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Eco-label Adoption in an Interdependent World

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  • José-Antonio Monteiro

Abstract

The growing popularity of national efforts to promote eco-labeling raises important questions. In particular, developing countries fear that the eco-label can deliberately impose the environmental concern of (high income) importing countries on their production methods. Yet, empirical studies of the adoption of eco-labelling schemes at the cross-country level are scarce due to the lack of data availability. In this paper, the decision to introduce an eco-label is analyzed through a heteroskedastic Bayesian spatial probit, which allows the government’s decision to introduce an eco-label to be influenced by the behaviour of the neighbouring countries. The estimation is performed by extending the joint updating approach proposed by Holmes & Held (2006) to a spatial framework. Empirical evidence highlights the importance of a high stage of development, innovation experience and potential scale effects in the implementation of an eco-label scheme. In addition, results confirm the existence of a strategic interdependence in the eco-label decision.

Suggested Citation

  • José-Antonio Monteiro, 2010. "Eco-label Adoption in an Interdependent World," IRENE Working Papers 10-01, IRENE Institute of Economic Research.
  • Handle: RePEc:irn:wpaper:10-01
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    2. Low, Sui Pheng & Gao, Shang & See, Yan Long, 2014. "Strategies and measures for implementing eco-labelling schemes in Singapore's construction industry," Resources, Conservation & Recycling, Elsevier, vol. 89(C), pages 31-40.

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    More about this item

    Keywords

    Bayesian Spatial Probit; International Trade; Environmental Policy; Eco-labelling;
    All these keywords.

    JEL classification:

    • F18 - International Economics - - Trade - - - Trade and Environment
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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