim Haxhimusa & Mario Liebensteiner, 2016. "Integration and Efficiency of European Electricity Markets: Evidence from Spot Prices," Department of Economics Working Papers wuwp226, Vienna University of Economics and Business, Department of Economics.
    7. Sebastian Nick, 2016. "The Informational Efficiency of European Natural Gas Hubs: Price Formation and Intertemporal Arbitrage," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    8. repec:dgr:rugsom:13001-eef is not listed on IDEAS
    9. Zachmann, Georg, 2013. "A stochastic fuel switching model for electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 5-13.
    10. Rabindra Nepal and John Foster, 2016. "Testing for Market Integration in the Australian National Electricity Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    11. Nepal, Rabindra & Jamasb, Tooraj, 2012. "Interconnections and market integration in the Irish Single Electricity Market," Energy Policy, Elsevier, vol. 51(C), pages 425-434.
    12. repec:ipg:wpaper:2014-502 is not listed on IDEAS
    13. repec:dgr:rugsom:13004-eef is not listed on IDEAS

    More about this item

    Keywords

    natural gas market; regulation; cointegration; price convergence; time-varying coefficient;

    JEL classification:

    • 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
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • L95 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Gas Utilities; Pipelines; Water Utilities

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