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The impact of pollution abatement investments on technology: Porter hypothesis revisited

Author

Listed:
  • Jean Pierre Huiban

    (INRA-ALISS)

  • Camilla Mastromarco

    () (Dipartimento di Scienze dell'Economia, Università del Salento, Italy)

  • Antonio Musolesi

    () (Department of Economics and Management, University of Ferrara, Italy)

  • Michel Simioni

    () (Toulouse School of Economics, INRA-GREMAQ and IDEI, France)

Abstract

This paper revisits the Porter hypothesis by pursuing two new directions. First, we compare the results obtained with two complementary approaches: parametric stochastic frontier analysis and conditional nonparametric frontier analysis. They presents relative advantages and drawbacks. Secondly, we pay attention not only on the average pollution abatement effort effect but we also focus on its variability across rms and over time. We provide new results suggesting that the traditional view about the effect of environmental regulation on productivity and the Porter hypothesis may coexist. This evidence supports the idea that a well-designed environmental regulation affects positively the rm performances in some instances.

Suggested Citation

  • Jean Pierre Huiban & Camilla Mastromarco & Antonio Musolesi & Michel Simioni, 2015. "The impact of pollution abatement investments on technology: Porter hypothesis revisited," SEEDS Working Papers 0815, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Apr 2015.
  • Handle: RePEc:srt:wpaper:0815
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    References listed on IDEAS

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    1. Thomas Broberg & Per-Olov Marklund & Eva Samakovlis & Henrik Hammar, 2013. "Testing the Porter hypothesis: the effects of environmental investments on efficiency in Swedish industry," Journal of Productivity Analysis, Springer, vol. 40(1), pages 43-56, August.
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    3. Gerhard Kempkes & Carsten Pohl, 2010. "The efficiency of German universities-some evidence from nonparametric and parametric methods," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2063-2079.
    4. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    5. Paul Lanoie & Jérémy Laurent‐Lucchetti & Nick Johnstone & Stefan Ambec, 2011. "Environmental Policy, Innovation and Performance: New Insights on the Porter Hypothesis," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 20(3), pages 803-842, September.
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    8. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
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    10. Tim Coelli & Sergio Perelman & Elliot Romano, 1999. "Accounting for Environmental Influences in Stochastic Frontier Models: With Application to International Airlines," Journal of Productivity Analysis, Springer, vol. 11(3), pages 251-273, June.
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    Cited by:

    1. George van Leeuwen & Pierre Mohnen, 2017. "Revisiting the Porter hypothesis: an empirical analysis of Green innovation for the Netherlands," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 26(1-2), pages 63-77, February.
    2. repec:kap:enreec:v:70:y:2018:i:2:d:10.1007_s10640-017-0128-5 is not listed on IDEAS
    3. Jana Stoever & John P. Weche, 2018. "Environmental Regulation and Sustainable Competitiveness: Evaluating the Role of Firm-Level Green Investments in the Context of the Porter Hypothesis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 70(2), pages 429-455, June.

    More about this item

    Keywords

    Porter hypothesis; pollution abatement investment; stochastic frontier analysis; time-varying eciency; Vuong test; conditional nonparametric frontier analysis.;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General

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