IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v109y2022ics0140988322000834.html
   My bibliography  Save this article

Firm-level energy rebound effects and relative efficiency in the German manufacturing sector

Author

Listed:
  • Berner, Anne
  • Lange, Steffen
  • Silbersdorff, Alexander

Abstract

Energy use has not decreased significantly over the last decade even though energy efficiency has increased in Germany. The lacking impact of recent energy efficiency measures could be related to growth-induced rebound effects. To quantify and understand these rebound effects and identify rebound-driving and rebound-mitigating firm characteristics, we analyze an official micro-level data set in the German manufacturing sector, with information on more than 16,000 firms. A prerequisite for the rebound estimation is the dynamic analysis of firms’ relative efficiency scores. To this end, we apply quantile regression including fixed effects. We find that a comparative reduction of energy in a firm’s production process is associated with a reduced energy use in the following years. However, we also found that 4.5 to 5.3% of potential energy savings at the firm level are on average eaten up by expanding production in the subsequent periods. At face value, this growth-induced rebound effect is small. However, our analysis shows that the magnitude of the rebound effect is not constant but depends on characteristics and investment decisions of the respective firms.

Suggested Citation

  • Berner, Anne & Lange, Steffen & Silbersdorff, Alexander, 2022. "Firm-level energy rebound effects and relative efficiency in the German manufacturing sector," Energy Economics, Elsevier, vol. 109(C).
    • Handle: RePEc:eee:eneeco:v:109:y:2022:i:c:s0140988322000834
    DOI: 10.1016/j.eneco.2022.105903
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988322000834
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2022.105903?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. Li, Ke & Zhang, Ning & Liu, Yanchu, 2016. "The energy rebound effects across China’s industrial sectors: An output distance function approach," Applied Energy, Elsevier, vol. 184(C), pages 1165-1175.
    2. Franklin Satterthwaite, 1941. "Synthesis of variance," Psychometrika, Springer;The Psychometric Society, vol. 6(5), pages 309-316, October.
    3. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    4. Manuel Frondel and Colin Vance, 2013. "Re-Identifying the Rebound: What About Asymmetry?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    5. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    6. Audrey Laporte & Adrian Rohit Dass, 2016. "The Use of Panel Quantile Regression for Efficiency Measurement: Insights from Monte Carlo Simulations," Working Papers 160005, Canadian Centre for Health Economics.
    7. Stern, David I., 2020. "How large is the economy-wide rebound effect?," Energy Policy, Elsevier, vol. 147(C).
    8. A. Greening, Lorna & Greene, David L. & Difiglio, Carmen, 2000. "Energy efficiency and consumption -- the rebound effect -- a survey," Energy Policy, Elsevier, vol. 28(6-7), pages 389-401, June.
    9. Boyd, Gale A. & Lee, Jonathan M., 2019. "Measuring plant level energy efficiency and technical change in the U.S. metal-based durable manufacturing sector using stochastic frontier analysis," Energy Economics, Elsevier, vol. 81(C), pages 159-174.
    10. Morakinyo O. Adetutu, Anthony J. Glass, and Thomas G. Weyman-Jones, 2016. "Economy-wide Estimates of Rebound Effects: Evidence from Panel Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    11. Yan, Zheming & Ouyang, Xiaoling & Du, Kerui, 2019. "Economy-wide estimates of energy rebound effect: Evidence from China's provinces," Energy Economics, Elsevier, vol. 83(C), pages 389-401.
    12. Ferrara, Giancarlo & Vidoli, Francesco, 2017. "Semiparametric stochastic frontier models: A generalized additive model approach," European Journal of Operational Research, Elsevier, vol. 258(2), pages 761-777.
    13. Amjadi, Golnaz & Lundgren, Tommy & Persson, Lars, 2018. "The Rebound Effect in Swedish Heavy Industry," Energy Economics, Elsevier, vol. 71(C), pages 140-148.
    14. Llorca, Manuel & Jamasb, Tooraj, 2017. "Energy efficiency and rebound effect in European road freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 98-110.
    15. Chunping Liu & Audrey Laporte & Brian S. Ferguson, 2008. "The quantile regression approach to efficiency measurement: insights from Monte Carlo simulations," Health Economics, John Wiley & Sons, Ltd., vol. 17(9), pages 1073-1087, September.
    16. Saunders, Harry D., 2013. "Historical evidence for energy efficiency rebound in 30 US sectors and a toolkit for rebound analysts," Technological Forecasting and Social Change, Elsevier, vol. 80(7), pages 1317-1330.
    17. Saunders, Harry D., 2008. "Fuel conserving (and using) production functions," Energy Economics, Elsevier, vol. 30(5), pages 2184-2235, September.
    18. Paul E. Brockway & Harry Saunders & Matthew K. Heun & Timothy J. Foxon & Julia K. Steinberger & John R. Barrett & Steve Sorrell, 2017. "Energy Rebound as a Potential Threat to a Low-Carbon Future: Findings from a New Exergy-Based National-Level Rebound Approach," Energies, MDPI, vol. 10(1), pages 1-24, January.
    19. Petrick, Sebastian, 2013. "Carbon efficiency, technology, and the role of innovation patterns: Evidence from German plant-level microdata," Kiel Working Papers 1833, Kiel Institute for the World Economy (IfW Kiel).
    20. De Borger, Bruno & Mulalic, Ismir & Rouwendal, Jan, 2016. "Measuring the rebound effect with micro data: A first difference approach," Journal of Environmental Economics and Management, Elsevier, vol. 79(C), pages 1-17.
    21. Harty D. Saunders, 1992. "The Khazzoom-Brookes Postulate and Neoclassical Growth," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 131-148.
    22. Anna Dahlqvist, Tommy Lundgren, and Per-Olov Marklund, 2021. "The Rebound Effect in Energy-Intensive Industries: A Factor Demand Model with Asymmetric Price Response," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 177-204.
    23. Bentzen, Jan, 2004. "Estimating the rebound effect in US manufacturing energy consumption," Energy Economics, Elsevier, vol. 26(1), pages 123-134, January.
    24. Kube, Roland & von Graevenitz, Kathrine & Löschel, Andreas & Massier, Philipp, 2019. "Do voluntary environmental programs reduce emissions? EMAS in the German manufacturing sector," Energy Economics, Elsevier, vol. 84(S1).
    25. Haas, Reinhard & Biermayr, Peter, 2000. "The rebound effect for space heating Empirical evidence from Austria," Energy Policy, Elsevier, vol. 28(6-7), pages 403-410, June.
    26. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    27. Orea, Luis & Llorca, Manuel & Filippini, Massimo, 2015. "A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand," Energy Economics, Elsevier, vol. 49(C), pages 599-609.
    28. repec:dau:papers:123456789/1908 is not listed on IDEAS
    29. Fare, Rolf & Grosskopf, Shawna, 1992. "Malmquist Productivity Indexes and Fisher Ideal Indexes," Economic Journal, Royal Economic Society, vol. 102(410), pages 158-160, January.
    30. Amjadi, Golnaz & Lundgren, Tommy & Zhou, Whenchao, 2020. "A Dynamic Analysis of Industrial Energy Efficiency and the Rebound Effect," CERE Working Papers 2020:1, CERE - the Center for Environmental and Resource Economics.
    31. Zhang, Yue-Jun & Peng, Hua-Rong & Su, Bin, 2017. "Energy rebound effect in China's Industry: An aggregate and disaggregate analysis," Energy Economics, Elsevier, vol. 61(C), pages 199-208.
    32. Todd Gerarden & Richard G. Newell & Robert N. Stavins, 2015. "Deconstructing the Energy-Efficiency Gap: Conceptual Frameworks and Evidence," American Economic Review, American Economic Association, vol. 105(5), pages 183-186, May.
    33. Joeri Rogelj & Alexander Popp & Katherine V. Calvin & Gunnar Luderer & Johannes Emmerling & David Gernaat & Shinichiro Fujimori & Jessica Strefler & Tomoko Hasegawa & Giacomo Marangoni & Volker Krey &, 2018. "Scenarios towards limiting global mean temperature increase below 1.5 °C," Nature Climate Change, Nature, vol. 8(4), pages 325-332, April.
    34. Berkhout, Peter H. G. & Muskens, Jos C. & W. Velthuijsen, Jan, 2000. "Defining the rebound effect," Energy Policy, Elsevier, vol. 28(6-7), pages 425-432, June.
    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. Hasan, Mohammad Maruf & Du, Fang, 2023. "The role of foreign trade and technology innovation on economic recovery in China: The mediating role of natural resources development," Resources Policy, Elsevier, vol. 80(C).
    2. Zhu, Minglei & Huang, Haiyan & Ma, Weiwen, 2023. "Transformation of natural resource use: Moving towards sustainability through ICT-based improvements in green total factor energy efficiency," Resources Policy, Elsevier, vol. 80(C).
    3. Madina Khudaykulova & He Yuanqiong & Akmal Khudaykulov, 2022. "Economic Consequences and Implications of the Ukraine-Russia War," International Journal of Management Science and Business Administration, Inovatus Services Ltd., vol. 8(4), pages 44-52, May.

    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. Adha, Rishan & Hong, Cheng-Yih & Firmansyah, M. & Paranata, Ade, 2021. "Rebound effect with energy efficiency determinants: a two-stage analysis of residential electricity consumption in Indonesia," MPRA Paper 110444, University Library of Munich, Germany.
    2. Dahlqvist, Anna & Lundgren, Tommy & Marklund, Per-Olov, 2017. "Assessing the Rebound Effect in Energy Intensive Industries: A Factor Demand Model Approach with Asymmetric Price Response," Working Papers 150, National Institute of Economic Research.
    3. Rocha, Felipe Freitas da & Almeida, Edmar Luiz Fagundes de, 2021. "A general equilibrium model of macroeconomic rebound effect: A broader view," Energy Economics, Elsevier, vol. 98(C).
    4. Ouyang, Xiaoling & Yang, Yuchuan & Du, Kerui & Cheng, Zhenyu, 2022. "How does residential electricity consumption respond to electricity efficiency improvement? Evidence from 287 prefecture-level cities in China," Energy Policy, Elsevier, vol. 171(C).
    5. Du, Kerui & Liu, Xueyue & Zhao, Cheng, 2023. "Environmental regulation mitigates energy rebound effect," Energy Economics, Elsevier, vol. 125(C).
    6. Lin, Boqiang & Zhu, Runqing, 2022. "How does market-oriented reform influence the rebound effect of China’s mining industry?," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 34-44.
    7. Lin, Boqiang & Chen, Yufang & Zhang, Guoliang, 2017. "Technological progress and rebound effect in China's nonferrous metals industry: An empirical study," Energy Policy, Elsevier, vol. 109(C), pages 520-529.
    8. Bruns, Stephan B. & Moneta, Alessio & Stern, David I., 2021. "Estimating the economy-wide rebound effect using empirically identified structural vector autoregressions," Energy Economics, Elsevier, vol. 97(C).
    9. Yan, Zheming & Ouyang, Xiaoling & Du, Kerui, 2019. "Economy-wide estimates of energy rebound effect: Evidence from China's provinces," Energy Economics, Elsevier, vol. 83(C), pages 389-401.
    10. Jin, Taeyoung & Kim, Jinsoo, 2019. "A new approach for assessing the macroeconomic growth energy rebound effect," Applied Energy, Elsevier, vol. 239(C), pages 192-200.
    11. Zhang, Yue-Jun & Peng, Hua-Rong & Liu, Zhao & Tan, Weiping, 2015. "Direct energy rebound effect for road passenger transport in China: A dynamic panel quantile regression approach," Energy Policy, Elsevier, vol. 87(C), pages 303-313.
    12. Cansino, José M. & Ordóñez, Manuel & Prieto, Manuela, 2022. "Decomposition and measurement of the rebound effect: The case of energy efficiency improvements in Spain," Applied Energy, Elsevier, vol. 306(PA).
    13. Zhang, Jiangshan & Lin Lawell, C.-Y. Cynthia, 2017. "The macroeconomic rebound effect in China," Energy Economics, Elsevier, vol. 67(C), pages 202-212.
    14. Orea, Luis & Llorca, Manuel & Filippini, Massimo, 2015. "A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand," Energy Economics, Elsevier, vol. 49(C), pages 599-609.
    15. Amjadi, Golnaz & Lundgren, Tommy & Persson, Lars, 2018. "The Rebound Effect in Swedish Heavy Industry," Energy Economics, Elsevier, vol. 71(C), pages 140-148.
    16. Jafari, Mahboubeh & Stern, David I. & Bruns, Stephan B., 2022. "How large is the economy-wide rebound effect in middle income countries? Evidence from Iran," Ecological Economics, Elsevier, vol. 193(C).
    17. Li, Guohao & Niu, Miaomiao & Xiao, Jin & Wu, Jiaqian & Li, Jinkai, 2023. "The rebound effect of decarbonization in China’s power sector under the carbon trading scheme," Energy Policy, Elsevier, vol. 177(C).
    18. Colmenares, Gloria & Löschel, Andreas & Madlener, Reinhard, 2019. "The rebound effect and its representation in energy and climate models," CAWM Discussion Papers 106, University of Münster, Münster Center for Economic Policy (MEP).
    19. Wang, Zhaohua & Lu, Milin & Wang, Jian-Cai, 2014. "Direct rebound effect on urban residential electricity use: An empirical study in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 124-132.
    20. Rishan Adha & Cheng-Yih Hong, 2021. "How Large the Direct Rebound Effect for Residential Electricity Consumption When the Artificial Neural Network Takes on the Role? A Taiwan Case Study of Household Electricity Consumption," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 354-364.

    More about this item

    Keywords

    Rebound effect; Manufacturing sectors; Energy efficiency; Quantile regression; Micro data;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    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:eneeco:v:109:y:2022:i:c:s0140988322000834. 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.elsevier.com/locate/eneco .

    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.