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A New Index of Environmental Quality Based on Greenhouse Gas Emissions

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Author Info

  • Elettra Agliardi

    ()
    (University of Bologna, Italy)

  • Mehmet Pinar

    ()
    (Edge Hill University, UK)

  • Thanasis Stengos

    ()
    (University of Guelph, Canada)

Abstract

A weighting scheme is proposed to construct a new index of environmental quality based on greenhouse gas (GHG) emissions for different countries using an approach that relies on consistent tests for stochastic dominance (SD) efficiency. The benchmark is an index that is based on the average actual contributions of the respective GHG emission types to the total. Our index stochastically dominates the chosen benchmark and allows us to gure out the “worst” and “best” case scenarios, where environmental degradation is at its maximum and minimum, respectively. If a common global action were to be taken by all countries involved, these scenarios would correspond to the most and least effective possible actions, respectively, that could be undertaken when compared to the benchmark. Then, countries are ranked and their rankings are compared with alternative rankings (e.g., the Kyoto Protocol, Annex I, and the Environmental Sustainability Index, ESI). The test statistics and the estimators are computed using mixed integer programming methods. Then, employing a complementary SD approach, pairwise SD tests are employed to examine the dynamic progress of each separate GHG emission (i.e.,CO2, methane, nitrous oxide, and other GHG emissions) over time, from 1990 to 2005, within 5-year horizons. Pairwise SD tests are used to examine the major industry contributors to the GHG emissions at any given time and to uncover the industry which contributes the most to total emissions.

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Bibliographic Info

Paper provided by The Rimini Centre for Economic Analysis in its series Working Paper Series with number 12_13.

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Date of creation: Jan 2013
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Handle: RePEc:rim:rimwps:12_13

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Keywords: Environmental Quality; Emissions; Nonparametric Stochastic Dominance; Mixed Integer Programming;

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References

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  1. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
  2. Hamilton, Kirk & Clemens, Michael, 1999. "Genuine Savings Rates in Developing Countries," World Bank Economic Review, World Bank Group, vol. 13(2), pages 333-56, May.
  3. Palmer, Karen & Burtraw, Dallas, 2005. "Cost-effectiveness of renewable electricity policies," Energy Economics, Elsevier, vol. 27(6), pages 873-894, November.
  4. Kenneth J. Arrow & Partha Dasgupta & Lawrence H. Goulder & Kevin J. Mumford & Kirsten Oleson, 2010. "Sustainability and the Measurement of Wealth," NBER Working Papers 16599, National Bureau of Economic Research, Inc.
  5. Elettra Agliardi, 2011. "Sustainability in Uncertain Economies," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 48(1), pages 71-82, January.
  6. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2012. "Measuring human development: a stochastic dominance approach," Working Papers 1209, University of Guelph, Department of Economics and Finance.
  7. Yan, Xiaoyu & Crookes, Roy J., 2009. "Reduction potentials of energy demand and GHG emissions in China's road transport sector," Energy Policy, Elsevier, vol. 37(2), pages 658-668, February.
  8. 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.
  9. Kenneth Arrow & Partha Dasgupta & Lawrence Goulder & Gretchen Daily & Paul Ehrlich & Geoffrey Heal & Simon Levin & Karl-Göran Mäler & Stephen Schneider & David Starrett & Brian Walker, 2004. "Are We Consuming Too Much?," Journal of Economic Perspectives, American Economic Association, vol. 18(3), pages 147-172, Summer.
  10. Scaillet, Olivier & Topaloglou, Nikolas, 2010. "Testing for Stochastic Dominance Efficiency," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 169-180.
  11. repec:oup:renvpo:v:6:y::i:1:p:45-64 is not listed on IDEAS
  12. Richard Schmalensee, 2012. "Evaluating Policies to Increase Electricity Generation from Renewable Energy," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 6(1), pages 45-64.
  13. 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.
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