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Cross-border and cross-regional electricity transmission: Is there a price impact in south Norway?

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  • Bendiksen, Vidar
  • Løining, Lars Olai Fjellestad
  • Lyócsa, Štefan

Abstract

The potential impact of cross-border electricity exchange on domestic prices is a topic of active public debate in many countries. In this study, we quantify the extent to which electricity flows have contributed to hourly spot prices in Southern Norway (bidding region NO2). Using data from 2015 to 2024 and a system of non-crossing quantile regressions, we find that while electricity transmission flows have a limited effect on expected and median prices, they do help explain variation in the tails of the future price distribution. Specifically, regional electricity transmission and transmission with Netherlands and Denmark is only weakly associated with future prices. By contrast, electricity flows with Great Britain and Germany/Luxembourg have the potential to increase price volatility in Norway. While these effects can be economically significant, in-sample, they do not translate into improved out-of-sample forecasts of the price distribution. We discuss the policy implications of these findings and conclude that, on average, cross-border electricity flows do not themselves lead to increases in market prices. However, decoupling wholesale and retail prices for households through government subsidies and the introduction of fixed-rate schemes effectively addresses increased price volatility. Regarding the debate over restricting electricity flows, our results suggest that such policies should be trading partner-specific and should take into account the varying conditions under which cross-border electricity flows occur.

Suggested Citation

  • Bendiksen, Vidar & Løining, Lars Olai Fjellestad & Lyócsa, Štefan, 2025. "Cross-border and cross-regional electricity transmission: Is there a price impact in south Norway?," Energy Economics, Elsevier, vol. 150(C).
    • Handle: RePEc:eee:eneeco:v:150:y:2025:i:c:s0140988325007054
    DOI: 10.1016/j.eneco.2025.108878
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    References listed on IDEAS

    as
    1. Linh Phuong Catherine Do & Štefan Lyócsa & Peter Molnár, 2019. "Impact of wind and solar production on electricity prices: Quantile regression approach," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1752-1768, October.
    2. Thellufsen, Jakob Zinck & Lund, Henrik, 2017. "Cross-border versus cross-sector interconnectivity in renewable energy systems," Energy, Elsevier, vol. 124(C), pages 492-501.
    3. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    4. Sunila, Kanerva & Bergaentzlé, Claire & Martin, Bénédicte & Ekroos, Ari, 2019. "A supra-national TSO to enhance offshore wind power development in the Baltic Sea? A legal and regulatory analysis," Energy Policy, Elsevier, vol. 128(C), pages 775-782.
    5. Antweiler, Werner, 2016. "Cross-border trade in electricity," Journal of International Economics, Elsevier, vol. 101(C), pages 42-51.
    6. repec:aen:journl:ej39-3-roques is not listed on IDEAS
    7. Severin Borenstein & James B. Bushnell, 2022. "Do Two Electricity Pricing Wrongs Make a Right? Cost Recovery, Externalities, and Efficiency," American Economic Journal: Economic Policy, American Economic Association, vol. 14(4), pages 80-110, November.
    8. Michael McAleer & Bernardo da Veiga, 2008. "Single-index and portfolio models for forecasting value-at-risk thresholds," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 217-235.
    9. Howard D. Bondell & Brian J. Reich & Huixia Wang, 2010. "Noncrossing quantile regression curve estimation," Biometrika, Biometrika Trust, vol. 97(4), pages 825-838.
    10. Do, Linh Phuong Catherine & Lyócsa, Štefan & Molnár, Peter, 2021. "Residual electricity demand: An empirical investigation," Applied Energy, Elsevier, vol. 283(C).
    11. Torstein Bye & Einar Hope, 2005. "Deregulation of electricity markets : The Norwegian experience," Discussion Papers 433, Statistics Norway, Research Department.
    12. Brownlees, Christian & Souza, André B.M., 2021. "Backtesting global Growth-at-Risk," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 312-330.
    13. Unger, Elizabeth A. & Ulfarsson, Gudmundur F. & Gardarsson, Sigurdur M. & Matthiasson, Thorolfur, 2018. "The effect of wind energy production on cross-border electricity pricing: The case of western Denmark in the Nord Pool market," Economic Analysis and Policy, Elsevier, vol. 58(C), pages 121-130.
    14. Peter R. Hansen & Asger Lunde & James M. Nason, 2011. "The Model Confidence Set," Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
    15. Siddiqui, Sauleh & Vaillancourt, Kathleen & Bahn, Olivier & Victor, Nadejda & Nichols, Christopher & Avraam, Charalampos & Brown, Maxwell, 2020. "Integrated North American energy markets under different futures of cross-border energy infrastructure," Energy Policy, Elsevier, vol. 144(C).
    16. Lehna, Malte & Scheller, Fabian & Herwartz, Helmut, 2022. "Forecasting day-ahead electricity prices: A comparison of time series and neural network models taking external regressors into account," Energy Economics, Elsevier, vol. 106(C).
    17. Efimova, Olga & Serletis, Apostolos, 2014. "Energy markets volatility modelling using GARCH," Energy Economics, Elsevier, vol. 43(C), pages 264-273.
    18. Fabio Busetti, 2017. "Quantile Aggregation of Density Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 495-512, August.
    19. Haugom, Erik & Lyócsa, Štefan & Halousková, Martina, 2024. "The tipping point of electricity price attention: When a problem becomes a problem," Economics Letters, Elsevier, vol. 235(C).
    20. Li, Wei & Becker, Denis Mike, 2021. "Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling," Energy, Elsevier, vol. 237(C).
    21. repec:aen:journl:ej40-3-furio is not listed on IDEAS
    22. Ganepola, Chanaka N. & Shubita, Moade & Lee, Lillian, 2023. "The electric shock: Causes and consequences of electricity prices in the United Kingdom," Energy Economics, Elsevier, vol. 126(C).
    23. Uribe, Jorge M. & Guillen, Montserrat & Mosquera-López, Stephania, 2018. "Uncovering the nonlinear predictive causality between natural gas and electricity prices," Energy Economics, Elsevier, vol. 74(C), pages 904-916.
    24. Beyza, Jesus & Gil, Pablo & Masera, Marcelo & Yusta, Jose M., 2020. "Security assessment of cross-border electricity interconnections," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    25. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    26. Pardo, Angel & Meneu, Vicente & Valor, Enric, 2002. "Temperature and seasonality influences on Spanish electricity load," Energy Economics, Elsevier, vol. 24(1), pages 55-70, January.
    27. Cepeda, Mauricio, 2018. "Assessing cross-border integration of capacity mechanisms in coupled electricity markets," Energy Policy, Elsevier, vol. 119(C), pages 28-40.
    28. Schaber, Katrin & Steinke, Florian & Hamacher, Thomas, 2012. "Transmission grid extensions for the integration of variable renewable energies in Europe: Who benefits where?," Energy Policy, Elsevier, vol. 43(C), pages 123-135.
    29. de Menezes, Lilian M. & Houllier, Melanie A., 2015. "Germany's nuclear power plant closures and the integration of electricity markets in Europe," Energy Policy, Elsevier, vol. 85(C), pages 357-368.
    30. Silvester, Benjamin Ronald, 2025. "Hesitation at increasing integration: The feasibility of Norway expanding cross-border renewable electricity interconnection to support European decarbonisation," Technological Forecasting and Social Change, Elsevier, vol. 213(C).
    31. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Non-crossing convex quantile regression," Economics Letters, Elsevier, vol. 233(C).
    32. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    33. Mosquera-López, Stephania & Uribe, Jorge M. & Joaqui-Barandica, Orlando, 2024. "Weather conditions, climate change, and the price of electricity," Energy Economics, Elsevier, vol. 137(C).
    34. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
    35. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    36. Timilsina,Govinda R. & Deluque Curiel,Ilka Fabiana & Chattopadhyay,Debabrata, 2021. "How Much Does Latin America Gain from Enhanced Cross-Border Electricity Trade in the Short Run ?," Policy Research Working Paper Series 9692, The World Bank.
    37. Jahns, Christopher & Podewski, Caroline & Weber, Christoph, 2020. "Supply curves for hydro reservoirs – Estimation and usage in large-scale electricity market models," Energy Economics, Elsevier, vol. 87(C).
    38. Tschora, Léonard & Pierre, Erwan & Plantevit, Marc & Robardet, Céline, 2022. "Electricity price forecasting on the day-ahead market using machine learning," Applied Energy, Elsevier, vol. 313(C).
    39. Denny, E. & Tuohy, A. & Meibom, P. & Keane, A. & Flynn, D. & Mullane, A. & O'Malley, M., 2010. "The impact of increased interconnection on electricity systems with large penetrations of wind generation: A case study of Ireland and Great Britain," Energy Policy, Elsevier, vol. 38(11), pages 6946-6954, November.
    40. Keles, Dogan & Dehler-Holland, Joris & Densing, Martin & Panos, Evangelos & Hack, Felix, 2020. "Cross-border effects in interconnected electricity markets - an analysis of the Swiss electricity prices," Energy Economics, Elsevier, vol. 90(C).
    41. Uribe, Jorge M. & Mosquera-López, Stephanía & Guillen, Montserrat, 2020. "Characterizing electricity market integration in Nord Pool," Energy, Elsevier, vol. 208(C).
    42. Bublitz, Andreas & Keles, Dogan & Fichtner, Wolf, 2017. "An analysis of the decline of electricity spot prices in Europe: Who is to blame?," Energy Policy, Elsevier, vol. 107(C), pages 323-336.
    43. Biancardi, Andrea & Mendes, Carla & Staffell, Iain, 2024. "Battery electricity storage as both a complement and substitute for cross-border interconnection," Energy Policy, Elsevier, vol. 189(C).
    44. Léonard Tschora & Erwan Pierre & Marc Plantevit & Céline Robardet, 2022. "Electricity price forecasting on the day-ahead market using machine learning," Post-Print hal-03621974, HAL.
    45. Helena Chuliá & Dolores Furió & Jorge M. Uribe, 2019. "Volatility Spillovers in Energy Markets," The Energy Journal, , vol. 40(3), pages 173-198, May.
    46. Dutton, Joseph & Lockwood, Matthew, 2017. "Ideas, institutions and interests in the politics of cross-border electricity interconnection: Greenlink, Britain and Ireland," Energy Policy, Elsevier, vol. 105(C), pages 375-385.
    47. Sebastien Annan-Phan & Fabien A. Roques, 2018. "Market Integration and Wind Generation: An Empirical Analysis of the Impact of Wind Generation on Cross-border Power Prices," The Energy Journal, , vol. 39(3), pages 1-24, May.
    48. Grohnheit, Poul Erik & Sneum, Daniel Møller, 2023. "Calm before the storm: Market prices in a power market with an increasing share of wind power," Energy Policy, Elsevier, vol. 179(C).
    49. Wei Li & Denis Mike Becker, 2021. "Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling," Papers 2101.05249, arXiv.org, revised Jul 2021.
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    JEL classification:

    • L90 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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