IDEAS home Printed from https://ideas.repec.org/a/spr/envpol/v24y2022i4d10.1007_s10018-021-00335-5.html
   My bibliography  Save this article

Prevention or cure? Optimal abatement mix

Author

Listed:
  • Moriah Bostian

    (Lewis & Clark College
    Umeå University)

  • Rolf Färe

    (Oregon State University
    University of Maryland)

  • Shawna Grosskopf

    (Oregon State University
    Umeå University)

  • Tommy Lundgren

    (Umeå University)

Abstract

We develop a model for pollution abatement that distinguishes between prevention and treatment technologies, in order to better understand the optimal mix of abatement measures. Our model separates the production process into two stages, an initial production and prevention stage and a final treatment (or cure) stage. We allow for reallocation of abatement investment across the production stages, in order to improve overall abatement and production and to better understand the tradeoffs between abatement measures. This framework is relevant in practice for numerous industrial production processes, including manufacturing and energy, which employ different abatement measures at different stages of production. In our application to Sweden’s pulp and paper sector, we find the industry could achieve further gains to both production and emissions reductions, beyond those estimated using more common single-stage technology estimation methods, by reallocating abatement investments. These results could be used to improve firm environmental management decisions, and to better target policy incentives to specific forms of abatement.

Suggested Citation

  • Moriah Bostian & Rolf Färe & Shawna Grosskopf & Tommy Lundgren, 2022. "Prevention or cure? Optimal abatement mix," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 24(4), pages 503-531, October.
  • Handle: RePEc:spr:envpol:v:24:y:2022:i:4:d:10.1007_s10018-021-00335-5
    DOI: 10.1007/s10018-021-00335-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10018-021-00335-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10018-021-00335-5?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. Moriah Bostian & Rolf Färe & Shawna Grosskopf & Tommy Lundgren & William L. Weber, 2018. "Time substitution for environmental performance: The case of Swedish manufacturing," Empirical Economics, Springer, vol. 54(1), pages 129-152, February.
    2. Rolf Färe & Shawna Grosskopf & Dimitri Margaritis & William Weber, 2012. "Technological change and timing reductions in greenhouse gas emissions," Journal of Productivity Analysis, Springer, vol. 37(3), pages 205-216, June.
    3. Jaffe Adam B. & Stavins Robert N., 1995. "Dynamic Incentives of Environmental Regulations: The Effects of Alternative Policy Instruments on Technology Diffusion," Journal of Environmental Economics and Management, Elsevier, vol. 29(3), pages 43-63, November.
    4. Jurate Jaraite & Andrius Kazukauskas & Tommy Lundgren, 2014. "The effects of climate policy on environmental expenditure and investment: evidence from Sweden," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 3(2), pages 148-166, July.
    5. Krüger, Jens & Hampf, Benjamin, 2015. "Optimal Directions for Directional Distance Functions: An Exploration of Potential Reductions of Greenhouse Gases," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77007, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Suzi Kerr & Richard G. Newell, 2003. "Policy‐Induced Technology Adoption: Evidence from the U.S. Lead Phasedown," Journal of Industrial Economics, Wiley Blackwell, vol. 51(3), pages 317-343, September.
    7. Laura Cáceres & Daniel Méndez & Jairo Fernández & Rafael Marcé, 2018. "From End-of-Pipe to Nature Based Solutions: a Simple Statistical Tool for Maximizing the Ecosystem Services Provided by Reservoirs for Drinking Water Treatment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(4), pages 1307-1323, March.
    8. Triguero, Angela & Moreno-Mondéjar, Lourdes & Davia, María A., 2014. "The influence of energy prices on adoption of clean technologies and recycling: Evidence from European SMEs," Energy Economics, Elsevier, vol. 46(C), pages 246-257.
    9. Benjamin Hampf & Jens J. Krüger, 2015. "Optimal Directions for Directional Distance Functions: An Exploration of Potential Reductions of Greenhouse Gases," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(3), pages 920-938.
    10. Sushama Murty & R. Robert Russell, 2018. "Modeling emission-generating technologies: reconciliation of axiomatic and by-production approaches," Empirical Economics, Springer, vol. 54(1), pages 7-30, February.
    11. 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.
    12. Bostian, Moriah & Färe, Rolf & Grosskopf, Shawna & Lundgren, Tommy, 2018. "Network Representations of Pollution-Generating Technologies," International Review of Environmental and Resource Economics, now publishers, vol. 11(3), pages 193-231, August.
    13. Frondel, Manuel & Horbach, Jens & Rennings, Klaus, 2008. "What triggers environmental management and innovation? Empirical evidence for Germany," Ecological Economics, Elsevier, vol. 66(1), pages 153-160, May.
    14. Manuel Frondel & Jens Horbach & Klaus Rennings, 2007. "End‐of‐pipe or cleaner production? An empirical comparison of environmental innovation decisions across OECD countries," Business Strategy and the Environment, Wiley Blackwell, vol. 16(8), pages 571-584, December.
    15. Scott E. Atkinson & Mike G. Tsionas, 2018. "Shadow directional distance functions with bads: GMM estimation of optimal directions and efficiencies," Empirical Economics, Springer, vol. 54(1), pages 207-230, February.
    16. 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.
    17. Ayres, Robert U & Kneese, Allen V, 1969. "Production , Consumption, and Externalities," American Economic Review, American Economic Association, vol. 59(3), pages 282-297, June.
    18. Yang, Hongliang & Pollitt, Michael, 2010. "The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants," Energy Policy, Elsevier, vol. 38(8), pages 4440-4444, August.
    19. 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.
    20. 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.
    21. Cinzia Daraio & Léopold Simar, 2016. "Efficiency and benchmarking with directional distances: a data-driven approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(7), pages 928-944, July.
    22. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    23. Färe, Rolf & Pasurka, Carl & Vardanyan, Michael, 2017. "On endogenizing direction vectors in parametric directional distance function-based models," European Journal of Operational Research, Elsevier, vol. 262(1), pages 361-369.
    24. 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).
    25. 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.
    26. Chiang Kao, 2017. "Network Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-3-319-31718-2, December.
    27. Katrin Millock & Céline Nauges, 2006. "Ex Post Evaluation of an Earmarked Tax on Air Pollution," Land Economics, University of Wisconsin Press, vol. 82(1), pages 68-84.
    28. Hammar, Henrik & Löfgren, Åsa, 2010. "Explaining adoption of end of pipe solutions and clean technologies--Determinants of firms' investments for reducing emissions to air in four sectors in Sweden," Energy Policy, Elsevier, vol. 38(7), pages 3644-3651, July.
    29. Adam Jaffe & Richard Newell & Robert Stavins, 2002. "Environmental Policy and Technological Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 22(1), pages 41-70, June.
    30. Amjadi, Golnaz, 2020. "Environment versus Jobs: An Industry-level Analysis of Sweden," CERE Working Papers 2020:13, CERE - the Center for Environmental and Resource Economics, revised 04 Nov 2020.
    31. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    32. Sarkis, Joseph & Cordeiro, James J., 2001. "An empirical evaluation of environmental efficiencies and firm performance: Pollution prevention versus end-of-pipe practice," European Journal of Operational Research, Elsevier, vol. 135(1), pages 102-113, November.
    33. Wu, Ge & Baležentis, Tomas & Sun, Chuanwang & Xu, Shuhua, 2019. "Source control or end-of-pipe control: Mitigating air pollution at the regional level from the perspective of the Total Factor Productivity change decomposition," Energy Policy, Elsevier, vol. 129(C), pages 1227-1239.
    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. Zhou, Yi & Zhou, Wenji & Wei, Chu, 2023. "Environmental performance of the Chinese cement enterprise: An empirical analysis using a text-based directional vector," Energy Economics, Elsevier, vol. 125(C).
    2. Rolf Färe & Shawna Grosskopf & Carl A. Pasurka, 2023. "Revealed pollution abatement costs revisited," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 25(4), pages 601-629, October.
    3. Daniel Leppert, 2023. "“No fences make bad neighbors” but markets make better ones: cap-and-trade reduces cross-border SO2 in a natural experiment," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 25(3), pages 407-433, July.

    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. Niu, Yiran & Boussemart, Jean-Philippe & Shen, Zhiyang & Vardanyan, Michael, 2024. "Performance evaluation using multi-stage production frameworks: Assessing the tradeoffs among the economic, environmental, and social well-being," European Journal of Operational Research, Elsevier, vol. 318(3), pages 1000-1013.
    2. Finn R. Førsund, 2021. "Performance measurement and joint production of intended and unintended outputs," Journal of Productivity Analysis, Springer, vol. 55(3), pages 157-175, June.
    3. 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.
    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. Andreas Eder, 2022. "Environmental efficiency measurement when producers control pollutants under heterogeneous conditions: a generalization of the materials balance approach," Journal of Productivity Analysis, Springer, vol. 57(2), pages 157-176, April.
    6. 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.
    7. repec:zbw:inwedp:752021 is not listed on IDEAS
    8. Dakpo, K Hervé & Lansink, Alfons Oude, 2019. "Dynamic pollution-adjusted inefficiency under the by-production of bad outputs," European Journal of Operational Research, Elsevier, vol. 276(1), pages 202-211.
    9. 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.
    10. Vardanyan, Michael & Valdmanis, Vivian G. & Leleu, Hervé & Ferrier, Gary D., 2022. "Estimating technology characteristics of the U.S. hospital industry using directional distance functions with optimal directions," Omega, Elsevier, vol. 113(C).
    11. 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.
    12. Kenneth Løvold Rødseth, 2017. "Environmental regulations and allocative efficiency: application to coal-to-gas substitution in the U.S. electricity sector," Journal of Productivity Analysis, Springer, vol. 47(2), pages 129-142, April.
    13. 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.
    14. Amer Ait Sidhoum, 2023. "Assessing the contribution of farmers’ working conditions to productive efficiency in the presence of uncertainty, a nonparametric approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8601-8622, August.
    15. Justas Streimikis & Z. Y. Shen & Tomas Balezentis, 2024. "Does the energy-related greenhouse gas emission abatement cost depend on the optimization direction: shadow pricing based on the weak disposability technology in the European Union agriculture," 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. 32(3), pages 593-619, September.
    16. 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.
    17. 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).
    18. Subhash C. Ray & Shilpa Sethia, 2024. "A state-level resource allocation model for emission reduction and efficiency improvement in thermal power plants," Indian Economic Review, Springer, vol. 59(1), pages 205-257, October.
    19. 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.
    20. Pham, Manh D. & Zelenyuk, Valentin, 2019. "Weak disposability in nonparametric production analysis: A new taxonomy of reference technology sets," European Journal of Operational Research, Elsevier, vol. 274(1), pages 186-198.
    21. Hammar, Henrik & Löfgren, Åsa, 2010. "Explaining adoption of end of pipe solutions and clean technologies--Determinants of firms' investments for reducing emissions to air in four sectors in Sweden," Energy Policy, Elsevier, vol. 38(7), pages 3644-3651, July.

    More about this item

    Keywords

    Abatement; Production technology; Network model; Environmental investment; Emissions policy;
    All these keywords.

    JEL classification:

    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    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:spr:envpol:v:24:y:2022:i:4:d:10.1007_s10018-021-00335-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.