Modelling biodiversity

George Halkos

MPRA Paper from University Library of Munich, Germany

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, CO¬2 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.

Keywords: Nonparametric quantile regression; biodiversity (search for similar items in EconPapers)
JEL-codes: C10 C14 C40 Q20 Q57 (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (1)

Published in Journal of Policy Modeling 4.33(2011): pp. 618-635

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:39075

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