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The role of the reference alternative in the specification of asymmetric discrete choice models

Author

Listed:
  • Lorenzo Masiero

    () (Institute for Economic Research (IRE), Faculty of Economics, University of Lugano, Switzerland)

  • John M. Rose

    () (Institute of Transport and Logistics Studies (ITLS), Faculty of Economics and Business, The University of Sydney, Australia)

Abstract

Within the discrete choice modelling literature, there has been growing interest in including reference alternatives within stated choice survey tasks. Recent studies have investigated asymmetric utility specifications by estimating discrete choice models that include different parameters according to gains and losses relative to the values of the reference attributes. This paper analyses asymmetric discrete choice models by comparing specifications expressed as deviations from the reference point and specifications expressed in absolute values. The results suggest that the selection of the appropriate asymmetric model specification should be based on the type of the stated choice experiment.

Suggested Citation

  • Lorenzo Masiero & John M. Rose, 2011. "The role of the reference alternative in the specification of asymmetric discrete choice models," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 1104, USI Università della Svizzera italiana.
  • Handle: RePEc:lug:wpaper:1104
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    References listed on IDEAS

    as
    1. David Revelt and Kenneth Train., 2000. "Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier," Economics Working Papers E00-274, University of California at Berkeley.
    2. Masiero, Lorenzo & Hensher, David A., 2010. "Analyzing loss aversion and diminishing sensitivity in a freight transport stated choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 349-358, June.
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    5. Hess, Stephane, 2008. "Treatment of reference alternatives in stated choice surveys for air travel choice behaviour," Journal of Air Transport Management, Elsevier, vol. 14(5), pages 275-279.
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    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, December.
    8. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    9. Mauricio Sillano & Juan de Dios Ortúzar, 2005. "Willingness-to-Pay Estimation with Mixed Logit Models: Some New Evidence," Environment and Planning A, , vol. 37(3), pages 525-550, March.
    10. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
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    12. Jeff Brazell & Christopher Diener & Ekaterina Karniouchina & William Moore & Válerie Séverin & Pierre-Francois Uldry, 2006. "The no-choice option and dual response choice designs," Marketing Letters, Springer, vol. 17(4), pages 255-268, December.
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    Cited by:

    1. Ferrari, Paolo, 2014. "The dynamics of modal split for freight transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 163-176.
    2. Sotirios Thanos & Maria Kamargianni & Andreas Schäfer, 2018. "Car Travel Demand: Spillovers and Asymmetric Price Effects in a Spatial Setting," Transportation Science, INFORMS, vol. 52(3), pages 621-636, June.
    3. Punel, Aymeric & Stathopoulos, Amanda, 2017. "Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 18-38.
    4. Ferrari, Paolo, 2015. "Dynamic cost functions and freight transport modal split evolution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 115-134.
    5. Feo-Valero, María & Arencibia, Ana Isabel & Román, Concepción, 2016. "Analyzing discrepancies between willingness to pay and willingness to accept for freight transport attributes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 151-164.
    6. Ferrari, Paolo, 2016. "Instability and dynamic cost elasticities in freight transport systems," Transport Policy, Elsevier, vol. 49(C), pages 226-233.
    7. Hongli Xu & Hai Yang & Jing Zhou & Yafeng Yin, 2017. "A Route Choice Model with Context-Dependent Value of Time," Transportation Science, INFORMS, vol. 51(2), pages 536-548, May.

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    More about this item

    Keywords

    stated choice experiments; reference alternative; preference asymmetry; willingness to pay;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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