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Transition choice probabilities and welfare analysis in random utility models with imperfect before–after correlation

  • Delle Site, Paolo
  • Salucci, Marco Valerio

Welfare in random utility models is used to be analysed on the basis of only the expectation of the compensating variation. De Palma and Kilani (De Palma, A., Kilani, K., 2011. Transition choice probabilities and welfare analysis in additive random utility models. Economic Theory 46(3), 427–454) have developed a framework for conditional welfare analysis which provides analytic expressions of transition choice probabilities and associated welfare measures. The contribution is of practical relevance in transportation because it allows to compute shares of shifters and non-shifters and attribute benefits to them in a rigorous way. In De Palma and Kilani (2011) the usual assumption of unchanged random terms before and after is made.

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Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

Volume (Year): 58 (2013)
Issue (Month): C ()
Pages: 215-242

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Handle: RePEc:eee:transb:v:58:y:2013:i:c:p:215-242
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  1. Paolo Delle Site, 2008. "On the geometry of the consumer's surplus line integral," Economics Bulletin, AccessEcon, vol. 4(6), pages 1-7.
  2. Constant Tra, 2009. "Nonlinear Income Effects in Random Utility Models: Revisiting the Accuracy of the Representative Consumer Approximation," Working Papers 0924, University of Nevada, Las Vegas , Department of Economics.
  3. André Palma & Karim Kilani, 2011. "Transition choice probabilities and welfare analysis in additive random utility models," Economic Theory, Springer, vol. 46(3), pages 427-454, April.
  4. repec:cup:cbooks:9780521766555 is not listed on IDEAS
  5. John K. Dagsvik & Anders Karlstr�m, 2005. "Compensating Variation and Hicksian Choice Probabilities in Random Utility Models that are Nonlinear in Income," Review of Economic Studies, Oxford University Press, vol. 72(1), pages 57-76.
  6. Joseph A. Herriges & Catherine L. Kling, 1999. "Nonlinear Income Effects in Random Utility Models," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 62-72, February.
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  8. Small, Kenneth A & Rosen, Harvey S, 1981. "Applied Welfare Economics with Discrete Choice Models," Econometrica, Econometric Society, vol. 49(1), pages 105-30, January.
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  10. Laurie Garrow & Tudor Bodea & Misuk Lee, 2010. "Generation of synthetic datasets for discrete choice analysis," Transportation, Springer, vol. 37(2), pages 183-202, March.
  11. repec:ebl:ecbull:v:4:y:2008:i:6:p:1-7 is not listed on IDEAS
  12. Delle Site, Paolo, 2013. "Integration of choice probabilities in logit," Economics Letters, Elsevier, vol. 120(1), pages 57-60.
  13. Viton, Philip A., 1985. "On the interpretation of income variables in discrete-choice models," Economics Letters, Elsevier, vol. 17(3), pages 203-206.
  14. Jara-Díaz, Sergio R. & Videla, Jorge, 1989. "Detection of income effect in mode choice: Theory and application," Transportation Research Part B: Methodological, Elsevier, vol. 23(6), pages 393-400, December.
  15. Ruud H Koning & Geert Ridder, 1999. "Discrete Choice and Stochastic Utility Maximization," Economics Working Paper Archive 413, The Johns Hopkins University,Department of Economics.
  16. Jara-Diaz, Sergio R., 1990. "Consumer's surplus and the value of travel time savings," Transportation Research Part B: Methodological, Elsevier, vol. 24(1), pages 73-77, February.
  17. von Haefen, Roger H., 2003. "Incorporating observed choice into the construction of welfare measures from random utility models," Journal of Environmental Economics and Management, Elsevier, vol. 45(2), pages 145-165, March.
  18. Viauroux, Christelle, 2011. "Pricing urban congestion: A structural random utility model with traffic anticipation," European Economic Review, Elsevier, vol. 55(7), pages 877-902.
  19. J. E. Stiglitz, 1999. "Introduction," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 28(3), pages 249-254, November.
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