IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v73y2021ics0301420721001446.html
   My bibliography  Save this article

Efficiency assessment of coal mine use and land restoration: Considering climate change and income differences

Author

Listed:
  • Chiu, Yung-ho
  • Huang, Kuei-Ying
  • Chang, Tzu-Han
  • Lin, Tai-Yu

Abstract

Coal burning is still the main source of power generation in many Asian countries and is also the biggest cause of climate change. This research thus employs meta dynamic two-stage SBM (slack-based measure) under the exogenous model to examine 24 provinces in China as the research object. The first stage evaluates the efficiency of coal mining, taking employment in the coal industry and fixed assets in the mining industry as inputs, the development of non-oil and gas mineral resources a desirable output, and land damage as undesirable output and link. The second stage assesses the efficiency of land recovery, using land recovery funding as the input and recovery area as the output, and considers the climate change effect. The contribution herein is to discuss the degree of land destruction and the efficiency of land recovery through the different economic environments of different provinces and to divide the two groups by GDP. We also introduce high and low temperature days as exogenous variables to highlight the impact of climate change factors and to expose efficiency issues that may be underestimated. The results are as follows. (1) The efficiency value of the coal mining stage is higher than that of the land recovery stage, showing that China still pays more attention to economic benefits and ignores environmental responsibility issues. (2) More than 90% of China's provinces have coal mining expertise, but 70% of the provinces have low land recovery performance. (3) Eight provinces did not follow the Atmospheric Pollution Prevention Action Plan (APCP), the efficiency of coal mining deteriorated after the implementation of the policy. (4) Before the implementation of the APCP, land recovery in high GDP provinces was less efficient than in low GDP provinces. (5) Activating the APCP policy does not help technology upgrade. (6) The APCP policy caused the provinces to misevaluate their investments in fixed assets and misdirected their decisions on land recovery funding. However, the efficiency of land recovery after the implement of APCP was better. (7) Neglecting climatic factors causes serious errors in coal mine efficiency.

Suggested Citation

  • Chiu, Yung-ho & Huang, Kuei-Ying & Chang, Tzu-Han & Lin, Tai-Yu, 2021. "Efficiency assessment of coal mine use and land restoration: Considering climate change and income differences," Resources Policy, Elsevier, vol. 73(C).
    • Handle: RePEc:eee:jrpoli:v:73:y:2021:i:c:s0301420721001446
    DOI: 10.1016/j.resourpol.2021.102130
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420721001446
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2021.102130?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. Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity and intermediate products: A frontier approach," Economics Letters, Elsevier, vol. 50(1), pages 65-70, January.
    2. Qi, Xiaoyan & Guo, Pibin & Guo, Yanshan & Liu, Xiuli & Zhou, Xijun, 2020. "Understanding energy efficiency and its drivers: An empirical analysis of China’s 14 coal intensive industries," Energy, Elsevier, vol. 190(C).
    3. Zhang, Yijun & Song, Yi, 2020. "Unified efficiency of coal mining enterprises in China: An analysis based on meta-frontier non-radial directional distance functions," Resources Policy, Elsevier, vol. 65(C).
    4. Wu, Peng & Wang, Yiqing & Chiu, Yung-ho & Li, Ying & Lin, Tai-Yu, 2019. "Production efficiency and geographical location of Chinese coal enterprises - undesirable EBM DEA," Resources Policy, Elsevier, vol. 64(C).
    5. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    6. Jiro Nemoto & Mika Goto, 2003. "Measurement of Dynamic Efficiency in Production: An Application of Data Envelopment Analysis to Japanese Electric Utilities," Journal of Productivity Analysis, Springer, vol. 19(2), pages 191-210, April.
    7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    8. Wang, Wensheng & Zhang, Chengyi, 2018. "Evaluation of relative technological innovation capability: Model and case study for China's coal mine," Resources Policy, Elsevier, vol. 58(C), pages 144-149.
    9. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    10. Kaoru Tone & Miki Tsutsui, 2014. "Slacks-Based Network DEA," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 231-259, Springer.
    11. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    12. Nemoto, Jiro & Goto, Mika, 1999. "Dynamic data envelopment analysis: modeling intertemporal behavior of a firm in the presence of productive inefficiencies," Economics Letters, Elsevier, vol. 64(1), pages 51-56, July.
    13. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    14. Du, Limin & Hanley, Aoife & Zhang, Ning, 2016. "Environmental technical efficiency, technology gap and shadow price of coal-fuelled power plants in China: A parametric meta-frontier analysis," Resource and Energy Economics, Elsevier, vol. 43(C), pages 14-32.
    15. Du, Limin & Mao, Jie, 2015. "Estimating the environmental efficiency and marginal CO2 abatement cost of coal-fired power plants in China," Energy Policy, Elsevier, vol. 85(C), pages 347-356.
    16. Wang, Ning & Li, Heng & Liu, Gengyuan & Meng, Fanxin & Shan, Shaolei & Wang, Zongshui, 2018. "Developing a more comprehensive energy efficiency index for coal production: Indicators, methods and case study," Energy, Elsevier, vol. 162(C), pages 944-952.
    17. Wang, Zhiping & Feng, Chao & Chen, Jinyu & Huang, Jianbai, 2017. "The driving forces of material use in China: An index decomposition analysis," Resources Policy, Elsevier, vol. 52(C), pages 336-348.
    18. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    19. Wang, Ning & Wen, Zongguo & Liu, Mingqi & Guo, Jie, 2016. "Constructing an energy efficiency benchmarking system for coal production," Applied Energy, Elsevier, vol. 169(C), pages 301-308.
    20. Kasap, Yaşar & Şensöğüt, Cem & Ören, Özer, 2020. "Efficiency change of coal used for energy production in Turkey," Resources Policy, Elsevier, vol. 65(C).
    21. Chen, Chien-Ming, 2009. "A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks," European Journal of Operational Research, Elsevier, vol. 194(3), pages 687-699, May.
    22. Park, K. Sam & Park, Kwangtae, 2009. "Measurement of multiperiod aggregative efficiency," European Journal of Operational Research, Elsevier, vol. 193(2), pages 567-580, March.
    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. Anggi Putri Kurniadi & Hasdi Aimon & Zamroni Salim & Ragimun Ragimun & Adang Sonjaya & Sigit Setiawan & Viktor Siagian & Lokot Zein Nasution & R Nurhidajat & Mutaqin Mutaqin & Joko Sabtohadi, 2024. "Analysis of Existing and Forecasting for Coal and Solar Energy Consumption on Climate Change in Asia Pacific: New Evidence for Sustainable Development Goals," International Journal of Energy Economics and Policy, Econjournals, vol. 14(4), pages 352-359, July.
    2. Xu, Jiuping & Shu, Kejing & Wang, Fengjuan & Yang, Guocan, 2024. "Bi-level multi-objective distribution strategy integrating the permit trading scheme towards coal production capacity layout optimization: Case study from China," Resources Policy, Elsevier, vol. 91(C).
    3. Wang, Zongrun & Cao, Xuxin & Ren, Xiaohang & Taghizadeh-Hesary, Farhad, 2024. "Can digital transformation affect coal utilization efficiency in China? Evidence from spatial econometric analyses," Resources Policy, Elsevier, vol. 91(C).
    4. Jin, Haifeng, 2023. "Analyzing factors and resource policymaking options for sustainable resource management and carbon neutrality in mining industry: Empirical study in China," Resources Policy, Elsevier, vol. 86(PB).
    5. Wang, Miao & Feng, Chao, 2023. "Measuring capacity utilization under the constraints of energy consumption and CO2 emissions using meta-frontier DEA: A case of China's non-ferrous metal industries," Resources Policy, Elsevier, vol. 80(C).
    6. Wei Xu & Jiahui Yi & Jinhua Cheng, 2022. "The Heterogeneity of High-Quality Economic Development in China’s Mining Cities: A Meta Frontier Function," IJERPH, MDPI, vol. 19(11), pages 1-23, 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. Li, Ying & Chiu, Yung-ho & Lin, Tai-Yu, 2019. "Coal production efficiency and land destruction in China's coal mining industry," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    2. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    3. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    4. Fang-Rong Ren & Ze Tian & Yu-Ting Shen & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Energy, CO 2 , and AQI Efficiency and Improvement of the Yangtze River Economic Belt," Energies, MDPI, vol. 12(4), pages 1-17, February.
    5. Aparicio, Juan & Kapelko, Magdalena, 2019. "Accounting for slacks to measure dynamic inefficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 278(2), pages 463-471.
    6. Wanke, Peter & Tsionas, Mike G. & Chen, Zhongfei & Moreira Antunes, Jorge Junio, 2020. "Dynamic network DEA and SFA models for accounting and financial indicators with an analysis of super-efficiency in stochastic frontiers: An efficiency comparison in OECD banking," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 456-468.
    7. Xiong, Xi & Yang, Guo-liang & Guan, Zhong-cheng, 2018. "Assessing R&D efficiency using a two-stage dynamic DEA model: A case study of research institutes in the Chinese Academy of Sciences," Journal of Informetrics, Elsevier, vol. 12(3), pages 784-805.
    8. Hsiao-Yin Chen & Chin-wei Huang & Yung-Ho Chiu, 2017. "An intertemporal efficiency and technology measurement for tourist hotel," Journal of Productivity Analysis, Springer, vol. 48(1), pages 85-96, August.
    9. Yu-Chuan Chen & Yung-Ho Chiu & Tzu-Han Chang & Tai-Yu Lin, 2023. "Sustainable Development, Government Efficiency, and People’s Happiness," Journal of Happiness Studies, Springer, vol. 24(4), pages 1549-1578, April.
    10. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    11. Zhen Shi & Yingju Wu & Yung-ho Chiu & Fengping Wu & Changfeng Shi, 2020. "Dynamic Linkages among Mining Production and Land Rehabilitation Efficiency in China," Land, MDPI, vol. 9(3), pages 1-25, March.
    12. Mergoni, Anna & Soncin, Mara & Agasisti, Tommaso, 2023. "The effect of ICT on schools’ efficiency: Empirical evidence on 23 European countries," Omega, Elsevier, vol. 119(C).
    13. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    14. Ying Li & Yung-ho Chiu & Tai-Yu Lin, 2019. "Research on New and Traditional Energy Sources in OECD Countries," IJERPH, MDPI, vol. 16(7), pages 1-21, March.
    15. Mohammad Nourani & Qian Long Kweh & Irene Wei Kiong Ting & Wen-Min Lu & Anna Strutt, 2022. "Evaluating traditional, dynamic and network business models: an efficiency-based study of Chinese insurance companies," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(4), pages 905-943, October.
    16. Alperovych, Yan & Amess, Kevin & Wright, Mike, 2013. "Private equity firm experience and buyout vendor source: What is their impact on efficiency?," European Journal of Operational Research, Elsevier, vol. 228(3), pages 601-611.
    17. Liang-Han Ma & Jin-Chi Hsieh & Ying Li & Yung-Ho Chiu, 2021. "Evaluating Efficiency Change in Taiwan’s Financial Industry," SAGE Open, , vol. 11(2), pages 21582440211, April.
    18. Zhang, Ning & Zhao, Yu & Wang, Na, 2022. "Is China's energy policy effective for power plants? Evidence from the 12th Five-Year Plan energy saving targets," Energy Economics, Elsevier, vol. 112(C).
    19. Chenjun Zhang & Rui Hua & Zhen Shi & Yung‐ho Chiu & Shijiong Qin & Xinrui Sun, 2021. "Study on water resources consumption and environmental pollution of China's provinces under different economic development levels," Natural Resources Forum, Blackwell Publishing, vol. 45(3), pages 305-325, August.
    20. Xianhua Tan & Danting Zheng & Yuanyuan Zhu & Sanggyun Na, 2023. "The Financing Efficiency of China’s Industrial Listed Enterprises Based on the Dynamic–Network SBM Model," Sustainability, MDPI, vol. 15(6), pages 1-19, March.

    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:jrpoli:v:73:y:2021:i:c:s0301420721001446. 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/inca/30467 .

    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.