IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v83y2019icp389-401.html
   My bibliography  Save this article

Economy-wide estimates of energy rebound effect: Evidence from China's provinces

Author

Listed:
  • Yan, Zheming
  • Ouyang, Xiaoling
  • Du, Kerui

Abstract

The ongoing debate on the magnitude of China's economy-wide energy rebound effect (RE) entails further investigations not only with more details, but also with more credible methods. In this study, a modified two-stage approach, which could avoid methodological issues regarding RE estimation, is applied to estimate macroeconomic RE with a data panel of 30 provinces in China during the period 1997–2015. In particular, in order to comprehensively measure energy efficiency, we construct a dynamic energy efficiency indicator which considers not only the static efficiency of energy use but also the technical change regarding energy usage. Using dynamic panel data models, we estimate the elasticity of energy consumption with respect to energy efficiency which directly links to the measurement of RE. The short-run and long-run estimates of RE are reported, and the 95% confidence interval was computed for each sample based on the nonparametric bootstrap method to further analyze the macroeconomic RE of different regions. Results indicate that the average RE of all provinces is 88.55% in the short run, and the average long-run RE is 77.50%; the RE in the developed eastern region continuously decreased, while RE in the western region increased to be the largest during the research period.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:eneeco:v:83:y:2019:i:c:p:389-401
    DOI: 10.1016/j.eneco.2019.07.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988319302488
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2019.07.027?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. Hashimzade, Nigar & Myles, Gareth & Black, John, 2017. "A Dictionary of Economics," OUP Catalogue, Oxford University Press, edition 5, number 9780198759430, Decembrie.
    3. Gale A. Boyd, 2008. "Estimating Plant Level Energy Efficiency with a Stochastic Frontier," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-44.
    4. Sorrell, Steve & Dimitropoulos, John, 2008. "The rebound effect: Microeconomic definitions, limitations and extensions," Ecological Economics, Elsevier, vol. 65(3), pages 636-649, April.
    5. Steve Sorrell, 2014. "Energy Substitution, Technical Change and Rebound Effects," Energies, MDPI, vol. 7(5), pages 1-24, April.
    6. Ouyang, Xiaoling & Sun, Chuanwang, 2015. "Energy savings potential in China's industrial sector: From the perspectives of factor price distortion and allocative inefficiency," Energy Economics, Elsevier, vol. 48(C), pages 117-126.
    7. Karen Turner, 2013. ""Rebound" Effects from Increased Energy Efficiency: A Time to Pause and Reflect," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    8. Shao, Shuai & Huang, Tao & Yang, Lili, 2014. "Using latent variable approach to estimate China׳s economy-wide energy rebound effect over 1954–2010," Energy Policy, Elsevier, vol. 72(C), pages 235-248.
    9. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    10. 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.
    11. 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).
    12. Lin, Boqiang & Li, Jianglong, 2014. "The rebound effect for heavy industry: Empirical evidence from China," Energy Policy, Elsevier, vol. 74(C), pages 589-599.
    13. Lu, Yingying & Liu, Yu & Zhou, Meifang, 2017. "Rebound effect of improved energy efficiency for different energy types: A general equilibrium analysis for China," Energy Economics, Elsevier, vol. 62(C), pages 248-256.
    14. Liu, Jingru & Sun, Xin & Lu, Bin & Zhang, Yunkun & Sun, Rui, 2016. "The life cycle rebound effect of air-conditioner consumption in China," Applied Energy, Elsevier, vol. 184(C), pages 1026-1032.
    15. Ju, Keyi & Su, Bin & Zhou, Dequn & Wu, Junmin, 2017. "Does energy-price regulation benefit China's economy and environment? Evidence from energy-price distortions," Energy Policy, Elsevier, vol. 105(C), pages 108-119.
    16. Lin, Boqiang & Yang, Fang & Liu, Xia, 2013. "A study of the rebound effect on China's current energy conservation and emissions reduction: Measures and policy choices," Energy, Elsevier, vol. 58(C), pages 330-339.
    17. Daron Acemoglu, 2002. "Directed Technical Change," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(4), pages 781-809.
    18. Glomsrod, Solveig & Taoyuan, Wei, 2005. "Coal cleaning: a viable strategy for reduced carbon emissions and improved environment in China?," Energy Policy, Elsevier, vol. 33(4), pages 525-542, March.
    19. Kenneth Gillingham & David Rapson & Gernot Wagner, 2016. "The Rebound Effect and Energy Efficiency Policy," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 10(1), pages 68-88.
    20. 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.
    21. Hu, Jin-Li & Wang, Shih-Chuan, 2006. "Total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 34(17), pages 3206-3217, November.
    22. 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.
    23. Wang, H. & Zhou, P. & Zhou, D.Q., 2012. "An empirical study of direct rebound effect for passenger transport in urban China," Energy Economics, Elsevier, vol. 34(2), pages 452-460.
    24. Everaert, Gerdie & Pozzi, Lorenzo, 2007. "Bootstrap-based bias correction for dynamic panels," Journal of Economic Dynamics and Control, Elsevier, vol. 31(4), pages 1160-1184, April.
    25. Lin, Boqiang & Liu, Xia, 2013. "Reform of refined oil product pricing mechanism and energy rebound effect for passenger transportation in China," Energy Policy, Elsevier, vol. 57(C), pages 329-337.
    26. Thomas, Brinda A. & Azevedo, Inês L., 2013. "Estimating direct and indirect rebound effects for U.S. households with input–output analysis Part 1: Theoretical framework," Ecological Economics, Elsevier, vol. 86(C), pages 199-210.
    27. Madlener, R. & Alcott, B., 2009. "Energy rebound and economic growth: A review of the main issues and research needs," Energy, Elsevier, vol. 34(3), pages 370-376.
    28. Song, Feng & Zheng, Xinye, 2012. "What drives the change in China's energy intensity: Combining decomposition analysis and econometric analysis at the provincial level," Energy Policy, Elsevier, vol. 51(C), pages 445-453.
    29. Stapleton, Lee & Sorrell, Steve & Schwanen, Tim, 2016. "Estimating direct rebound effects for personal automotive travel in Great Britain," Energy Economics, Elsevier, vol. 54(C), pages 313-325.
    30. Lin, Boqiang & Liu, Xia, 2012. "Dilemma between economic development and energy conservation: Energy rebound effect in China," Energy, Elsevier, vol. 45(1), pages 867-873.
    31. Ouyang, Xiaoling & Gao, Beiying & Du, Kerui & Du, Gang, 2018. "Industrial sectors' energy rebound effect: An empirical study of Yangtze River Delta urban agglomeration," Energy, Elsevier, vol. 145(C), pages 408-416.
    32. Ouyang, Jinlong & Long, Enshen & Hokao, Kazunori, 2010. "Rebound effect in Chinese household energy efficiency and solution for mitigating it," Energy, Elsevier, vol. 35(12), pages 5269-5276.
    33. Wang, Zhaohua & Lu, Milin, 2014. "An empirical study of direct rebound effect for road freight transport in China," Applied Energy, Elsevier, vol. 133(C), pages 274-281.
    34. Lin, Boqiang & Du, Kerui, 2014. "Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy," Energy, Elsevier, vol. 76(C), pages 884-890.
    35. Wang, Zhaohua & Han, Bai & Lu, Milin, 2016. "Measurement of energy rebound effect in households: Evidence from residential electricity consumption in Beijing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 852-861.
    36. Allan, Grant & Hanley, Nick & McGregor, Peter & Swales, Kim & Turner, Karen, 2007. "The impact of increased efficiency in the industrial use of energy: A computable general equilibrium analysis for the United Kingdom," Energy Economics, Elsevier, vol. 29(4), pages 779-798, July.
    37. Lin, Boqiang & Du, Kerui, 2015. "Measuring energy rebound effect in the Chinese economy: An economic accounting approach," Energy Economics, Elsevier, vol. 50(C), pages 96-104.
    38. Greene, David L., 2012. "Rebound 2007: Analysis of U.S. light-duty vehicle travel statistics," Energy Policy, Elsevier, vol. 41(C), pages 14-28.
    39. 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.
    40. Du, Kerui & Lin, Boqiang, 2017. "International comparison of total-factor energy productivity growth: A parametric Malmquist index approach," Energy, Elsevier, vol. 118(C), pages 481-488.
    41. Dimitropoulos, John, 2007. "Energy productivity improvements and the rebound effect: An overview of the state of knowledge," Energy Policy, Elsevier, vol. 35(12), pages 6354-6363, December.
    42. Sorrell, Steve & Dimitropoulos, John & Sommerville, Matt, 2009. "Empirical estimates of the direct rebound effect: A review," Energy Policy, Elsevier, vol. 37(4), pages 1356-1371, April.
    43. 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.
    44. Zhang, Jiangshan & Lin Lawell, C.-Y. Cynthia, 2017. "The macroeconomic rebound effect in China," Energy Economics, Elsevier, vol. 67(C), pages 202-212.
    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. Fei, Rilong & Wang, Haolin & Wen, Zihao & Yuan, Zhen & Yuan, Kaihua & Chunga, Joseph, 2021. "Tracking factor substitution and the rebound effect of China’s agricultural energy consumption: A new research perspective from asymmetric response," Energy, Elsevier, vol. 216(C).
    2. Chen, Jiandong & Gao, Ming & Shahbaz, Muhammad & Cheng, Shulei & Song, Malin, 2021. "An improved decomposition approach toward energy rebound effects in China: Review since 1992," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    3. Yang, Zhenbing & Shi, Qingquan & Lv, Xiangqiu & Shi, Qi, 2022. "Heterogeneous low-carbon targets and energy structure optimization: Does stricter carbon regulation really matter?," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 329-343.
    4. Meng, Ming & Qu, Danlei, 2022. "Understanding the green energy efficiencies of provinces in China: A Super-SBM and GML analysis," Energy, Elsevier, vol. 239(PA).
    5. 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).
    6. Abudureheman, Maliyamu & Jiang, Qingzhe & Dong, Xiucheng & Dong, Cong, 2022. "Spatial effects of dynamic comprehensive energy efficiency on CO2 reduction in China," Energy Policy, Elsevier, vol. 166(C).
    7. 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).
    8. Xu, Mengmeng & Lin, Boqiang & Wang, Siquan, 2021. "Towards energy conservation by improving energy efficiency? Evidence from China’s metallurgical industry," Energy, Elsevier, vol. 216(C).
    9. Zhou, P. & Zhang, H. & Zhang, L.P., 2022. "The drivers of energy intensity changes in Chinese cities: A production-theoretical decomposition analysis," Applied Energy, Elsevier, vol. 307(C).
    10. Du, Kerui & Liu, Xueyue & Zhao, Cheng, 2023. "Environmental regulation mitigates energy rebound effect," Energy Economics, Elsevier, vol. 125(C).
    11. 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).
    12. Bai, Caiquan & Feng, Chen & Du, Kerui & Wang, Yuansheng & Gong, Yuan, 2020. "Understanding spatial-temporal evolution of renewable energy technology innovation in China: Evidence from convergence analysis," Energy Policy, Elsevier, vol. 143(C).
    13. Maliyamu Abudureheman & Qingzhe Jiang & Xiucheng Dong & Cong Dong, 2022. "CO 2 Emissions in China: Does the Energy Rebound Matter?," Energies, MDPI, vol. 15(12), pages 1-25, June.
    14. Xie, Minghua & Yi, Xiangyu & Liu, Kui & Sun, Chuanwang & Kong, Qingbao, 2023. "How much natural gas does China need: An empirical study from the perspective of energy transition," Energy, Elsevier, vol. 266(C).
    15. 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).
    16. Berner, Anne & Bruns, Stephan & Moneta, Alessio & Stern, David I., 2022. "Do energy efficiency improvements reduce energy use? Empirical evidence on the economy-wide rebound effect in Europe and the United States," Energy Economics, Elsevier, vol. 110(C).
    17. Miao, Zhuang & Chen, Xiaodong, 2022. "Combining parametric and non-parametric approach, variable & source -specific productivity changes and rebound effect of energy & environment," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    18. Wang, Ailun & Lin, Boqiang, 2020. "Structural optimization and carbon taxation in China's commercial sector," Energy Policy, Elsevier, vol. 140(C).
    19. 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).
    20. Li, Xiaoyan & Xu, Hengzhou, 2020. "The Energy-conservation and Emission-reduction Paths of Industrial sectors: Evidence from Chinas 35 industrial sectors," Energy Economics, Elsevier, vol. 86(C).
    21. Maliyamu Abudureheman & Qingzhe Jiang & Jiong Gong & Abulaiti Yiming, 2023. "Estimating and Decomposing the TFP Growth of Service-Oriented Manufacturing in China: A Translogarithmic Stochastic Frontier Approach," Sustainability, MDPI, vol. 15(7), pages 1-20, March.
    22. Kong, Li & Mu, Xianzhong & Hu, Guangwen & Tu, Chuang, 2023. "Will energy efficiency improvements reduce energy consumption? Perspective of rebound effect and evidence from beijing," Energy, Elsevier, vol. 263(PA).
    23. Jarke-Neuert, Johannes & Perino, Grischa, 2020. "Energy efficiency promotion backfires under cap-and-trade," Resource and Energy Economics, Elsevier, vol. 62(C).
    24. Sun, Chuanwang & Chen, Zhilong & Guo, Zhiru & Wu, Huixin, 2022. "Energy rebound effect of various industries in China: Based on hybrid energy input-output model," Energy, Elsevier, vol. 261(PB).
    25. Peng, Hua-Rong & Zhang, Yue-Jun & Liu, Jing-Yue, 2023. "The energy rebound effect of digital development: Evidence from 285 cities in China," Energy, Elsevier, vol. 270(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. 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).
    2. Wen, Fenghua & Ye, Zhengke & Yang, Huaidong & Li, Ke, 2018. "Exploring the rebound effect from the perspective of household: An analysis of China's provincial level," Energy Economics, Elsevier, vol. 75(C), pages 345-356.
    3. 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.
    4. 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.
    5. Rongxin Wu & Boqiang Lin, 2022. "Does Energy Efficiency Realize Energy Conservation in the Iron and Steel Industry? A Perspective of Energy Rebound Effect," IJERPH, MDPI, vol. 19(18), pages 1-20, September.
    6. 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).
    7. 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).
    8. Brockway, Paul E. & Sorrell, Steve & Semieniuk, Gregor & Heun, Matthew Kuperus & Court, Victor, 2021. "Energy efficiency and economy-wide rebound effects: A review of the evidence and its implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    9. 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.
    10. Li, Jianglong & Liu, Hongxun & Du, Kerui, 2019. "Does market-oriented reform increase energy rebound effect? Evidence from China's regional development," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    11. Li, Ke & Lin, Boqiang, 2015. "Heterogeneity in rebound effects: Estimated results and impact of China’s fossil-fuel subsidies," Applied Energy, Elsevier, vol. 149(C), pages 148-160.
    12. Zhou, Meifang & Liu, Yu & Feng, Shenghao & Liu, Yang & Lu, Yingying, 2018. "Decomposition of rebound effect: An energy-specific, general equilibrium analysis in the context of China," Applied Energy, Elsevier, vol. 221(C), pages 280-298.
    13. Li, Jianglong & Li, Aijun & Xie, Xuan, 2018. "Rebound effect of transportation considering additional capital costs and input-output relationships: The role of subsistence consumption and unmet demand," Energy Economics, Elsevier, vol. 74(C), pages 441-455.
    14. 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).
    15. Lin, Boqiang & Zhu, Penghu, 2021. "Measurement of the direct rebound effect of residential electricity consumption: An empirical study based on the China family panel studies," Applied Energy, Elsevier, vol. 301(C).
    16. Chen, Zhenni & Du, Huibin & Li, Jianglong & Southworth, Frank & Ma, Shoufeng, 2019. "Achieving low-carbon urban passenger transport in China: Insights from the heterogeneous rebound effect," Energy Economics, Elsevier, vol. 81(C), pages 1029-1041.
    17. Ouyang, Xiaoling & Gao, Beiying & Du, Kerui & Du, Gang, 2018. "Industrial sectors' energy rebound effect: An empirical study of Yangtze River Delta urban agglomeration," Energy, Elsevier, vol. 145(C), pages 408-416.
    18. Liu, Hongxun & Du, Kerui & Li, Jianglong, 2019. "An improved approach to estimate direct rebound effect by incorporating energy efficiency: A revisit of China's industrial energy demand," Energy Economics, Elsevier, vol. 80(C), pages 720-730.
    19. Yuan, Zhen & Xu, Jie & Li, Bing & Yao, Tingting, 2022. "Limits of technological progress in controlling energy consumption: Evidence from the energy rebound effects across China's industrial sector," Energy, Elsevier, vol. 245(C).
    20. Li, Ke & Jiang, Zhujun, 2016. "The impacts of removing energy subsidies on economy-wide rebound effects in China: An input-output analysis," Energy Policy, Elsevier, vol. 98(C), pages 62-72.

    More about this item

    Keywords

    Energy efficiency measurement; Energy rebound effect; Shephard energy distance function; Malmquist energy productivity index;
    All these keywords.

    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
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    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:83:y:2019:i:c:p:389-401. 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.