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The Information Content of a Stated Choice Experiment

Author

Listed:
  • Jan Rouwendal

    (VU University Amsterdam)

  • Arianne de Blaeij

    (LEI, The Hague)

  • Piet Rietveld

    (VU University Amsterdam)

  • Erik Verhoef

    (VU University Amsterdam)

Abstract

This paper presents a method to assess the distribution of values of time, and values of statistical life, over participants to a stated choice experiment, that 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. The method 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.

Suggested Citation

  • Jan Rouwendal & Arianne de Blaeij & Piet Rietveld & Erik Verhoef, 2008. "The Information Content of a Stated Choice Experiment," Tinbergen Institute Discussion Papers 08-053/3, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20080053
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    References listed on IDEAS

    as
    1. Erik Meijer & Jan Rouwendal, 2006. "Measuring welfare effects in models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 227-244, March.
    2. Orley Ashenfelter, 2006. "Measuring the Value of a Statistical Life: Problems and Prospects," Economic Journal, Royal Economic Society, vol. 116(510), pages 10-23, March.
    3. 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 103-130, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

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    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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