IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/39075.html
   My bibliography  Save this paper

Modelling biodiversity

Author

Listed:
  • 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.

Suggested Citation

  • Halkos, George, 2010. "Modelling biodiversity," MPRA Paper 39075, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:39075
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/39075/1/MPRA_paper_39075.pdf
    File Function: original version
    Download Restriction: no

    References listed on IDEAS

    as
    1. 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.
    2. 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, vol. 61(2-3), pages 478-491, March.
    3. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    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, vol. 48(4), pages 527-547.
    5. 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, vol. 46(6), pages 817-837.
    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, vol. 8(04), pages 581-601, October.
    7. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    8. Nunes, Paulo A. L. D. & van den Bergh, Jeroen C. J. M., 2001. "Economic valuation of biodiversity: sense or nonsense?," Ecological Economics, Elsevier, vol. 39(2), pages 203-222, November.
    9. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    10. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    11. Buchinsky, Moshe, 1995. "Estimating the asymptotic covariance matrix for quantile regression models a Monte Carlo study," Journal of Econometrics, Elsevier, vol. 68(2), pages 303-338, August.
    12. Newey, Whitney K & Powell, James L, 1987. "Asymmetric Least Squares Estimation and Testing," Econometrica, Econometric Society, vol. 55(4), pages 819-847, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Paunić, Alida, 2016. "Brazil, Preservation of Forest and Biodiversity," MPRA Paper 71462, University Library of Munich, Germany.

    More about this item

    Keywords

    Nonparametric quantile regression; biodiversity;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:39075. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter) or (Rebekah McClure). General contact details of provider: http://edirc.repec.org/data/vfmunde.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.