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Posterior Analysis of Environmental Damage Evaluation in Europe

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  • Efthymios Tsionas
  • George Halkos

Abstract

In this paper we consider environmental damage evaluation using two types of econometric models to analyse tree damage due to acid deposits, using cross-country data for several European countries. First, we use a set of univariate Poisson models and second, a multinomial probit model with the difference that we do not observe class specific data. The damage function is parameterized in terms of a number of economic and environmental variables. Statistical inference is conducted using Bayesian methods relying on Markov Chain Monte Carlo simulation. Natural by-products of our method include an implied ranking of countries according to environmental damage, and (exact, finite sample) posterior distributions of average country-specific environmental damage.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal International Review of Applied Economics.

Volume (Year): 14 (2000)
Issue (Month): 3 ()
Pages: 371-390

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Handle: RePEc:taf:irapec:v:14:y:2000:i:3:p:371-390

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References

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  1. George Halkos, 1996. "Incomplete information in the acid rain game," Empirica, Springer, vol. 23(2), pages 129-148, June.
  2. Newey, Whitney K & West, Kenneth D, 1987. "A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix," Econometrica, Econometric Society, vol. 55(3), pages 703-08, May.
  3. Halkos, George E, 1993. "Optimal sulphur emissions abatement in Europe," MPRA Paper 33536, University Library of Munich, Germany.
  4. Naylor, J. C. & Smith, A. F. M., 1988. "Econometric illustrations of novel numerical integration strategies for Bayesian inference," Journal of Econometrics, Elsevier, vol. 38(1-2), pages 103-125.
  5. Amemiya, Takeshi, 1981. "Qualitative Response Models: A Survey," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1483-1536, December.
  6. Terza, Joseph V & Wilson, Paul W, 1990. "Analyzing Frequencies of Several Types of Events: A Mixed Multinomial-Poisson Approach," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 108-15, February.
  7. Tsionas, Efthymios G., 1998. "Monte Carlo inference in econometric models with symmetric stable disturbances," Journal of Econometrics, Elsevier, vol. 88(2), pages 365-401, November.
  8. Pearce, David & Crowards, Tom, 1996. "Particulate matter and human health in the United Kingdom," Energy Policy, Elsevier, vol. 24(7), pages 609-619, July.
  9. Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January.
  10. Pearce, David, 1996. "Economic valuation and health damage from air pollution in the developing world," Energy Policy, Elsevier, vol. 24(7), pages 627-630, July.
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Citations

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Cited by:
  1. Dimitris K. Christopoulos & Efthymios G. Tsionas, 2005. "Productivity growth and inflation in Europe: Evidence from panel cointegration tests," Empirical Economics, Springer, vol. 30(1), pages 137-150, January.
  2. Dimitris Christopoulos & Efthymios Tsionas, 2002. "Unemployment and government size: Is there any credible causality?," Applied Economics Letters, Taylor & Francis Journals, vol. 9(12), pages 797-800.
  3. Dimitris Christopoulos & John Loizides & Efthymios Tsionas, 2005. "The Abrams curve of government size and unemployment: evidence from panel data," Applied Economics, Taylor & Francis Journals, vol. 37(10), pages 1193-1199.

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