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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.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Policy Modeling.

Volume (Year): 33 (2011)
Issue (Month): 4 (July)
Pages: 618-635

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Handle: RePEc:eee:jpolmo:v:33:y:2011:i:4:p:618-635

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Web page: http://www.elsevier.com/locate/inca/505735

Related research

Keywords: Nonparametric quantile regression Partial regression Biodiversity;

References

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Cited by:
  1. Natina Yaduma & Mika Kortelainen & Ada Wossink, 2013. "The Environmental Kuznets Curve at Different Levels of Economic Development: A Counterfactual Quantile Regression Analysis for CO2 Emissions," The School of Economics Discussion Paper Series 1322, Economics, The University of Manchester.

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