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Energy Efficiency in Buildings in EU Countries

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  • Silke Friedrich

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Suggested Citation

  • Silke Friedrich, 2013. "Energy Efficiency in Buildings in EU Countries," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 11(02), pages 57-59, July.
    • Handle: RePEc:ces:ifodic:v:11:y:2013:i:02:p:57-59
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    File URL: https://www.ifo.de/DocDL/dicereport213-db4.pdf
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    References listed on IDEAS

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    1. Annunziata, Eleonora & Frey, Marco & Rizzi, Francesco, 2013. "Towards nearly zero-energy buildings: The state-of-art of national regulations in Europe," Energy, Elsevier, vol. 57(C), pages 125-133.
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    Cited by:

    1. Feser, Daniel & Runst, Petrik, 2015. "Energy efficiency consultants as change agents? Examining the reasons for EECs’ limited success," ifh Working Papers 1 (2015), Volkswirtschaftliches Institut für Mittelstand und Handwerk an der Universität Göttingen (ifh).
    2. Thonipara, Anita & Runst, Petrik & Ochsner, Christian & Bizer, Kilian, 2019. "Energy efficiency of residential buildings in the European Union – An exploratory analysis of cross-country consumption patterns," Energy Policy, Elsevier, vol. 129(C), pages 1156-1167.
    3. Feser, Daniel & Runst, Petrik, 2016. "Energy efficiency consultants as change agents? Examining the reasons for EECs’ limited success," Energy Policy, Elsevier, vol. 98(C), pages 309-317.
    4. Zhao, Yang & Li, Tingting & Zhang, Xuejun & Zhang, Chaobo, 2019. "Artificial intelligence-based fault detection and diagnosis methods for building energy systems: Advantages, challenges and the future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 85-101.
    5. Wang, Huilong & Xu, Peng & Lu, Xing & Yuan, Dengkuo, 2016. "Methodology of comprehensive building energy performance diagnosis for large commercial buildings at multiple levels," Applied Energy, Elsevier, vol. 169(C), pages 14-27.
    6. Wang, Zhanwei & Wang, Zhiwei & He, Suowei & Gu, Xiaowei & Yan, Zeng Feng, 2017. "Fault detection and diagnosis of chillers using Bayesian network merged distance rejection and multi-source non-sensor information," Applied Energy, Elsevier, vol. 188(C), pages 200-214.

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    More about this item

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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