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Nonparametric modelling of biodiversity: Determinants of threatened species

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  • Halkos, George E.

Abstract

This study uses a sample of 71 countries and nonparametric quantile and partial regressions to model a number of threatened species (reptiles, mammals, fish, birds, trees, plants) in relation to various economic and environmental variables (GDPc, CO2 emissions, agricultural production, energy intensity, protected areas, population and income inequality). From the analysis and due to high asymmetric distribution of the dependent variables it seems that a linear regression is not adequate and cannot capture properly the dimension of the threatened species. We find that using OLS instead of non-parametric techniques over- or under-estimates the parameters which may have serious policy implications.

Suggested Citation

  • Halkos, George E., 2011. "Nonparametric modelling of biodiversity: Determinants of threatened species," Journal of Policy Modeling, Elsevier, vol. 33(4), pages 618-635, July.
  • Handle: RePEc:eee:jpolmo:v:33:y:2011:i:4:p:618-635
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Halkos, George & Managi, Shunsuke, 2017. "Land use, forest preservation and biodiversity in Asia," MPRA Paper 82883, University Library of Munich, Germany.
    2. Natina Yaduma & Mika Kortelainen & Ada Wossink, 2015. "The environmental Kuznets curve at different levels of economic development: a counterfactual quantile regression analysis for CO 2 emissions," Journal of Environmental Economics and Policy, Taylor & Francis Journals, pages 278-303.
    3. Halkos, George & Matsiori, Steriani, 2017. "Estimating recreational values of coastal zones," MPRA Paper 80911, University Library of Munich, Germany.

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