IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v148y2020icp205-213.html
   My bibliography  Save this article

A spatio-temporal Durbin fixed effects IV-Model for ENTSO-E electricity flows analysis

Author

Listed:
  • Croonenbroeck, Carsten
  • Palm, Marcel

Abstract

For this article we combine publicly available data from several sources and establish a spatio-temporal panel data model that captures cross-border electricity flows for 29 European countries. As national electricity generation and load landscapes are quite heterogeneous, our results contradict some former results based on single-nation analyses. However, all resemblances and differences to other studies in this field are comprehensible: In general, countries tend to (net) export greater amounts of electricity if domestic wind power generation increases and smaller ones if domestic load increases. Net exports seem to be negatively dependent on photovoltaic infeed, while several controls like industrial electricity price, country size, and other renewables are statistically insignificant in several specifications and if significant, have rather small amounts of influence.

Suggested Citation

  • Croonenbroeck, Carsten & Palm, Marcel, 2020. "A spatio-temporal Durbin fixed effects IV-Model for ENTSO-E electricity flows analysis," Renewable Energy, Elsevier, vol. 148(C), pages 205-213.
  • Handle: RePEc:eee:renene:v:148:y:2020:i:c:p:205-213
    DOI: 10.1016/j.renene.2019.11.133
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148119318270
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2019.11.133?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Neuhoff, Karsten & Diekmann, Jochen & Kunz, Friedrich & Rüster, Sophia & Schill, Wolf-Peter & Schwenen, Sebastian, 2016. "A coordinated strategic reserve to safeguard the European energy transition," Utilities Policy, Elsevier, vol. 41(C), pages 252-263.
    2. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    3. Kemfert, Claudia & Kunz, Friedrich & Rosellón, Juan, 2016. "A welfare analysis of electricity transmission planning in Germany," Energy Policy, Elsevier, vol. 94(C), pages 446-452.
    4. Kunz, Friedrich, 2018. "Quo Vadis? (Un)scheduled electricity flows under market splitting and network extension in central Europe," Energy Policy, Elsevier, vol. 116(C), pages 198-209.
    5. Hirth, Lion & Mühlenpfordt, Jonathan & Bulkeley, Marisa, 2018. "The ENTSO-E Transparency Platform – A review of Europe’s most ambitious electricity data platform," Applied Energy, Elsevier, vol. 225(C), pages 1054-1067.
    6. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    7. J. Paul Elhorst, 2014. "Spatial Panel Data Models," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 37-93, Springer.
    8. Beran, Philip & Pape, Christian & Weber, Christoph, 2019. "Modelling German electricity wholesale spot prices with a parsimonious fundamental model – Validation & application," Utilities Policy, Elsevier, vol. 58(C), pages 27-39.
    9. Janda, Karel & Málek, Jan & Rečka, Lukáš, 2017. "Influence of renewable energy sources on transmission networks in Central Europe," Energy Policy, Elsevier, vol. 108(C), pages 524-537.
    10. M. Hashem Pesaran & Badi H. Baltagi, 2007. "Heterogeneity and cross section dependence in panel data models: theory and applications introduction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 229-232.
    11. Karel Janda & Jan Malek & Lukas Recka, 2017. "Influence of Renewable Energy Sources on Electricity Transmission Networks in Central Europe," Working Papers IES 2017/05, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2017.
    12. Agostini, Claudio A. & Guzmán, Andrés M. & Nasirov, Shahriyar & Silva, Carlos, 2019. "A surplus based framework for cross-border electricity trade in South America," Energy Policy, Elsevier, vol. 128(C), pages 673-684.
    13. Gianfranco Piras, 2013. "Efficient GMM Estimation of a Cliff and Ord Panel Data Model with Random Effects," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(3), pages 370-388, September.
    14. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    15. Zafirakis, Dimitrios & Chalvatzis, Konstantinos J. & Baiocchi, Giovanni, 2015. "Embodied CO2 emissions and cross-border electricity trade in Europe: Rebalancing burden sharing with energy storage," Applied Energy, Elsevier, vol. 143(C), pages 283-300.
    16. Irani Arraiz & David M. Drukker & Harry H. Kelejian & Ingmar R. Prucha, 2010. "A Spatial Cliff‐Ord‐Type Model With Heteroskedastic Innovations: Small And Large Sample Results," Journal of Regional Science, Wiley Blackwell, vol. 50(2), pages 592-614, May.
    17. Lion Hirth, 2018. "What caused the drop in European electricity prices? A factor decomposition analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    18. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    19. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    20. Pape, Christian & Hagemann, Simon & Weber, Christoph, 2016. "Are fundamentals enough? Explaining price variations in the German day-ahead and intraday power market," Energy Economics, Elsevier, vol. 54(C), pages 376-387.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuanying Chi & Wenbing Zhou & Songlin Tang & Yu Hu, 2022. "Driving Factors of CO 2 Emissions in China’s Power Industry: Relative Importance Analysis Based on Spatial Durbin Model," Energies, MDPI, vol. 15(7), pages 1-15, April.
    2. Abadie, Luis María & Chamorro, José Manuel, 2021. "Evaluation of a cross-border electricity interconnection: The case of Spain-France," Energy, Elsevier, vol. 233(C).
    3. Jha, Amit Prakash & Mahajan, Aarushi & Singh, Sanjay Kumar & Kumar, Piyush, 2022. "Renewable energy proliferation for sustainable development: Role of cross-border electricity trade," Renewable Energy, Elsevier, vol. 201(P1), pages 1189-1199.
    4. Doering, Kenji & Sendelbach, Luke & Steinschneider, Scott & Lindsay Anderson, C., 2021. "The effects of wind generation and other market determinants on price spikes," Applied Energy, Elsevier, vol. 300(C).

    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. Roger Bivand & Giovanni Millo & Gianfranco Piras, 2021. "A Review of Software for Spatial Econometrics in R," Mathematics, MDPI, vol. 9(11), pages 1-40, June.
    2. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    3. Mahler, Valentin & Girard, Robin & Kariniotakis, Georges, 2022. "Data-driven structural modeling of electricity price dynamics," Energy Economics, Elsevier, vol. 107(C).
    4. Debarsy, Nicolas & Ertur, Cem, 2010. "Testing for spatial autocorrelation in a fixed effects panel data model," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 453-470, November.
    5. Arbués, Pelayo & Baños, José F. & Mayor, Matías, 2015. "The spatial productivity of transportation infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 166-177.
    6. Abadie, Luis María & Chamorro, José Manuel, 2021. "Evaluation of a cross-border electricity interconnection: The case of Spain-France," Energy, Elsevier, vol. 233(C).
    7. Harald Badinger & Peter Egger, 2015. "Fixed Effects and Random Effects Estimation of Higher-order Spatial Autoregressive Models with Spatial Autoregressive and Heteroscedastic Disturbances," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(1), pages 11-35, March.
    8. Herrera Gómez, Marcos, 2017. "Fundamentos de Econometría Espacial Aplicada [Fundamentals of Applied Spatial Econometrics]," MPRA Paper 80871, University Library of Munich, Germany.
    9. repec:rri:wpaper:201303 is not listed on IDEAS
    10. Panagiotis Artelaris, 2021. "Regional economic growth and inequality in Greece," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 141-158, February.
    11. Álvarez, Inmaculada C. & Barbero, Javier & Zofío, José L., 2017. "A Panel Data Toolbox for MATLAB," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i06).
    12. Harald Badinger & Peter Egger, 2013. "Estimation and testing of higher-order spatial autoregressive panel data error component models," Journal of Geographical Systems, Springer, vol. 15(4), pages 453-489, October.
    13. Oliver W. Lerbs & Christian A. Oberst, 2014. "Explaining the Spatial Variation in Homeownership Rates: Results for German Regions," Regional Studies, Taylor & Francis Journals, vol. 48(5), pages 844-865, May.
    14. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
    15. Hong Hiep Hoang & Cong Minh Huynh & Nguyen Minh Huy Duong & Ngoc Hoe Chau, 2022. "Determinants of foreign direct investment in Southern Central Coast of Vietnam: a spatial econometric analysis," Economic Change and Restructuring, Springer, vol. 55(1), pages 285-310, February.
    16. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    17. repec:rri:wpaper:201301 is not listed on IDEAS
    18. Ming He & Kuan-Pin Lin, 2015. "Testing in a Random Effects Panel Data Model with Spatially Correlated Error Components and Spatially Lagged Dependent Variables," Econometrics, MDPI, vol. 3(4), pages 1-36, November.
    19. Paul Feichtinger & Klaus Salhofer, 2016. "The Fischler Reform of the Common Agricultural Policy and Agricultural Land Prices," Land Economics, University of Wisconsin Press, vol. 92(3), pages 411-432.
    20. João Romão & João Guerreiro & Paulo M. M. Rodrigues, 2017. "Territory and Sustainable Tourism Development: a Space-Time Analysis on European Regions," REGION, European Regional Science Association, vol. 4, pages 1-17.
    21. Julia Varlamova & Ekaterina Kadochnikova, 2023. "Modeling the Spatial Effects of Digital Data Economy on Regional Economic Growth: SAR, SEM and SAC Models," Mathematics, MDPI, vol. 11(16), pages 1-31, August.
    22. Pesaran, M. Hashem & Tosetti, Elisa, 2011. "Large panels with common factors and spatial correlation," Journal of Econometrics, Elsevier, vol. 161(2), pages 182-202, April.

    More about this item

    Keywords

    Spatial analysis; ENTSO-E; Electricity; Power flow;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

    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:renene:v:148:y:2020:i:c:p:205-213. 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.journals.elsevier.com/renewable-energy .

    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.