IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v74y2018icp441-455.html
   My bibliography  Save this article

Rebound effect of transportation considering additional capital costs and input-output relationships: The role of subsistence consumption and unmet demand

Author

Listed:
  • Li, Jianglong
  • Li, Aijun
  • Xie, Xuan

Abstract

The anticipated carbon mitigation through energy-saving technology progress might be partially or even totally offset due to rebound effect. A better understanding of rebound effect, especially the underling mechanisms, has important implications for energy efficiency policies to achieve the goal of sustainability. Previous studies usually ignore additional capital costs for adopting energy-efficient equipment and indirect carbon emissions for providing new consumption bundles. Also, the precise mechanisms of how living standard affects rebound effect are unknown. Using almost ideal demand system (AIDS) model and input-output relationships among sectors, this paper builds a method to estimate the rebound effect that allows for additional capital costs and carbon emission changes of all other goods and services due to backward-forward linkages. We find that rebound effect is over 100% for transportation in rural China even though additional capital costs would indeed reduce the magnitude, and the results are quite robust to alternative settings. As for the mechanisms, rebound effect is divided into substitution and income channels by Slutsky decomposition. Here we show that both of these two channels are dependent on living standard because of subsistence consumption and unmet demand. Carbon emissions of poor households will rebound more through income channel of unmet demand, while rich households usually do not restricted by subsistence consumption, and thus through substitution channel, rebound of carbon emissions would be larger for rich households. The opposite directions of mechanisms dig more information about the nonlinearity of rebound effect to income levels. Furthermore, given the estimating results, this paper gains several insights in terms of welfare benefits, rather than just focuses on carbon reduction.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:eneeco:v:74:y:2018:i:c:p:441-455
    DOI: 10.1016/j.eneco.2018.06.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988318302378
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2018.06.019?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. 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.
    2. Deaton, Angus, 1987. "Estimation of own- and cross-price elasticities from household survey data," Journal of Econometrics, Elsevier, vol. 36(1-2), pages 7-30.
    3. Vu, Linh & Glewwe, Paul, 2011. "Impacts of Rising Food Prices on Poverty and Welfare in Vietnam," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 36(1), pages 1-14, April.
    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. Jed Friedman & James Levinsohn, 2002. "The Distributional Impacts of Indonesia's Financial Crisis on Household Welfare: A "Rapid Response" Methodology," The World Bank Economic Review, World Bank, vol. 16(3), pages 397-423, December.
    6. Yang, Mian & Fan, Ying & Yang, Fuxia & Hu, Hui, 2014. "Regional disparities in carbon dioxide reduction from China's uniform carbon tax: A perspective on interfactor/interfuel substitution," Energy, Elsevier, vol. 74(C), pages 131-139.
    7. 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.
    8. Kenneth A. Small & Kurt Van Dender, 2007. "Fuel Efficiency and Motor Vehicle Travel: The Declining Rebound Effect," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 25-52.
    9. 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.
    10. Frondel, Manuel & Ritter, Nolan & Vance, Colin, 2012. "Heterogeneity in the rebound effect: Further evidence for Germany," Energy Economics, Elsevier, vol. 34(2), pages 461-467.
    11. Lin, Boqiang & Li, Jianglong, 2014. "The rebound effect for heavy industry: Empirical evidence from China," Energy Policy, Elsevier, vol. 74(C), pages 589-599.
    12. Thomas, Brinda A. & Azevedo, Inês L., 2013. "Estimating direct and indirect rebound effects for U.S. households with input–output analysis. Part 2: Simulation," Ecological Economics, Elsevier, vol. 86(C), pages 188-198.
    13. 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.
    14. Sorrell, Steve, 2015. "Reducing energy demand: A review of issues, challenges and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 74-82.
    15. 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.
    16. Li, Jianglong & Lin, Boqiang, 2017. "Rebound effect by incorporating endogenous energy efficiency: A comparison between heavy industry and light industry," Applied Energy, Elsevier, vol. 200(C), pages 347-357.
    17. Moshiri, Saeed & Aliyev, Kamil, 2017. "Rebound effect of efficiency improvement in passenger cars on gasoline consumption in Canada," Ecological Economics, Elsevier, vol. 131(C), pages 330-341.
    18. 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.
    19. 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.
    20. 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.
    21. Harry D. Saunders, 2015. "Recent Evidence for Large Rebound: Elucidating the Drivers and their Implications for Climate Change Models," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    22. 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.
    23. 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.
    24. Bentzen, Jan, 2004. "Estimating the rebound effect in US manufacturing energy consumption," Energy Economics, Elsevier, vol. 26(1), pages 123-134, January.
    25. Roy, Joyashree, 2000. "The rebound effect: some empirical evidence from India," Energy Policy, Elsevier, vol. 28(6-7), pages 433-438, June.
    26. Brannlund, Runar & Ghalwash, Tarek & Nordstrom, Jonas, 2007. "Increased energy efficiency and the rebound effect: Effects on consumption and emissions," Energy Economics, Elsevier, vol. 29(1), pages 1-17, January.
    27. 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.
    28. Chitnis, Mona & Sorrell, Steve, 2015. "Living up to expectations: Estimating direct and indirect rebound effects for UK households," Energy Economics, Elsevier, vol. 52(S1), pages 100-116.
    29. Li, Jianglong & Yang, Lisha & Long, Houyin, 2018. "Climatic impacts on energy consumption: Intensive and extensive margins," Energy Economics, Elsevier, vol. 71(C), pages 332-343.
    30. 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.
    31. Shao, Shuai & Tian, Zhihua & Yang, Lili, 2017. "High speed rail and urban service industry agglomeration: Evidence from China's Yangtze River Delta region," Journal of Transport Geography, Elsevier, vol. 64(C), pages 174-183.
    32. Mizobuchi, Kenichi, 2008. "An empirical study on the rebound effect considering capital costs," Energy Economics, Elsevier, vol. 30(5), pages 2486-2516, September.
    33. Cho, Won G. & Nam, Kiseok & Pagan, Jose A., 2004. "Economic growth and interfactor/interfuel substitution in Korea," Energy Economics, Elsevier, vol. 26(1), pages 31-50, January.
    34. Shao, Shuai & Yang, Lili & Gan, Chunhui & Cao, Jianhua & Geng, Yong & Guan, Dabo, 2016. "Using an extended LMDI model to explore techno-economic drivers of energy-related industrial CO2 emission changes: A case study for Shanghai (China)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 516-536.
    35. Chitnis, Mona & Sorrell, Steve & Druckman, Angela & Firth, Steven K. & Jackson, Tim, 2014. "Who rebounds most? Estimating direct and indirect rebound effects for different UK socioeconomic groups," Ecological Economics, Elsevier, vol. 106(C), pages 12-32.
    36. 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.
    37. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, 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. Yoo, Sunbin & Koh, Kyung Woong & Yoshida, Yoshikuni & Wakamori, Naoki, 2019. "Revisiting Jevons's paradox of energy rebound: Policy implications and empirical evidence in consumer-oriented financial incentives from the Japanese automobile market, 2006–2016," Energy Policy, Elsevier, vol. 133(C).
    2. 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.
    3. Du, Qiang & Han, Xiao & Li, Yi & Li, Zhe & Xia, Bo & Guo, Xiqian, 2021. "The energy rebound effect of residential buildings: Evidence from urban and rural areas in China," Energy Policy, Elsevier, vol. 153(C).
    4. 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).
    5. 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.
    6. 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.

    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. 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.
    2. Zhang, Yue-Jun & Liu, Zhao & Qin, Chang-Xiong & Tan, Tai-De, 2017. "The direct and indirect CO2 rebound effect for private cars in China," Energy Policy, Elsevier, vol. 100(C), pages 149-161.
    3. 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.
    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. 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.
    6. Du, Qiang & Han, Xiao & Li, Yi & Li, Zhe & Xia, Bo & Guo, Xiqian, 2021. "The energy rebound effect of residential buildings: Evidence from urban and rural areas in China," Energy Policy, Elsevier, vol. 153(C).
    7. 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.
    8. 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.
    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. 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.
    11. Milin Lu & Zhaohua Wang, 2017. "Rebound effects for residential electricity use in urban China: an aggregation analysis based E-I-O and scenario simulation," Annals of Operations Research, Springer, vol. 255(1), pages 525-546, August.
    12. 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.
    13. 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).
    14. Zha, Donglan & Chen, Qian & Wang, Lijun, 2022. "Exploring carbon rebound effects in Chinese households’ consumption: A simulation analysis based on a multi-regional input–output framework," Applied Energy, Elsevier, vol. 313(C).
    15. 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.
    16. 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).
    17. Chen, Qian & Zha, Donglan & Wang, Lijun & Yang, Guanglei, 2022. "The direct CO2 rebound effect in households: Evidence from China's provinces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    18. 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.
    19. 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.
    20. 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.

    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:74:y:2018:i:c:p:441-455. 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.