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Modelling biodiversity

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  • Halkos, George

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.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 39075.

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Date of creation: 2010
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Publication status: Published in Journal of Policy Modeling 4.33(2011): pp. 618-635
Handle: RePEc:pra:mprapa:39075

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Keywords: Nonparametric quantile regression; biodiversity;

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  1. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, Econometric Society, vol. 50(1), pages 43-61, January.
  2. Samuel Brody, 2003. "Examining the Effects of Biodiversity on the Ability of Local Plans to Manage Ecological Systems," Journal of Environmental Planning and Management, Taylor & Francis Journals, Taylor & Francis Journals, vol. 46(6), pages 817-837.
  3. Buchinsky, Moshe, 1995. "Estimating the asymptotic covariance matrix for quantile regression models a Monte Carlo study," Journal of Econometrics, Elsevier, Elsevier, vol. 68(2), pages 303-338, August.
  4. Rolf Groeneveld & Carla Grashof-Bokdam & Ekko van Ierland, 2005. "Metapopulations in Agricultural Landscapes: A Spatially Explicit Trade-off Analysis," Journal of Environmental Planning and Management, Taylor & Francis Journals, Taylor & Francis Journals, vol. 48(4), pages 527-547.
  5. Costanza, Robert & Fisher, Brendan & Mulder, Kenneth & Liu, Shuang & Christopher, Treg, 2007. "Biodiversity and ecosystem services: A multi-scale empirical study of the relationship between species richness and net primary production," Ecological Economics, Elsevier, Elsevier, vol. 61(2-3), pages 478-491, March.
  6. Halkos, George E., 2003. "Environmental Kuznets Curve for sulfur: evidence using GMM estimation and random coefficient panel data models," Environment and Development Economics, Cambridge University Press, Cambridge University Press, vol. 8(04), pages 581-601, October.
  7. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, Elsevier, vol. 32(1), pages 143-155, June.
  8. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
  9. Newey, Whitney K & Powell, James L, 1987. "Asymmetric Least Squares Estimation and Testing," Econometrica, Econometric Society, Econometric Society, vol. 55(4), pages 819-47, July.
  10. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, Econometric Society, vol. 46(1), pages 33-50, January.
  11. Nunes, Paulo A. L. D. & van den Bergh, Jeroen C. J. M., 2001. "Economic valuation of biodiversity: sense or nonsense?," Ecological Economics, Elsevier, Elsevier, vol. 39(2), pages 203-222, November.
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