IDEAS home Printed from https://ideas.repec.org/a/eee/retrec/v90y2021ics0739885921000925.html
   My bibliography  Save this article

Investigating the Profit Pollution Abatement Costs difference before and after the “Carbon neutral growth from 2020” strategy was proposed

Author

Listed:
  • Cui, Qiang
  • Li, Xin-yi

Abstract

Based on the empirical data of 22 airlines during 2014–2019, the paper studies the impact of the introduction of Carbon neutral growth from 2020 (CNG2020) strategy on airlines' pollution abatement costs. This research considers the prices of inputs and outputs, and proposes a new Profit Pollution Abatement Costs (PPAC) index to ensure that the calculated Net Pollution Abatement Costs (NPAC) index is a cost index rather than a physical index, and a two-stage network environment production function is established to discuss the NPAC differences before and after the CNG2020 strategy was proposed. The main findings are: (a)The introduction of CNG2020 strategy has had a certain degree of impact on the airlines’ net pollution abatement costs. (b)All Nippon Airways has the largest NPAC among the 22 airlines, while Delta Air Lines and Finnair have excellent pollution abatement performance during 2014–2019. (c)Aviation carbon emissions are closely related to jet fuel consumption and route distance.

Suggested Citation

  • Cui, Qiang & Li, Xin-yi, 2021. "Investigating the Profit Pollution Abatement Costs difference before and after the “Carbon neutral growth from 2020” strategy was proposed," Research in Transportation Economics, Elsevier, vol. 90(C).
  • Handle: RePEc:eee:retrec:v:90:y:2021:i:c:s0739885921000925
    DOI: 10.1016/j.retrec.2021.101120
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0739885921000925
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.retrec.2021.101120?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. Sarica, Kemal & Tyner, Wallace E., 2013. "Alternative policy impacts on US GHG emissions and energy security: A hybrid modeling approach," Energy Economics, Elsevier, vol. 40(C), pages 40-50.
    2. Adel Hatami-Marbini & Madjid Tavana & Ali Emrouznejad & Saber Saati, 2012. "Efficiency measurement in fuzzy additive data envelopment analysis," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 10(1), pages 1-20.
    3. 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.
    4. 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.
    5. Shahrokhi Shahraki, Hamed & Bachmann, Chris, 2019. "Integrating a Computable General Equilibrium model with empirically calibrated transportation models for border crossing investment analysis," Research in Transportation Economics, Elsevier, vol. 78(C).
    6. Zhang, Xu & Qi, Tian-yu & Ou, Xun-min & Zhang, Xi-liang, 2017. "The role of multi-region integrated emissions trading scheme: A computable general equilibrium analysis," Applied Energy, Elsevier, vol. 185(P2), pages 1860-1868.
    7. Cui, Qiang & Li, Ye & Lin, Jing-ling, 2018. "Pollution abatement costs change decomposition for airlines: An analysis from a dynamic perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 96-107.
    8. Li, Ye & Wang, Yan-zhang & Cui, Qiang, 2015. "Evaluating airline efficiency: An application of Virtual Frontier Network SBM," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 1-17.
    9. Ke Wang, 2016. "Potential carbon emission abatement cost recovery from carbon emission trading in China: an estimation of industry sector," CEEP-BIT Working Papers 94, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    10. Li, Ye & Cui, Qiang, 2017. "Carbon neutral growth from 2020 strategy and airline environmental inefficiency: A Network Range Adjusted Environmental Data Envelopment Analysis," Applied Energy, Elsevier, vol. 199(C), pages 13-24.
    11. Andreana, Gianmarco & Gualini, Andrea & Martini, Gianmaria & Porta, Flavio & Scotti, Davide, 2021. "The disruptive impact of COVID-19 on air transportation: An ITS econometric analysis," Research in Transportation Economics, Elsevier, vol. 90(C).
    12. Henning Jensen & Marcus Keogh-Brown & Richard Smith & Zaid Chalabi & Alan Dangour & Mike Davies & Phil Edwards & Tara Garnett & Moshe Givoni & Ulla Griffiths & Ian Hamilton & James Jarrett & Ian Rober, 2013. "The importance of health co-benefits in macroeconomic assessments of UK Greenhouse Gas emission reduction strategies," Climatic Change, Springer, vol. 121(2), pages 223-237, November.
    13. Cui, Qiang & Li, Ye & Wei, Yi-Ming, 2017. "Exploring the impacts of EU ETS on the pollution abatement costs of European airlines: An application of Network Environmental Production Function," Transport Policy, Elsevier, vol. 60(C), pages 131-142.
    14. Li, Ye & Wang, Yan-zhang & Cui, Qiang, 2016. "Has airline efficiency affected by the inclusion of aviation into European Union Emission Trading Scheme? Evidences from 22 airlines during 2008–2012," Energy, Elsevier, vol. 96(C), pages 8-22.
    15. He, Xiaoping, 2015. "Regional differences in China's CO2 abatement cost," Energy Policy, Elsevier, vol. 80(C), pages 145-152.
    16. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    17. Chen, Wenying & Wu, Zongxin & He, Jiankun & Gao, Pengfei & Xu, Shaofeng, 2007. "Carbon emission control strategies for China: A comparative study with partial and general equilibrium versions of the China MARKAL model," Energy, Elsevier, vol. 32(1), pages 59-72.
    18. HATAMI-MARBINI, Adel & TAVANA, Madjid & EMROUZNEJAD, Ali & SAATI, Saber, 2012. "Efficiency measurement in fuzzy additive data envelopment analysis," LIDAM Reprints CORE 2393, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Mallikarjun, Sreekanth, 2015. "Efficiency of US airlines: A strategic operating model," Journal of Air Transport Management, Elsevier, vol. 43(C), pages 46-56.
    20. Amorim, Filipa & Pina, André & Gerbelová, Hana & Pereira da Silva, Patrícia & Vasconcelos, Jorge & Martins, Victor, 2014. "Electricity decarbonisation pathways for 2050 in Portugal: A TIMES (The Integrated MARKAL-EFOM System) based approach in closed versus open systems modelling," Energy, Elsevier, vol. 69(C), pages 104-112.
    Full references (including those not matched with items on IDEAS)

    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. Cui, Qiang & Li, Ye & Wei, Yi-Ming, 2017. "Exploring the impacts of EU ETS on the pollution abatement costs of European airlines: An application of Network Environmental Production Function," Transport Policy, Elsevier, vol. 60(C), pages 131-142.
    2. Cui, Qiang, 2019. "Investigating the airlines emission reduction through carbon trading under CNG2020 strategy via a Network Weak Disposability DEA," Energy, Elsevier, vol. 180(C), pages 763-771.
    3. Li, Ye & Cui, Qiang, 2018. "Investigating the role of cooperation in the GHG abatement costs of airlines under CNG2020 strategy via a DEA cross PAC model," Energy, Elsevier, vol. 161(C), pages 725-736.
    4. Cui, Qiang & Li, Ye & Lin, Jing-ling, 2018. "Pollution abatement costs change decomposition for airlines: An analysis from a dynamic perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 96-107.
    5. Cui, Qiang & Jin, Zi-yin, 2020. "Airline environmental efficiency measures considering negative data: An application of a modified network Modified Slacks-based measure model," Energy, Elsevier, vol. 207(C).
    6. Cui, Qiang & Lin, Jing-ling & Jin, Zi-yin, 2020. "Evaluating airline efficiency under “Carbon Neutral Growth from 2020” strategy through a Network Interval Slack-Based Measure," Energy, Elsevier, vol. 193(C).
    7. Cui, Qiang & Li, Ye, 2017. "Airline efficiency measures under CNG2020 strategy: An application of a Dynamic By-production model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 130-143.
    8. Losa, Eduardo Tola & Arjomandi, Amir & Hervé Dakpo, K. & Bloomfield, Jason, 2020. "Efficiency comparison of airline groups in Annex 1 and non-Annex 1 countries: A dynamic network DEA approach," Transport Policy, Elsevier, vol. 99(C), pages 163-174.
    9. Cui, Qiang & Li, Ye, 2018. "Airline dynamic efficiency measures with a Dynamic RAM with unified natural & managerial disposability," Energy Economics, Elsevier, vol. 75(C), pages 534-546.
    10. Li, Ye & Cui, Qiang, 2017. "Carbon neutral growth from 2020 strategy and airline environmental inefficiency: A Network Range Adjusted Environmental Data Envelopment Analysis," Applied Energy, Elsevier, vol. 199(C), pages 13-24.
    11. Joe Zhu, 2022. "DEA under big data: data enabled analytics and network data envelopment analysis," Annals of Operations Research, Springer, vol. 309(2), pages 761-783, February.
    12. Ben Lahouel, Béchir & Taleb, Lotfi & Ben Zaied, Younes & Managi, Shunsuke, 2022. "Does primary stakeholder management improve competitiveness? A dynamic network non-parametric frontier approach," Economic Modelling, Elsevier, vol. 116(C).
    13. Cui, Qiang & Li, Ye & Yu, Chen-lu & Wei, Yi-Ming, 2016. "Evaluating energy efficiency for airlines: An application of Virtual Frontier Dynamic Slacks Based Measure," Energy, Elsevier, vol. 113(C), pages 1231-1240.
    14. Khezrimotlagh, Dariush & Kaffash, Sepideh & Zhu, Joe, 2022. "U.S. airline mergers’ performance and productivity change," Journal of Air Transport Management, Elsevier, vol. 102(C).
    15. Cui, Qiang & Li, Ye, 2020. "A cross efficiency distinguishing method to explore the cooperation degree in dynamic airline environmental efficiency," Transport Policy, Elsevier, vol. 99(C), pages 31-43.
    16. Arjomandi, Amir & Dakpo, K. Hervé & Seufert, Juergen Heinz, 2018. "Have Asian airlines caught up with European Airlines? A by-production efficiency analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 389-403.
    17. Cui, Qiang & Arjomandi, Amir, 2021. "Airline energy efficiency measures based on an epsilon-based Range-Adjusted Measure model," Energy, Elsevier, vol. 217(C).
    18. Xu, Xin & Cui, Qiang, 2017. "Evaluating airline energy efficiency: An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure," Energy, Elsevier, vol. 122(C), pages 274-286.
    19. Cui, Qiang & Wei, Yi-Ming & Li, Ye, 2016. "Exploring the impacts of the EU ETS emission limits on airline performance via the Dynamic Environmental DEA approach," Applied Energy, Elsevier, vol. 183(C), pages 984-994.
    20. Li, Ye & Cui, Qiang, 2018. "Airline efficiency with optimal employee allocation: An Input-shared Network Range Adjusted Measure," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 150-162.

    More about this item

    Keywords

    Network environmental production function; Pollution abatement costs; Profit PAC; Airline; CNG2020 strategy;
    All these keywords.

    JEL classification:

    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation
    • L98 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Government Policy

    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:retrec:v:90:y:2021:i:c:s0739885921000925. 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/wps/find/journaldescription.cws_home/620614/description#description .

    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.