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The information content of a stated choice experiment: A new method and its application to the value of a statistical life

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Author Info

  • Rouwendal, Jan
  • de Blaeij, Arianne
  • Rietveld, Piet
  • Verhoef, Erik

Abstract

This paper presents a new method to assess the distribution of values of time, and values of statistical life, over participants to a stated choice experiment. The method does not require the researcher to make an a priori assumption on the type of distribution, as is required for example for mixed logit models. It requires a few assumptions to hold true, namely that the valuations to be determined are constant for each individual, and that respondents make choices according to their preferences. These assumptions allow the derivation of lower and upper bounds on the (cumulative) distribution of the values of interest over respondents, by deriving for each choice set the value(s) for which the respondent would be indifferent between the alternatives offered, and next deriving from the choice actually made the respondent's implied minimum or maximum value(s). We also provide an extension of the method that incorporates the possibility that errors are made. The method is illustrated using data from an experiment investigating the value of time and the value of statistical life. We discuss the possibility to improve the information content of stated choice experiments by optimizing the attribute levels shown to respondents, which is especially relevant because it would help in selecting the appropriate distribution for mixed logit estimates for the same data.

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Bibliographic Info

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

Volume (Year): 44 (2010)
Issue (Month): 1 (January)
Pages: 136-151

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Handle: RePEc:eee:transb:v:44:y:2010:i:1:p:136-151

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Related research

Keywords: Stated preferences Value of a statistical life;

References

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  1. Scarpa, R. & Thiene, M. & Train, K., 2008. "Appendix to Utility in WTP space: a tool to address confounding random scale effects in destination choice to the Alps," American Journal of Agricultural Economics Appendices, Agricultural and Applied Economics Association, vol. 90(4), November.
  2. Foster, Vivien & Mourato, Susana, 2002. "Testing for Consistency in Contingent Ranking Experiments," Journal of Environmental Economics and Management, Elsevier, vol. 44(2), pages 309-328, September.
  3. Richard Blundell & Amanda Gosling & Hidehiko Ichimura & Costas Meghir, 2004. "Changes in the distribution of male and female wages accounting for employment composition using bounds," IFS Working Papers W04/25, Institute for Fiscal Studies.
  4. Meijer, E. & Rouwendal, J., 2000. "Measuring welfare effects in models with random coefficients," Research Report 00F25, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  5. Ashenfelter, Orley, 2006. "Measuring the Value of a Statistical Life: Problems and Prospects," IZA Discussion Papers 1911, Institute for the Study of Labor (IZA).
  6. Garrett Sonnier & Andrew Ainslie & Thomas Otter, 2007. "Heterogeneity distributions of willingness-to-pay in choice models," Quantitative Marketing and Economics, Springer, vol. 5(3), pages 313-331, September.
  7. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
  8. Matzkin, Rosa L, 1992. "Nonparametric and Distribution-Free Estimation of the Binary Threshold Crossing and the Binary Choice Models," Econometrica, Econometric Society, vol. 60(2), pages 239-70, March.
  9. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521586115.
  10. Riccardo Scarpa & Danny Campbell & W. George Hutchinson, 2007. "Benefit Estimates for Landscape Improvements: Sequential Bayesian Design and Respondents’ Rationality in a Choice Experiment," Land Economics, University of Wisconsin Press, vol. 83(4), pages 617-634.
  11. Balcombe, Kelvin & Chalak, Ali & Fraser, Iain, 2009. "Model selection for the mixed logit with Bayesian estimation," Journal of Environmental Economics and Management, Elsevier, vol. 57(2), pages 226-237, March.
  12. Dan Rigby & Kelvin Balcombe & Michael Burton, 2009. "Mixed Logit Model Performance and Distributional Assumptions: Preferences and GM foods," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 42(3), pages 279-295, March.
  13. Loomes, Graham & Moffatt, Peter G & Sugden, Robert, 2002. " A Microeconometric Test of Alternative Stochastic Theories of Risky Choice," Journal of Risk and Uncertainty, Springer, vol. 24(2), pages 103-30, March.
  14. Riccardo Scarpa & Mara Thiene & Kenneth Train, 2008. "Utility in Willingness to Pay Space: A Tool to Address Confounding Random Scale Effects in Destination Choice to the Alps," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 994-1010.
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Cited by:
  1. Bliemer, Michiel C.J. & Rose, John M., 2011. "Experimental design influences on stated choice outputs: An empirical study in air travel choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 63-79, January.
  2. Börjesson, Maria & Eliasson, Jonas, 2012. "Experiences from the Swedish Value of Time study," Working papers in Transport Economics 2012:8, CTS - Centre for Transport Studies Stockholm (KTH and VTI).

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