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Environmental Regulation and Firm Efficiency: Studying the Porter Hypothesis using a Directional Output Distance Function

Author

Listed:
  • Marklund, Per-Olov

    (Department of Economics, Umeå University)

Abstract

The purpose of this paper is to suggest a procedure to empirically test the Porter hypothesis. This hypothesis argues that environmental regulation not only increases environmental quality, but also brings the polluting producers information that makes them more resource efficient, as well as able to develop new technologies. Specifically, the hypothesis tested is whether there is a positive significant correlation between producers’ technical output efficiency and environmental regulation. Efficiency is first estimated using a methodology where the production technology is represented by a directional output distance function, which credits a simultaneous expansion of market goods and contraction of emissions. Then, by regressing the obtained efficiency scores on an index that approximates environmental regulatory intensity, the Porter hypothesis is explicitly tested. The test procedure is applied on 12 Swedish pulp plants during 1983-1990. The result shows no support for the Porter hypothesis.

Suggested Citation

  • Marklund, Per-Olov, 2003. "Environmental Regulation and Firm Efficiency: Studying the Porter Hypothesis using a Directional Output Distance Function," Umeå Economic Studies 619, Umeå University, Department of Economics.
    • Handle: RePEc:hhs:umnees:0619
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    References listed on IDEAS

    as
    1. Adam B. Jaffe & Karen Palmer, 1997. "Environmental Regulation And Innovation: A Panel Data Study," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 610-619, November.
    2. Xepapadeas, Anastasios & de Zeeuw, Aart, 1999. "Environmental Policy and Competitiveness: The Porter Hypothesis and the Composition of Capital," Journal of Environmental Economics and Management, Elsevier, vol. 37(2), pages 165-182, March.
    3. Gollop, Frank M & Roberts, Mark J, 1983. "Environmental Regulations and Productivity Growth: The Case of Fossil-Fueled Electric Power Generation," Journal of Political Economy, University of Chicago Press, vol. 91(4), pages 654-674, August.
    4. 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.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Kriechel, Ben & Ziesemer, Thomas, 2003. "The Environmental Porter Hypothesis as a Technology Adoption Problem?," Research Memorandum 011, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    2. repec:dgr:umamer:2005008 is not listed on IDEAS
    3. Ben Kriechel & Thomas Ziesemer, 2009. "The environmental Porter hypothesis: theory, evidence, and a model of timing of adoption," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 18(3), pages 267-294.
    4. Anabel Zárate-Marco & Jaime Vallés-Giménez, 2015. "Environmental tax and productivity in a decentralized context: new findings on the Porter hypothesis," European Journal of Law and Economics, Springer, vol. 40(2), pages 313-339, October.
    5. Vivek Ghosal & Andreas Stephan & Jan F. Weiss, 2019. "Decentralized environmental regulations and plant‐level productivity," Business Strategy and the Environment, Wiley Blackwell, vol. 28(6), pages 998-1011, September.

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    More about this item

    Keywords

    Porter hypothesis; environmental regulation; technical efficiency; parametric directional output distance function;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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