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Meta-analysis in model implementation: choice sets and the valuation of air quality improvements

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Author Info

  • H. Spencer Banzhaf

    (Department of Economics, Andrew Young School of Policy Studies, Georgia State University, Atlanta, Georgia, USA)

  • V. Kerry Smith

    (Department of Economics, Arizona State University, Tempe, Arizona, USA)

Abstract

This research illustrates how the methods developed for meta-analysis can serve to document and summarize voluminous information derived from repeated sensitivity analyses. Our application is to the sensitivity of welfare estimates derived from discrete choice models to assumptions about the choice set. These assumptions affect welfare estimates through both the estimated parameters of the model and, conditional on the parameters, the substitution among alternatives. In our specific application, the evaluation is in terms of estimated benefits of air quality improvements in Los Angeles based on discrete choices of neighborhood and housing. Copyright © 2007 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/jae.977
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File URL: http://qed.econ.queensu.ca:80/jae/2007-v22.6/
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 22 (2007)
Issue (Month): 6 ()
Pages: 1013-1031

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Handle: RePEc:jae:japmet:v:22:y:2007:i:6:p:1013-1031

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References

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  1. Quigley, John M., 2006. "Urban Economics," Berkeley Program on Housing and Urban Policy, Working Paper Series qt0jr0p2tk, Berkeley Program on Housing and Urban Policy.
  2. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, October.
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Cited by:
  1. Kuminoff, Nicolai V. & Parmeter, Christopher F. & Pope, Jaren C., 2010. "Which hedonic models can we trust to recover the marginal willingness to pay for environmental amenities?," Journal of Environmental Economics and Management, Elsevier, vol. 60(3), pages 145-160, November.
  2. Scrogin, David & Hofler, Richard & Boyle, Kevin J. & Milon, J. Walter, 2004. "On The Frontier Of Generating Revealed Preference Choice Sets: An Efficient Approach," 2004 Annual meeting, August 1-4, Denver, CO 20134, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  3. Domanski, Adam, 2009. "Estimating Mixed Logit Recreation Demand Models With Large Choice Sets," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49413, Agricultural and Applied Economics Association.
  4. Phaneuf, Daniel J. & Smith, V. Kerry, 2006. "Recreation Demand Models," Handbook of Environmental Economics, in: K. G. Mäler & J. R. Vincent (ed.), Handbook of Environmental Economics, edition 1, volume 2, chapter 15, pages 671-761 Elsevier.
  5. Kaul, Sapna & Boyle, Kevin J. & Kuminoff, Nicolai V. & Parmeter, Christopher F. & Pope, Jaren C., 2013. "What can we learn from benefit transfer errors? Evidence from 20 years of research on convergent validity," Journal of Environmental Economics and Management, Elsevier, vol. 66(1), pages 90-104.

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