IDEAS home Printed from https://ideas.repec.org/p/ags/iaae21/315100.html
   My bibliography  Save this paper

Environmental Efficiency Measurement When Producers Control Pollutants Under Heterogeneous Conditions: A Generalization of the Materials Balance Approach

Author

Listed:
  • Eder, Andreas

Abstract

This article provides a generalization of the materials balance-based production model introduced by Coelli et al. (2007). Based on this, some new environmental efficiency (EE) measures are presented. The Coelli et al. (2007) EE measure and its extension by Rødseth (2016) produce biased efficiency estimates if the material flow coefficients (MFCs) are heterogeneous across decision-making units and non-discretionary. Furthermore, the Coelli et al. (2007) measure fails to reward emission reductions by emission control. To overcome these shortcomings, this paper proposes production models which allow for heterogeneous MFCs reflecting differences of external environmental factors or non-controllable heterogeneities in inputs and outputs, and which properly take into account emission abatement activities. Based on this, EE measures are provided and decomposed into (i) a part reflecting emission control efficiency (ECE), (ii) a part measuring material input efficiency (MIE), and (iii) a part reflecting the efficient allocation between material and non-material inputs (environmental allocative efficiency, EAE). The approach is illustrated by an empirical application to arable farming in Austria utilizing data from 90 farms for the year 2011. Soil erosion is considered an undesirable output and land a material input. The average EE, ECE, MIE, and EAE are 0.53, 0.96, 0.69, and 0.79, respectively. The results indicate that actual output can be potentially achieved with 47% less soil loss. Most of the potential to improve EE is due to differences in MIE and EAE. Removing inefficiencies in the implementation of existing, subsidized erosion controls allows soil loss to be reduced by 4%.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Eder, Andreas, 2021. "Environmental Efficiency Measurement When Producers Control Pollutants Under Heterogeneous Conditions: A Generalization of the Materials Balance Approach," 2021 Conference, August 17-31, 2021, Virtual 315100, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae21:315100
    DOI: 10.22004/ag.econ.315100
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/315100/files/0-0_Paper_18751_handout_212_0.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.315100?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ruggiero, John, 1998. "Non-discretionary inputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 111(3), pages 461-469, December.
    2. Graves, A.R. & Morris, J. & Deeks, L.K. & Rickson, R.J. & Kibblewhite, M.G. & Harris, J.A. & Farewell, T.S. & Truckle, I., 2015. "The total costs of soil degradation in England and Wales," Ecological Economics, Elsevier, vol. 119(C), pages 399-413.
    3. Trung Thanh Nguyen & Viet-Ngu Hoang & Bumsuk Seo, 2012. "Cost and environmental efficiency of rice farms in South Korea," Agricultural Economics, International Association of Agricultural Economists, vol. 43(4), pages 369-378, July.
    4. Hampf, Benjamin, 2018. "Measuring Inefficiency in the Presence of Bad Outputs: Does the Disposability Assumption Matter?," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 110815, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Viet-Ngu Hoang & Mohammad Alauddin, 2012. "Input-Orientated Data Envelopment Analysis Framework for Measuring and Decomposing Economic, Environmental and Ecological Efficiency: An Application to OECD Agriculture," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 51(3), pages 431-452, March.
    6. Rolf Färe & Shawna Grosskopf, 2003. "Nonparametric Productivity Analysis with Undesirable Outputs: Comment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 1070-1074.
    7. Eder, Andreas & Salhofer, Klaus & Scheichel, Eva, 2021. "Land tenure, soil conservation, and farm performance: An eco-efficiency analysis of Austrian crop farms," Ecological Economics, Elsevier, vol. 180(C).
    8. 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.
    9. Mercedes Beltrán-Esteve & José Gómez-Limón & Andrés Picazo-Tadeo & Ernest Reig-Martínez, 2014. "A metafrontier directional distance function approach to assessing eco-efficiency," Journal of Productivity Analysis, Springer, vol. 41(1), pages 69-83, February.
    10. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2019. "Environmental efficiency measurement with heterogeneous input quality: A nonparametric analysis of U.S. power plants," Energy Economics, Elsevier, vol. 81(C), pages 610-625.
    11. Pethig, Rudiger, 2006. "Non-linear production, abatement, pollution and materials balance reconsidered," Journal of Environmental Economics and Management, Elsevier, vol. 51(2), pages 185-204, March.
    12. Benjamin Hampf & Kenneth Løvold Rødseth, 2017. "Optimal profits under environmental regulation: the benefits from emission intensity averaging," Annals of Operations Research, Springer, vol. 255(1), pages 367-390, August.
    13. Peter Bogetoft & Lars Otto, 2011. "Benchmarking with DEA, SFA, and R," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7961-2, December.
    14. Amer Ait Sidhoum & Teresa Serra & Laure Latruffe, 2020. "Measuring sustainability efficiency at farm level: a data envelopment analysis approach [Economic and environmental efficiency of district heating plants]," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 47(1), pages 200-225.
    15. Fare, Rolf & Grosskopf, Shawna, 2004. "Modeling undesirable factors in efficiency evaluation: Comment," European Journal of Operational Research, Elsevier, vol. 157(1), pages 242-245, August.
    16. Ruggiero, John, 1996. "On the measurement of technical efficiency in the public sector," European Journal of Operational Research, Elsevier, vol. 90(3), pages 553-565, May.
    17. Hoang, Viet-Ngu & Coelli, Tim, 2011. "Measurement of agricultural total factor productivity growth incorporating environmental factors: A nutrients balance approach," Journal of Environmental Economics and Management, Elsevier, vol. 62(3), pages 462-474.
    18. Hampf, Benjamin & Rodseth, Kenneth, 2017. "Optimal Profits under Environmental Regulation: The Benefits from Emission Intesity Averaging," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 92492, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    19. Bostian, Moriah & Färe, Rolf & Grosskopf, Shawna & Lundgren, Tommy, 2016. "Environmental investment and firm performance: A network approach," Energy Economics, Elsevier, vol. 57(C), pages 243-255.
    20. Hoang, Viet-Ngu & Nguyen, Trung Thanh, 2013. "Analysis of environmental efficiency variations: A nutrient balance approach," Ecological Economics, Elsevier, vol. 86(C), pages 37-46.
    21. Bostian, Moriah & Färe, Rolf & Grosskopf, Shawna & Lundgren, Tommy, 2019. "Prevention or cure? Abatement efficiency in a network technology," CERE Working Papers 2019:11, CERE - the Center for Environmental and Resource Economics.
    22. Benjamin Hampf, 2014. "Separating environmental efficiency into production and abatement efficiency: a nonparametric model with application to US power plants," Journal of Productivity Analysis, Springer, vol. 41(3), pages 457-473, June.
    23. Benjamin Hampf, 2018. "Measuring inefficiency in the presence of bad outputs: Does the disposability assumption matter?," Empirical Economics, Springer, vol. 54(1), pages 101-127, February.
    24. Welch, Eric & Barnum, Darold, 2009. "Joint environmental and cost efficiency analysis of electricity generation," Ecological Economics, Elsevier, vol. 68(8-9), pages 2336-2343, June.
    25. David Griggs & Mark Stafford-Smith & Owen Gaffney & Johan Rockström & Marcus C. Öhman & Priya Shyamsundar & Will Steffen & Gisbert Glaser & Norichika Kanie & Ian Noble, 2013. "Sustainable development goals for people and planet," Nature, Nature, vol. 495(7441), pages 305-307, March.
    26. Dakpo, K Hervé, 2016. "On modeling pollution-generating technologies: a new formulation of the by-production approach," Working Papers 245191, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    27. 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.
    28. Fare, Rolf, et al, 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.
    29. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    30. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2015. "Carbon dioxide emission standards for U.S. power plants: An efficiency analysis perspective," Energy Economics, Elsevier, vol. 50(C), pages 140-153.
    31. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    32. Ayres, Robert U & Kneese, Allen V, 1969. "Production , Consumption, and Externalities," American Economic Review, American Economic Association, vol. 59(3), pages 282-297, June.
    33. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    34. Tim Coelli & Ludwig Lauwers & Guido Huylenbroeck, 2007. "Environmental efficiency measurement and the materials balance condition," Journal of Productivity Analysis, Springer, vol. 28(1), pages 3-12, October.
    35. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
    36. Hampf, Benjamin & Rodseth, Kenneth, 2019. "Environmental Efficiency Measurement with Heterogeneous Input Quality: A Nonparametric Analysis of U.S. Power Plants," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 118700, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    37. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    38. Knox Lovell, C. A. & Pastor, Jesus T. & Turner, Judi A., 1995. "Measuring macroeconomic performance in the OECD: A comparison of European and non-European countries," European Journal of Operational Research, Elsevier, vol. 87(3), pages 507-518, December.
    39. Finn R. Førsund, 2018. "Multi-equation modelling of desirable and undesirable outputs satisfying the materials balance," Empirical Economics, Springer, vol. 54(1), pages 67-99, February.
    40. Lauwers, Ludwig, 2009. "Justifying the incorporation of the materials balance principle into frontier-based eco-efficiency models," Ecological Economics, Elsevier, vol. 68(6), pages 1605-1614, April.
    41. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    42. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2015. "Carbon dioxode emission standards for U.S. power plants: An efficiency analysis perspective," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77009, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    43. Subhash C. Ray & Kankana Mukherjee & Anand Venkatesh, 2018. "Nonparametric measures of efficiency in the presence of undesirable outputs: a by-production approach," Empirical Economics, Springer, vol. 54(1), pages 31-65, February.
    44. K Hervé Dakpo & Philippe Jeanneaux & Laure Latruffe, 2017. "Greenhouse gas emissions and efficiency in French sheep meat farming: A non-parametric framework of pollution-adjusted technologies," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 44(1), pages 33-65.
    45. Timo Kuosmanen & Mika Kortelainen, 2005. "Measuring Eco‐efficiency of Production with Data Envelopment Analysis," Journal of Industrial Ecology, Yale University, vol. 9(4), pages 59-72, October.
    46. Hampf, Benjamin, 2014. "Separating Environmental Efficiency into Production and Abatement Efficiency - A Nonparametric Model with Application to U.S. Power Plants," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 69997, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    47. Murty, Sushama & Robert Russell, R. & Levkoff, Steven B., 2012. "On modeling pollution-generating technologies," Journal of Environmental Economics and Management, Elsevier, vol. 64(1), pages 117-135.
    48. Serra, Teresa & Chambers, Robert G. & Oude Lansink, Alfons, 2014. "Measuring technical and environmental efficiency in a state-contingent technology," European Journal of Operational Research, Elsevier, vol. 236(2), pages 706-717.
    49. Fare, R. & Grosskopf, S. & Pasurka, C., 1986. "Effects on relative efficiency in electric power generation due to environmental controls," Resources and Energy, Elsevier, vol. 8(2), pages 167-184, June.
    50. Rüdiger Pethig, 2003. "The 'materials balance approach' to pollution: its origin, implications and acceptance," Volkswirtschaftliche Diskussionsbeiträge 105-03, Universität Siegen, Fakultät Wirtschaftswissenschaften, Wirtschaftsinformatik und Wirtschaftsrecht.
    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. Andreas Eder, 2021. "Environmental efficiency measurement when producers control pollutants under heterogeneous conditions: a generalization of the materials balance approach," Working Papers 752021, University of Natural Resources and Life Sciences, Vienna, Department of Economics and Social Sciences, Institute for Sustainable Economic Development.
    2. repec:zbw:inwedp:752021 is not listed on IDEAS
    3. Aparicio, Juan & Kapelko, Magdalena & Zofío, José L., 2020. "The measurement of environmental economic inefficiency with pollution-generating technologies," Resource and Energy Economics, Elsevier, vol. 62(C).
    4. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2019. "Environmental efficiency measurement with heterogeneous input quality: A nonparametric analysis of U.S. power plants," Energy Economics, Elsevier, vol. 81(C), pages 610-625.
    5. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    6. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    7. Ke Wang & Yi-Ming Wei & Zhimin Huang, 2017. "Environmental efficiency and abatement efficiency measurements of China¡¯s thermal power industry: A data envelopment analysis based materials balance approach," CEEP-BIT Working Papers 108, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    8. Ke Wang & Zhifu Mi & Yi‐Ming Wei, 2019. "Will Pollution Taxes Improve Joint Ecological and Economic Efficiency of Thermal Power Industry in China?: A DEA‐Based Materials Balance Approach," Journal of Industrial Ecology, Yale University, vol. 23(2), pages 389-401, April.
    9. Abad, Arnaud & Briec, Walter, 2019. "On the axiomatic of pollution-generating technologies: Non-parametric production analysis," European Journal of Operational Research, Elsevier, vol. 277(1), pages 377-390.
    10. Atkinson, Scott E. & Tsionas, Mike G., 2021. "Generalized estimation of productivity with multiple bad outputs: The importance of materials balance constraints," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1165-1186.
    11. Dakpo, Hervé K & Jeanneaux, Philippe & Latruffe, Laure, 2014. "Inclusion of undesirable outputs in production technology modeling: The case of greenhouse gas emissions in French meat sheep farming," Working Papers 207806, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
    12. Aldanondo, Ana M. & Casasnovas, Valero L. & Almansa, M. Carmen, 2016. "Cost-constrained measures of environmental efficiency: a material balance approach," MPRA Paper 72490, University Library of Munich, Germany.
    13. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    14. Hampf, Benjamin, 2018. "Cost and environmental efficiency of U.S. electricity generation: Accounting for heterogeneous inputs and transportation costs," Energy, Elsevier, vol. 163(C), pages 932-941.
    15. Fang, Lei, 2020. "Opening the “black box” of environmental production technology in a nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 286(2), pages 769-780.
    16. Juan Aparicio & Magdalena Kapelko & Lidia Ortiz, 2021. "Modelling environmental inefficiency under a quota system," Operational Research, Springer, vol. 21(2), pages 1097-1124, June.
    17. Finn R. Førsund, 2018. "Multi-equation modelling of desirable and undesirable outputs satisfying the materials balance," Empirical Economics, Springer, vol. 54(1), pages 67-99, February.
    18. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2017. "Assessing environmental performance in the European Union: Eco-innovation versus catching-up," Energy Policy, Elsevier, vol. 104(C), pages 240-252.
    19. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2015. "Carbon dioxide emission standards for U.S. power plants: An efficiency analysis perspective," Energy Economics, Elsevier, vol. 50(C), pages 140-153.
    20. K Hervé Dakpo, 2016. "On modeling pollution-generating technologies: a new formulation of the by-production approach," Working Papers SMART 16-06, INRAE UMR SMART.
    21. Benjamin Hampf, 2018. "Measuring inefficiency in the presence of bad outputs: Does the disposability assumption matter?," Empirical Economics, Springer, vol. 54(1), pages 101-127, February.

    More about this item

    Keywords

    Environmental Economics and Policy; Resource /Energy Economics and Policy;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ags:iaae21:315100. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/iaaeeea.html .

    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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/iaaeeea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.