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Exploring the effect of countries’ economic prosperity on their biodiversity performance

Author

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  • Halkos, George
  • Tzeremes, Nickolaos

Abstract

This paper demonstrates an evaluation of 71 developed and under-developed countries’ biodiversity performance using a methodological framework based to the new advances of Data Envelopment Analysis (DEA). By using conditional DEA, bootstrapping and kernel density estimations, efficiency levels of 71 countries are compared and analyzed. In such a way the paper by modelling and measuring countries’ biodiversity performance analyses whether the countries environmental policies have been used efficiently in order to enhance biodiversity. Our empirical results indicate that there are major inefficiencies among the 71 countries in terms of their biodiversity performances which have been negatively influenced by their higher levels of population and of GDP per capita.

Suggested Citation

  • Halkos, George & Tzeremes, Nickolaos, 2009. "Exploring the effect of countries’ economic prosperity on their biodiversity performance," MPRA Paper 32102, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:32102
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    File URL: https://mpra.ub.uni-muenchen.de/32102/1/MPRA_paper_32102.pdf
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    References listed on IDEAS

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    1. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    2. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    3. Bădin, Luiza & Simar, Léopold, 2009. "A Bias-Corrected Nonparametric Envelopment Estimator Of Frontiers," Econometric Theory, Cambridge University Press, vol. 25(05), pages 1289-1318, October.
    4. Fare, R. & Grosskopf, S. & Hernandez-Sancho, F., 2004. "Environmental performance: an index number approach," Resource and Energy Economics, Elsevier, vol. 26(4), pages 343-352, December.
    5. Halkos, George Emm. & Tzeremes, Nickolaos G., 2009. "Exploring the existence of Kuznets curve in countries' environmental efficiency using DEA window analysis," Ecological Economics, Elsevier, vol. 68(7), pages 2168-2176, May.
    6. Jeong, Seok-Oh & Simar, Léopold, 2006. "Linearly interpolated FDH efficiency score for nonconvex frontiers," Journal of Multivariate Analysis, Elsevier, vol. 97(10), pages 2141-2161, November.
    7. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Cinzia Daraio & Léopold Simar, 2007. "Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach," Journal of Productivity Analysis, Springer, vol. 28(1), pages 13-32, October.
    10. Taskin, Fatma & Zaim, Osman, 2000. "Searching for a Kuznets curve in environmental efficiency using kernel estimation," Economics Letters, Elsevier, vol. 68(2), pages 217-223, August.
    11. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    12. Simar, Leopold & Wilson, Paul W., 2002. "Non-parametric tests of returns to scale," European Journal of Operational Research, Elsevier, vol. 139(1), pages 115-132, May.
    13. Osman Zaim & Fatma Taskin, 2000. "A Kuznets Curve in Environmental Efficiency: An Application on OECD Countries," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 17(1), pages 21-36, September.
    14. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    15. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
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    Cited by:

    1. Gren, Ing-Marie & Campos, Monica & Gustafsson, Lena & Elofsson, Katarina, 2013. "Species Imperilment on the Global Scale: Empirical evidences of economic causes," Working Paper Series 2013:7, Swedish University of Agricultural Sciences, Department Economics.

    More about this item

    Keywords

    Biodiversity; Conditional DEA; Bootstrap techniques; Convexity test; Kernel density estimation;

    JEL classification:

    • C69 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Other
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics

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