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How wrong can you be, without noticing? Further evidence on speci cation errors in the Conditional Logit

  • Tomás del Barrio Casto

    (University of the Balearic Islands, Palma de Mallorca)

  • William Nilsson

    (University of the Balearic Islands, Palma de Mallorca)

  • Andrés J. Picazo-Tadeo

    (University of Valencia)

Discrete choice models such as the conditional logit model are widely used tools in applied econometrics and, particularly, in the eld of environmental valuation and welfare measurement in order to provide policymakers with sound information for making strategic choices. Monte Carlo simulations are used in this study to analyze biases due to omitted relevant variables and functional form misspeci cation in the conditional logit model. Using an easy-to-estimate speci cation test is effective to reduce the risks for large biases. One somewhat discouraging result is, however, that a moderate bias can be found even when the omitted variable is orthogonal to the explanatory variables included. This result is particularly interesting considering the increasing interest in using randomized experiments to obtain causal interpretations of key parameters. Randomization, with independence between included and omitted variables, does not guarantee unbiased estimates in the conditional logit model.

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File URL: ftp://147.156.210.157/RePEc/pdf/eec_1318.pdf
File Function: First version, 2013
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Paper provided by Department of Applied Economics II, Universidad de Valencia in its series Working Papers with number 1318.

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Length: 48 pages
Date of creation: Jul 2013
Date of revision:
Handle: RePEc:eec:wpaper:1318
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  1. Torres, Cati & Hanley, Nick & Riera, Antoni, 2011. "How wrong can you be? Implications of incorrect utility function specification for welfare measurement in choice experiments," Journal of Environmental Economics and Management, Elsevier, vol. 62(1), pages 111-121, July.
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  3. Mauricio Sillano & Juan de Dios Ort�zar, 2005. "Willingness-to-pay estimation with mixed logit models: some new evidence," Environment and Planning A, Pion Ltd, London, vol. 37(3), pages 525-550, March.
  4. Nick Hanley & Robert Wright & Vic Adamowicz, 1998. "Using Choice Experiments to Value the Environment," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 11(3), pages 413-428, April.
  5. Kosenius, Anna-Kaisa, 2010. "Heterogeneous preferences for water quality attributes: The Case of eutrophication in the Gulf of Finland, the Baltic Sea," Ecological Economics, Elsevier, vol. 69(3), pages 528-538, January.
  6. Westerberg, Vanja Holmquist & Lifran, Robert & Olsen, Søren Bøye, 2010. "To restore or not? A valuation of social and ecological functions of the Marais des Baux wetland in Southern France," Ecological Economics, Elsevier, vol. 69(12), pages 2383-2393, October.
  7. Hanley, Nick & Mourato, Susana & Wright, Robert E, 2001. " Choice Modelling Approaches: A Superior Alternative for Environmental Valuation?," Journal of Economic Surveys, Wiley Blackwell, vol. 15(3), pages 435-62, July.
  8. Esmeralda A. Ramalho & Joaquim J. S. Ramalho, 2012. "Alternative Versions of the RESET Test for Binary Response Index Models: A Comparative Study," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(1), pages 107-130, 02.
  9. Adamowicz W. & Louviere J. & Williams M., 1994. "Combining Revealed and Stated Preference Methods for Valuing Environmental Amenities," Journal of Environmental Economics and Management, Elsevier, vol. 26(3), pages 271-292, May.
  10. Murdock, Jennifer, 2006. "Handling unobserved site characteristics in random utility models of recreation demand," Journal of Environmental Economics and Management, Elsevier, vol. 51(1), pages 1-25, January.
  11. Manski, Charles F, 1999. "Analysis of Choice Expectations in Incomplete Scenarios," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 49-66, December.
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