IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v161y2018icp859-869.html
   My bibliography  Save this article

Impact of technological progress on China's textile industry and future energy saving potential forecast

Author

Listed:
  • Lin, Boqiang
  • Chen, Yu
  • Zhang, Guoliang

Abstract

China has the largest textile industry with the complete industrial chain and also the largest textile exporter in the world. The study analyses the energy substitution effect of technological progress of China's textile industry using a macroeconomics approach. In order to predict future energy saving potential, we examine the relationship between energy intensity and its five main factors (technological progress, enterprise scale, labor productivity, dependence on foreign trade and industrial electricity price) by co-integration technique. Empirical results indict that electricity shows alternative features to other energy sources in the context of technological progress in China's textile industry. Besides, there exists a long-run equilibrium among energy intensity and the five main factors. Monte Carlo method was applied for risk analysis to ensure the reliability of forecast. Further, future energy saving potential and CO2 emission reduction of China's textile industry was predicted using scenario analysis. The result shows that energy conservation potential of China's textile industry is 16.16–27.53 million tons of standard coal equivalent in 2025. Additionally, it was revealed that the CO2 emission reduction caused by the energy conservation will be 32.63–55.60 million tons in 2025. Finally, future policy priorities for energy conservation of Chinese textile industry are suggested.

Suggested Citation

  • Lin, Boqiang & Chen, Yu & Zhang, Guoliang, 2018. "Impact of technological progress on China's textile industry and future energy saving potential forecast," Energy, Elsevier, vol. 161(C), pages 859-869.
  • Handle: RePEc:eee:energy:v:161:y:2018:i:c:p:859-869
    DOI: 10.1016/j.energy.2018.07.178
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218314750
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2018.07.178?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. Feng, Chao & Wang, Miao, 2017. "The economy-wide energy efficiency in China’s regional building industry," Energy, Elsevier, vol. 141(C), pages 1869-1879.
    2. Hamzacebi, Coskun & Es, Huseyin Avni, 2014. "Forecasting the annual electricity consumption of Turkey using an optimized grey model," Energy, Elsevier, vol. 70(C), pages 165-171.
    3. Chang, Kai & Pei, Ping & Zhang, Chao & Wu, Xin, 2017. "Exploring the price dynamics of CO2 emissions allowances in China's emissions trading scheme pilots," Energy Economics, Elsevier, vol. 67(C), pages 213-223.
    4. Worrell, Ernst & Martin, Nathan & Price, Lynn, 2000. "Potentials for energy efficiency improvement in the US cement industry," Energy, Elsevier, vol. 25(12), pages 1189-1214.
    5. Lin, Boqiang & Zhang, Guoliang, 2013. "Estimates of electricity saving potential in Chinese nonferrous metals industry," Energy Policy, Elsevier, vol. 60(C), pages 558-568.
    6. Hasanbeigi, Ali & Price, Lynn, 2012. "A review of energy use and energy efficiency technologies for the textile industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3648-3665.
    7. Peter C. B. Phillips & Bruce E. Hansen, 1990. "Statistical Inference in Instrumental Variables Regression with I(1) Processes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(1), pages 99-125.
    8. Tony Irawan & Djoni Hartono & Noer Azam Achsani, 2010. "An Analysis of Energy Intensity in Indonesian Manufacturing," Working Papers in Economics and Development Studies (WoPEDS) 201007, Department of Economics, Padjadjaran University, revised Aug 2010.
    9. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    10. Welsch, Heinz & Ochsen, Carsten, 2005. "The determinants of aggregate energy use in West Germany: factor substitution, technological change, and trade," Energy Economics, Elsevier, vol. 27(1), pages 93-111, January.
    11. Nabavi-Pelesaraei, Ashkan & Hosseinzadeh-Bandbafha, Homa & Qasemi-Kordkheili, Peyman & Kouchaki-Penchah, Hamed & Riahi-Dorcheh, Farshid, 2016. "Applying optimization techniques to improve of energy efficiency and GHG (greenhouse gas) emissions of wheat production," Energy, Elsevier, vol. 103(C), pages 672-678.
    12. Wolde-Rufael, Yemane, 2010. "Bounds test approach to cointegration and causality between nuclear energy consumption and economic growth in India," Energy Policy, Elsevier, vol. 38(1), pages 52-58, January.
    13. Lin, Boqiang & Wang, Xiaolei, 2014. "Promoting energy conservation in China's iron & steel sector," Energy, Elsevier, vol. 73(C), pages 465-474.
    14. Osterwald-Lenum, Michael, 1992. "A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 461-472, August.
    15. Kitamura, Yuichi, 1998. "Likelihood-Based Inference In Cointegrated Vector Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 14(4), pages 517-524, August.
    16. Zhou, P. & Ang, B.W., 2008. "Decomposition of aggregate CO2 emissions: A production-theoretical approach," Energy Economics, Elsevier, vol. 30(3), pages 1054-1067, May.
    17. Liu, Yaobin, 2009. "Exploring the relationship between urbanization and energy consumption in China using ARDL (autoregressive distributed lag) and FDM (factor decomposition model)," Energy, Elsevier, vol. 34(11), pages 1846-1854.
    18. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    19. Meier, Alan & Rosenfeld, Arthur H. & Wright, Janice, 1982. "Supply curves of conserved energy for California's residential sector," Energy, Elsevier, vol. 7(4), pages 347-358.
    20. Peng, Lihong & Zhang, Yiting & Wang, Yejun & Zeng, Xiaoling & Peng, Najun & Yu, Ang, 2015. "Energy efficiency and influencing factor analysis in the overall Chinese textile industry," Energy, Elsevier, vol. 93(P1), pages 1222-1229.
    21. Hong, Gui-Bing & Su, Te-Li & Lee, Jenq-Daw & Hsu, Tsung-Chi & Chen, Hua-Wei, 2010. "Energy conservation potential in Taiwanese textile industry," Energy Policy, Elsevier, vol. 38(11), pages 7048-7053, November.
    22. Lin, Boqiang & Wang, Xiaolei, 2014. "Exploring energy efficiency in China׳s iron and steel industry: A stochastic frontier approach," Energy Policy, Elsevier, vol. 72(C), pages 87-96.
    23. Mukherjee, Kankana, 2008. "Energy use efficiency in the Indian manufacturing sector: An interstate analysis," Energy Policy, Elsevier, vol. 36(2), pages 662-672, February.
    24. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    25. Song, Ma-Lin & Zhang, Lin-Ling & Liu, Wei & Fisher, Ron, 2013. "Bootstrap-DEA analysis of BRICS’ energy efficiency based on small sample data," Applied Energy, Elsevier, vol. 112(C), pages 1049-1055.
    26. Uri, Noel D. & Flanagan, Stephen P., 1979. "Short-term forecasting of crude petroleum and natural gas production," Applied Energy, Elsevier, vol. 5(4), pages 297-310, October.
    27. Lin, Boqiang & Moubarak, Mohamed & Ouyang, Xiaoling, 2014. "Carbon dioxide emissions and growth of the manufacturing sector: Evidence for China," Energy, Elsevier, vol. 76(C), pages 830-837.
    28. Lin, Boqiang & Moubarak, Mohamed, 2014. "Mitigation potential of carbon dioxide emissions in the Chinese textile industry," Applied Energy, Elsevier, vol. 113(C), pages 781-787.
    29. Palanichamy, C. & Sundar Babu, N., 2005. "Second stage energy conservation experience with a textile industry," Energy Policy, Elsevier, vol. 33(5), pages 603-609, March.
    30. Lin, Boqiang & Xie, Chunping, 2013. "Estimation on oil demand and oil saving potential of China's road transport sector," Energy Policy, Elsevier, vol. 61(C), pages 472-482.
    31. Lin, Boqiang & Zhao, Hongli, 2016. "Technological progress and energy rebound effect in China׳s textile industry: Evidence and policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 173-181.
    32. Hang, Leiming & Tu, Meizeng, 2007. "The impacts of energy prices on energy intensity: Evidence from China," Energy Policy, Elsevier, vol. 35(5), pages 2978-2988, May.
    33. Yuan, Chaoqing & Liu, Sifeng & Wu, Junlong, 2009. "Research on energy-saving effect of technological progress based on Cobb-Douglas production function," Energy Policy, Elsevier, vol. 37(8), pages 2842-2846, August.
    34. David F. Hendry & Katarina Juselius, 2001. "Explaining Cointegration Analysis: Part II," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 75-120.
    35. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    36. Hu, Jin-Li & Kao, Chih-Hung, 2007. "Efficient energy-saving targets for APEC economies," Energy Policy, Elsevier, vol. 35(1), pages 373-382, January.
    37. Tang, Chor Foon & Tan, Eu Chye, 2013. "Exploring the nexus of electricity consumption, economic growth, energy prices and technology innovation in Malaysia," Applied Energy, Elsevier, vol. 104(C), pages 297-305.
    38. Lin, Boqiang & Jia, Zhijie, 2018. "Impact of quota decline scheme of emission trading in China: A dynamic recursive CGE model," Energy, Elsevier, vol. 149(C), pages 190-203.
    39. Saikkonen, Pentti, 1991. "Asymptotically Efficient Estimation of Cointegration Regressions," Econometric Theory, Cambridge University Press, vol. 7(1), pages 1-21, March.
    40. Belloumi, Mounir, 2009. "Energy consumption and GDP in Tunisia: Cointegration and causality analysis," Energy Policy, Elsevier, vol. 37(7), pages 2745-2753, July.
    41. An, Ning & Zhao, Weigang & Wang, Jianzhou & Shang, Duo & Zhao, Erdong, 2013. "Using multi-output feedforward neural network with empirical mode decomposition based signal filtering for electricity demand forecasting," Energy, Elsevier, vol. 49(C), pages 279-288.
    42. Lin, Boqiang & Moubarak, Mohamed, 2014. "Estimation of energy saving potential in China's paper industry," Energy, Elsevier, vol. 65(C), pages 182-189.
    43. Lin, Boqiang & Jia, Zhijie, 2017. "The impact of Emission Trading Scheme (ETS) and the choice of coverage industry in ETS: A case study in China," Applied Energy, Elsevier, vol. 205(C), pages 1512-1527.
    44. Hondroyiannis, George, 2004. "Estimating residential demand for electricity in Greece," Energy Economics, Elsevier, vol. 26(3), pages 319-334, May.
    45. Lin, Boqiang & Zhang, Li & Wu, Ya, 2012. "Evaluation of electricity saving potential in China's chemical industry based on cointegration," Energy Policy, Elsevier, vol. 44(C), pages 320-330.
    46. Hasanbeigi, Ali & Price, Lynn & Lu, Hongyou & Lan, Wang, 2010. "Analysis of energy-efficiency opportunities for the cement industry in Shandong Province, China: A case study of 16 cement plants," Energy, Elsevier, vol. 35(8), pages 3461-3473.
    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. Zhang, Dayong & Li, Jun & Ji, Qiang, 2020. "Does better access to credit help reduce energy intensity in China? Evidence from manufacturing firms," Energy Policy, Elsevier, vol. 145(C).
    2. Tian, Jiamian & Coreynen, Wim & Matthyssens, Paul & Shen, Lei, 2022. "Platform-based servitization and business model adaptation by established manufacturers," Technovation, Elsevier, vol. 118(C).
    3. Lin, Boqiang & Chen, Yu, 2019. "Will economic infrastructure development affect the energy intensity of China's manufacturing industry?," Energy Policy, Elsevier, vol. 132(C), pages 122-131.
    4. Liu, Yang & Dong, Kangyin & Wang, Jianda & Taghizadeh-Hesary, Farhad, 2023. "Towards sustainable development goals: Does common prosperity contradict carbon reduction?," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 70-88.
    5. Leonel Jorge Ribeiro Nunes & Radu Godina & João Carlos de Oliveira Matias, 2019. "Technological Innovation in Biomass Energy for the Sustainable Growth of Textile Industry," Sustainability, MDPI, vol. 11(2), pages 1-12, January.
    6. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    7. Clara Inés Pardo Martínez, 2009. "Energy use and energy efficiency development in the German and Colombian textile industries," Serie de Documentos en Economía y Violencia 6862, Centro de Investigaciones en Violencia, Instituciones y Desarrollo Económico (VIDE).
    8. Xiekui Zhang & Peiyao Liu & Hongfei Zhu, 2022. "The Impact of Industrial Intelligence on Energy Intensity: Evidence from China," Sustainability, MDPI, vol. 14(12), pages 1-16, June.
    9. A S M Monjurul Hasan & Mohammad Rokonuzzaman & Rashedul Amin Tuhin & Shah Md. Salimullah & Mahfuz Ullah & Taiyeb Hasan Sakib & Patrik Thollander, 2019. "Drivers and Barriers to Industrial Energy Efficiency in Textile Industries of Bangladesh," Energies, MDPI, vol. 12(9), pages 1-19, May.
    10. Lin, Boqiang & Bai, Rui, 2020. "Dynamic energy performance evaluation of Chinese textile industry," Energy, Elsevier, vol. 199(C).
    11. Abbas, Shahbaz & Chiang Hsieh, Lin-Han & Techato, Kuaanan, 2021. "Supply chain integrated decision model in order to synergize the energy system of textile industry from its resource waste," Energy, Elsevier, vol. 229(C).
    12. Chen, Yu & Lin, Boqiang, 2021. "How does infrastructure affect energy services?," Energy, Elsevier, vol. 231(C).
    13. Jian Xu & Binghan Wang, 2019. "Intellectual Capital Performance of the Textile Industry in Emerging Markets: A Comparison with China and South Korea," Sustainability, MDPI, vol. 11(8), pages 1-16, April.

    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. Wang, Xiaolei & Lin, Boqiang, 2016. "How to reduce CO2 emissions in China׳s iron and steel industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1496-1505.
    2. Lin, Boqiang & Wang, Xiaolei, 2014. "Promoting energy conservation in China's iron & steel sector," Energy, Elsevier, vol. 73(C), pages 465-474.
    3. Lin, Boqiang & Zhang, Guoliang, 2013. "Estimates of electricity saving potential in Chinese nonferrous metals industry," Energy Policy, Elsevier, vol. 60(C), pages 558-568.
    4. Gang Du & Chuanwang Sun, 2015. "Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China," Sustainability, MDPI, vol. 7(6), pages 1-25, June.
    5. Lin, Boqiang & Zhang, Li & Wu, Ya, 2012. "Evaluation of electricity saving potential in China's chemical industry based on cointegration," Energy Policy, Elsevier, vol. 44(C), pages 320-330.
    6. Lin, Boqiang & Moubarak, Mohamed, 2014. "Estimation of energy saving potential in China's paper industry," Energy, Elsevier, vol. 65(C), pages 182-189.
    7. Lin, Boqiang & Ouyang, Xiaoling, 2014. "Electricity demand and conservation potential in the Chinese nonmetallic mineral products industry," Energy Policy, Elsevier, vol. 68(C), pages 243-253.
    8. Lin, Boqiang & Wu, Ya & Zhang, Li, 2012. "Electricity saving potential of the power generation industry in China," Energy, Elsevier, vol. 40(1), pages 307-316.
    9. Lin, Boqiang & Wang, Ailun, 2015. "Estimating energy conservation potential in China's commercial sector," Energy, Elsevier, vol. 82(C), pages 147-156.
    10. Lin, Boqiang & Long, Houyin, 2014. "Promoting carbon emissions reduction in China's chemical process industry," Energy, Elsevier, vol. 77(C), pages 822-830.
    11. Ouyang, Xiaoling & Lin, Boqiang, 2015. "An analysis of the driving forces of energy-related carbon dioxide emissions in China’s industrial sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 838-849.
    12. Lin, Boqiang & Chen, Yufang, 2019. "Does electricity price matter for innovation in renewable energy technologies in China?," Energy Economics, Elsevier, vol. 78(C), pages 259-266.
    13. Lin, Boqiang & Bai, Rui, 2020. "Dynamic energy performance evaluation of Chinese textile industry," Energy, Elsevier, vol. 199(C).
    14. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5, July-Dece.
    15. Lin, Boqiang & Long, Houyin, 2014. "How to promote energy conservation in China’s chemical industry," Energy Policy, Elsevier, vol. 73(C), pages 93-102.
    16. Lin, Boqiang & Chen, Yu, 2020. "Will land transport infrastructure affect the energy and carbon dioxide emissions performance of China’s manufacturing industry?," Applied Energy, Elsevier, vol. 260(C).
    17. Miguel Ángel Mendoza González, 2020. "Sensibilidad y asimetrías ante choques de ingreso en el consumo privado de México, 1995-2017. (Sensitivity and asymmetries of income shocks in Mexico's private consumption, 1995-2017)," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 21-58, May.
    18. Solarin, Sakiru Adebola & Shahbaz, Muhammad, 2013. "Trivariate causality between economic growth, urbanisation and electricity consumption in Angola: Cointegration and causality analysis," Energy Policy, Elsevier, vol. 60(C), pages 876-884.
    19. Balsalobre-Lorente, Daniel & Bekun, Festus Victor & Etokakpan, Mfonobong Udom & Driha, Oana M., 2019. "A road to enhancements in natural gas use in Iran: A multivariate modelling approach," Resources Policy, Elsevier, vol. 64(C).
    20. Jason Allen & Robert Amano & David P. Byrne & Allan W. Gregory, 2009. "Canadian city housing prices and urban market segmentation," Canadian Journal of Economics, Canadian Economics Association, vol. 42(3), pages 1132-1149, August.

    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:energy:v:161:y:2018:i:c:p:859-869. 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/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.