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Biased estimates in discrete choice models: the appropriate inclusion of psychometric data into the valuation of recycled wastewater

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  • Gibson, Fiona L.
  • Burton, Michael P.

Abstract

The introduction of measurement bias in parameter estimates into non-linear discrete choice models, as a result of using factor analysis, was identified by Train et al. (1987). They found that the inclusion of factor scores, used to represent relationships amongst like variables, into a subsequent discrete choice models introduced measurement bias as the measurement error associated with each factor score is excluded. This is an issue for non-market valuation given the increase in popularity of including psychometric data, such as primitive beliefs, attitudes and motivations, in willingness to pay estimates. This study explores the relationship between willingness to pay and primitive beliefs through a case study eliciting Perth community values for drinking recycled wastewater. The standard discrete decision model, with sequential inclusion of factor scores, is compared to an equivalent discrete decision model, which corrects for the measurement bias by simultaneously estimating the underlying latent variables using a measurement model. Previous research has focused on the issue of biased parameters. Here we also consider the implications for willingness to pay estimates.

Suggested Citation

  • Gibson, Fiona L. & Burton, Michael P., 2009. "Biased estimates in discrete choice models: the appropriate inclusion of psychometric data into the valuation of recycled wastewater," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47943, Australian Agricultural and Resource Economics Society.
  • Handle: RePEc:ags:aare09:47943
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    File URL: http://purl.umn.edu/47943
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    1. Train, Kenneth E & McFadden, Daniel L & Goett, Andrew A, 1987. "Consumer Attitudes and Voluntary Rate Schedules for Public Utilities," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 383-391, August.
    2. V. Kerry Smith, 1996. "Can Contingent Valuation Distinguish Economic Values for Different Public Goods?," Land Economics, University of Wisconsin Press, vol. 72(2), pages 139-151.
    3. McCallum, B T, 1972. "Relative Asymptotic Bias from Errors of Omission and Measurement," Econometrica, Econometric Society, vol. 40(4), pages 757-758, July.
    4. Sophia Rabe-Hesketh & Anders Skrondal, 2012. "Multilevel and Longitudinal Modeling Using Stata, 3rd Edition," Stata Press books, StataCorp LP, edition 3, number mimus2, April.
    5. Wang, Liqun, 2002. "A simple adjustment for measurement errors in some limited dependent variable models," Statistics & Probability Letters, Elsevier, vol. 58(4), pages 427-433, July.
    6. Cook, A. J. & Kerr, G. N. & Moore, K., 2002. "Attitudes and intentions towards purchasing GM food," Journal of Economic Psychology, Elsevier, vol. 23(5), pages 557-572, October.
    7. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2003. "Maximum likelihood estimation of generalized linear models with covariate measurement error," Stata Journal, StataCorp LP, vol. 3(4), pages 386-411, December.
    8. Milon, J. Walter & Scrogin, David, 2006. "Latent preferences and valuation of wetland ecosystem restoration," Ecological Economics, Elsevier, vol. 56(2), pages 162-175, February.
    9. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "Generalized multilevel structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 167-190, June.
    10. Kotchen, Matthew J. & Reiling, Stephen D., 2000. "Environmental attitudes, motivations, and contingent valuation of nonuse values: a case study involving endangered species," Ecological Economics, Elsevier, vol. 32(1), pages 93-107, January.
    11. Spash, Clive L. & Urama, Kevin & Burton, Rob & Kenyon, Wendy & Shannon, Peter & Hill, Gary, 2009. "Motives behind willingness to pay for improving biodiversity in a water ecosystem: Economics, ethics and social psychology," Ecological Economics, Elsevier, vol. 68(4), pages 955-964, February.
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    Cited by:

    1. Xuemei Fu & Zhicai Juan, 2017. "Estimation of multinomial probit-kernel integrated choice and latent variable model: comparison on one sequential and two simultaneous approaches," Transportation, Springer, vol. 44(1), pages 91-116, January.

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    Keywords

    discrete choice models; attitudes; factor analysis; measurement models; recycled wastewater;

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