IDEAS home Printed from https://ideas.repec.org/p/csc/cerisp/201209.html
   My bibliography  Save this paper

Comparing green performances of Italian and German firms

Author

Abstract

This paper analyses the environmental efficiency of a sample of chemical firms located in Italy and Germany, which are included in the European Pollution Emission and Transfer Register (E-PRTR). The adoption of a common set of standards can open important way to compare economical and ecological performances of firms which must follow the same formal rule, but operating in different countries. The Directional Distance Function (DDF) approach is here applied to obtain global efficiency scores able to consider pollution in computations: emissions generally increase between 2004 and 2007, with a worse performance of Italian ?rms. Eco-ef?ciency indicators partially slim down that evidence considering both turnover and input usage, underlining a reduction of average inef?ciencies over time. From a dynamic viewpoint empirical ?ndings shows a most favourable trends in environmental TFP growth for German ?rms.

Suggested Citation

  • Alessandro Manello, 2012. "Comparing green performances of Italian and German firms," CERIS Working Paper 201209, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
    • Handle: RePEc:csc:cerisp:201209
    as

    Download full text from publisher

    File URL: https://www.byterfly.eu/islandora/object/librib:345098
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rolf Färe & Shawna Grosskopf & Carl A Pasurka, Jr., 2001. "Accounting for Air Pollution Emissions in Measures of State Manufacturing Productivity Growth," Journal of Regional Science, Wiley Blackwell, vol. 41(3), pages 381-409, August.
    2. Fare, Rolf, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    3. Fare, Rolf & Grosskopf, Shawna & Weber, William L., 2006. "Shadow prices and pollution costs in U.S. agriculture," Ecological Economics, Elsevier, vol. 56(1), pages 89-103, January.
    4. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    5. Picazo-Tadeo, Andres J. & Reig-Martinez, Ernest & Hernandez-Sancho, Francesc, 2005. "Directional distance functions and environmental regulation," Resource and Energy Economics, Elsevier, vol. 27(2), pages 131-142, June.
    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. Ke Wang & Yujiao Xian & Chia-Yen Lee & Yi-Ming Wei & Zhimin Huang, 2019. "On selecting directions for directional distance functions in a non-parametric framework: a review," Annals of Operations Research, Springer, vol. 278(1), pages 43-76, July.
    2. Manello, Alessandro, 2017. "Productivity growth, environmental regulation and win–win opportunities: The case of chemical industry in Italy and Germany," European Journal of Operational Research, Elsevier, vol. 262(2), pages 733-743.
    3. Chen, Po-Chi & Yu, Ming-Miin & Chang, Ching-Cheng & Hsu, Shih-Hsun & Managi, Shunsuke, 2015. "The enhanced Russell-based directional distance measure with undesirable outputs: Numerical example considering CO2 emissions," Omega, Elsevier, vol. 53(C), pages 30-40.
    4. Margaréta Halická & Mária Trnovská, 2018. "Negative features of hyperbolic and directional distance models for technologies with undesirable outputs," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 887-907, December.
    5. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    6. Trinks, Arjan & Mulder, Machiel & Scholtens, Bert, 2020. "An Efficiency Perspective on Carbon Emissions and Financial Performance," Ecological Economics, Elsevier, vol. 175(C).
    7. Li, Ke & Lin, Boqiang, 2015. "Measuring green productivity growth of Chinese industrial sectors during 1998–2011," China Economic Review, Elsevier, vol. 36(C), pages 279-295.
    8. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Shadman, Foroogh, 2014. "Power industry restructuring and eco-efficiency changes: A new slacks-based model in Malmquist–Luenberger Index measurement," Energy Policy, Elsevier, vol. 68(C), pages 132-145.
    9. Hoang, Viet-Ngu & Rao, D.S. Prasada, 2010. "Measuring and decomposing sustainable efficiency in agricultural production: A cumulative exergy balance approach," Ecological Economics, Elsevier, vol. 69(9), pages 1765-1776, July.
    10. Wei, Chu & Löschel, Andreas & Liu, Bing, 2015. "Energy-saving and emission-abatement potential of Chinese coal-fired power enterprise: A non-parametric analysis," Energy Economics, Elsevier, vol. 49(C), pages 33-43.
    11. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    12. Chung, Yeimin & Heshmati, Almas, 2013. "Measurement of Environmentally Sensitive Productivity Growth in Korean Industries," IZA Discussion Papers 7235, Institute of Labor Economics (IZA).
    13. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    14. Macpherson, Alexander J. & Principe, Peter P. & Smith, Elizabeth R., 2010. "A directional distance function approach to regional environmental-economic assessments," Ecological Economics, Elsevier, vol. 69(10), pages 1918-1925, August.
    15. Yao, Xin & Guo, Chengwen & Shao, Shuai & Jiang, Zhujun, 2016. "Total-factor CO2 emission performance of China’s provincial industrial sector: A meta-frontier non-radial Malmquist index approach," Applied Energy, Elsevier, vol. 184(C), pages 1142-1153.
    16. Oh, Dong-hyun & Heshmati, Almas, 2010. "A sequential Malmquist-Luenberger productivity index: Environmentally sensitive productivity growth considering the progressive nature of technology," Energy Economics, Elsevier, vol. 32(6), pages 1345-1355, November.
    17. 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.
    18. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Slacks-based efficiency measures for modeling environmental performance," Ecological Economics, Elsevier, vol. 60(1), pages 111-118, November.
    19. Gang Tian & Jian Shi & Licheng Sun & Xingle Long & Benhai Guo, 2017. "Dynamic changes in the energy–carbon performance of Chinese transportation sector: a meta-frontier non-radial directional distance function approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(2), pages 585-607, November.
    20. Subhash C. Ray & Kankana Mukherjee, 2007. "Efficiency in Managing the Environment and the Opportunity Cost of Pollution Abatement," Working papers 2007-09, University of Connecticut, Department of Economics.

    More about this item

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects

    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:csc:cerisp:201209. 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: Anna Perin or Giancarlo Birello (email available below). General contact details of provider: https://edirc.repec.org/data/cerisit.html .

    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.