IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v48y2015i1p439-459.html
   My bibliography  Save this article

An environmental degradation index based on stochastic dominance

Author

Listed:
  • Elettra Agliardi

    ()

  • Mehmet Pinar

    ()

  • Thanasis Stengos

    ()

Abstract

We employ a stochastic dominance (SD) approach to derive a relative environmental degradation index across countries. The variables that are considered include countries’ greenhouse gas (GHG) emissions, water pollution and the net forest depletion, as from the data set of the World Bank. A worst-case scenario index to measure environmental degradation across different countries and at different times is constructed applying a methodology that is based on multivariate comparisons of country panel data over various years and consistent tests for SD efficiency. The test statistics and the estimators are computed using mixed integer programming methods. It is found that in the worst-case scenario index, GHG emissions contribute the most (with a weight around 68 %), net forest depletion contributes with around 30 %, and water pollution contributes the least (with a weight around 2 %). Our index can be a useful tool for policy making in conveying information on the environmental quality and a quick assessment of sustainable performance across countries and over time. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Elettra Agliardi & Mehmet Pinar & Thanasis Stengos, 2015. "An environmental degradation index based on stochastic dominance," Empirical Economics, Springer, vol. 48(1), pages 439-459, February.
  • Handle: RePEc:spr:empeco:v:48:y:2015:i:1:p:439-459
    DOI: 10.1007/s00181-014-0853-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00181-014-0853-3
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kenneth Arrow & Partha Dasgupta & Karl-Göran Mäler, 2003. "Evaluating Projects and Assessing Sustainable Development in Imperfect Economies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 26(4), pages 647-685, December.
    2. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 735-765.
    3. Hamilton, Kirk & Clemens, Michael, 1999. "Genuine Savings Rates in Developing Countries," World Bank Economic Review, World Bank Group, vol. 13(2), pages 333-356, May.
    4. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2013. "Measuring human development: a stochastic dominance approach," Journal of Economic Growth, Springer, vol. 18(1), pages 69-108, March.
    5. Alkire, Sabina & Foster, James, 2011. "Counting and multidimensional poverty measurement," Journal of Public Economics, Elsevier, vol. 95(7), pages 476-487.
    6. Arrow, Kenneth J. & Dasgupta, Partha & Goulder, Lawrence H. & Mumford, Kevin J. & Oleson, Kirsten, 2012. "Sustainability and the measurement of wealth," Environment and Development Economics, Cambridge University Press, vol. 17(03), pages 317-353, June.
    7. Elettra Agliardi, 2011. "Sustainability in Uncertain Economies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 48(1), pages 71-82, January.
    8. Scaillet, Olivier & Topaloglou, Nikolas, 2010. "Testing for Stochastic Dominance Efficiency," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 169-180.
    9. Caterina Cruciani & Silvio Giove & Mehmet Pinar & Matteo Sostero, 2012. "Constructing the FEEM Sustainability Index: A Choquet-Integral Application," Working Papers 2012.50, Fondazione Eni Enrico Mattei.
    10. Esty, Daniel C. & Porter, Michael E., 2005. "National environmental performance: an empirical analysis of policy results and determinants," Environment and Development Economics, Cambridge University Press, vol. 10(04), pages 391-434, August.
    11. Russell Davidson & Jean-Yves Duclos, 2000. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," Econometrica, Econometric Society, vol. 68(6), pages 1435-1464, November.
    12. Agliardi, Elettra & Agliardi, Rossella & Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2012. "A new country risk index for emerging markets: A stochastic dominance approach," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 741-761.
    13. Hilary Sigman, 2002. "International Spillovers and Water Quality in Rivers: Do Countries Free Ride?," American Economic Review, American Economic Association, vol. 92(4), pages 1152-1159, September.
    14. Esty, Daniel C. & Porter, Michael E., 2005. "National environmental performance: an empirical analysis of policy results and determinants," Environment and Development Economics, Cambridge University Press, vol. 10(04), pages 381-389, August.
    15. Muller, Christophe & Trannoy, Alain, 2011. "A dominance approach to the appraisal of the distribution of well-being across countries," Journal of Public Economics, Elsevier, vol. 95(3), pages 239-246.
    16. Carlo Carraro & Lorenza Campagnolo & Fabio Eboli & Elisa Lanzi & Ramiro Parrado & Elisa Portale, 2012. "Quantifying Sustainability: A New Approach and World Ranking," Working Papers 2012.94, Fondazione Eni Enrico Mattei.
    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. repec:spr:empeco:v:55:y:2018:i:4:d:10.1007_s00181-017-1343-1 is not listed on IDEAS
    2. E. Agliardi & M. Pinar & T. Stengos, 2014. "Assessing temporal trends and industry contributions to air and water pollution using stochastic dominance," Working Papers wp981, Dipartimento Scienze Economiche, Universita' di Bologna.
    3. Thomakos, Dimitrios D. & Alexopoulos, Thomas A., 2016. "Carbon intensity as a proxy for environmental performance and the informational content of the EPI," Energy Policy, Elsevier, vol. 94(C), pages 179-190.

    More about this item

    Keywords

    Environmental degradation; Emissions; Water pollution; Forest depletion; Nonparametric stochastic dominance; Mixed integer programming; C4; C5; C14; Q01; Q5; Q51;

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

    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:spr:empeco:v:48:y:2015:i:1:p:439-459. 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: (Sonal Shukla) or (Andrew Huffard). General contact details of provider: http://www.springer.com .

    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.