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Environmental policy performance and its determinants: Application of a three-level random intercept model

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  • Galeotti, Marzio
  • Rubashkina, Yana
  • Salini, Silvia
  • Verdolini, Elena

Abstract

This paper contributes to the study of environmental and energy policy by using a three-level random intercept (TLRI) model to rank the performance of different countries. Inspired by the literature on Item Response Theory and multilevel latent models, the TLRI model treats policy commitment as a latent variable which is estimated conditional on the difficulty of the policy portfolio implemented by each country. This approach is characterized by three novel aspects. First, the model results in a ranking of countries which is conditional on the complexity of their chosen policy portfolio. Second, it provides a unified framework in which to construct a policy indicator and to study its determinants through a latent regression approach. The resulting country ranking can thus be cleaned from the effect of economic and institutional observables which affect policy design and implementation. Third, the model estimates parameters which can be used to describe and compare policy portfolios across countries. We apply this methodology to the case of energy efficiency policies in the industrial sectors of 29 EU countries between 2004 and 2011. In the conclusions we highlight the future possible applications of this approach, which are not confined to the realm of environmental and energy policy.

Suggested Citation

  • Galeotti, Marzio & Rubashkina, Yana & Salini, Silvia & Verdolini, Elena, 2018. "Environmental policy performance and its determinants: Application of a three-level random intercept model," Energy Policy, Elsevier, vol. 114(C), pages 134-144.
  • Handle: RePEc:eee:enepol:v:114:y:2018:i:c:p:134-144
    DOI: 10.1016/j.enpol.2017.11.053
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    Cited by:

    1. Nicolli, Francesco & Vona, Francesco, 2019. "Energy market liberalization and renewable energy policies in OECD countries," Energy Policy, Elsevier, vol. 128(C), pages 853-867.
    2. Marzio Galeotti & Silvia Salini & Elena Verdolini, 2017. "Measuring Environmental Policy Stringency: Approaches, Validity, and Impact on Energy Efficiency," Development Working Papers 412, Centro Studi Luca d'Agliano, University of Milano.
    3. Galeotti, Marzio & Salini, Silvia & Verdolini, Elena, 2020. "Measuring environmental policy stringency: Approaches, validity, and impact on environmental innovation and energy efficiency," Energy Policy, Elsevier, vol. 136(C).
    4. Cartelle Barros, Juan José & Lara Coira, Manuel & de la Cruz López, María Pilar & del Caño Gochi, Alfredo & Soares, Isabel, 2020. "Probabilistic multicriteria environmental assessment of power plants: A global approach," Applied Energy, Elsevier, vol. 260(C).

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    More about this item

    Keywords

    Q58; O57; C33; Energy policy; Environmental policy; Ranking; Policy portfolios;
    All these keywords.

    JEL classification:

    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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