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On the use of flexible mixing distributions in WTP space: an induced value choice experiment

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  • Claudia Bazzani
  • Marco A. Palma
  • Rodolfo M. Nayga

Abstract

In this study, we use data from an induced value choice experiment to compare estimates from mixed logit models in willingness to pay (WTP) space using different parameter distributional assumptions. Specifically, we test differences in WTP estimates when using flexible parameter mixing distributions (i.e. Legendre polynomials, step functions and splines) and conventional parameter distributions (normal and lognormal). Similar WTP estimates are obtained. However, we observe that WTP estimates are statistically different from the induced value when conventional distributions are assumed, but they are not when more flexible distributions are assumed. This suggests that flexible distributions can provide more reliable WTP estimates.

Suggested Citation

  • Claudia Bazzani & Marco A. Palma & Rodolfo M. Nayga, 2018. "On the use of flexible mixing distributions in WTP space: an induced value choice experiment," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), pages 185-198, April.
    • Handle: RePEc:bla:ajarec:v:62:y:2018:i:2:p:185-198
    DOI: 10.1111/1467-8489.12246
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    Cited by:

    1. Fraser, Iain & Balcombe, Kelvin & Williams, Louis & McSorley, Eugene, 2021. "Preference stability in discrete choice experiments. Some evidence using eye-tracking," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 94(C).
    2. Lang, Ghislaine & Farsi, Mehdi & Lanz, Bruno & Weber, Sylvain, 2021. "Energy efficiency and heating technology investments: Manipulating financial information in a discrete choice experiment," Resource and Energy Economics, Elsevier, vol. 64(C).
    3. Riccardo Scarpa & Cristiano Franceschinis & Mara Thiene, 2021. "Logit Mixed Logit Under Asymmetry and Multimodality of WTP: A Monte Carlo Evaluation," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 643-662, March.
    4. J. Ross Pruitt & Kaitlyn M. Melton & Marco A. Palma, 2021. "Does Physical Activity Influence Consumer Acceptance of Gene Edited Food?," Sustainability, MDPI, vol. 13(14), pages 1-12, July.
    5. Pellegrini, Andrea & Lombardi, Ginevra Virginia & Scarpa, Riccardo & Rose, John M., 2024. "A nonparametric random effects model for the valuation of forest recreation services: An application to forest sites in Tuscany, Italy," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 68(02), January.
    6. Sergio Colombo & Wiktor Budziński & Mikołaj Czajkowski & Klaus Glenk, 2022. "The relative performance of ex‐ante and ex‐post measures to mitigate hypothetical and strategic bias in a stated preference study," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 845-873, September.
    7. I. G. Ukpong & K. G. Balcombe & I. M. Fraser & F. J. Areal, 2019. "Preferences for Mitigation of the Negative Impacts of the Oil and Gas Industry in the Niger Delta Region of Nigeria," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(2), pages 811-843, October.
    8. Bansal, Prateek & Hurtubia, Ricardo & Tirachini, Alejandro & Daziano, Ricardo A., 2019. "Flexible estimates of heterogeneity in crowding valuation in the New York City subway," Journal of choice modelling, Elsevier, vol. 31(C), pages 124-140.
    9. Marco A. Palma & Myriah D. Johnson & David P. Anderson, 2019. "The effects of experience versus description of attributes on willingness‐to‐pay for beefsteaks," Agricultural Economics, International Association of Agricultural Economists, vol. 50(2), pages 129-137, March.
    10. Pulkit Marwah & Yu Yvette Zhang & Mengmeng Gu, 2022. "Impacts of Crapemyrtle Bark Scale on Consumers and the Horticulture Industry," Sustainability, MDPI, vol. 14(3), pages 1-11, February.
    11. Black, Michael A. & Ahmadiani, Mona & Bagnall, Dianna K. & Morgan, Cristine L.S. & Ogieriakhi, Macson & Woodward, Richard T., 2025. "Discrete choice experiment estimates on the value of soil health attributes in Central Texas," Ecological Economics, Elsevier, vol. 235(C).
    12. Sergio Colombo & Wiktor Budziński & Mikołaj Czajkowski & Klaus Glenk, 2020. "Ex-ante and ex-post measures to mitigate hypothetical bias. Are they alternative or complementary tools to increase the reliability and validity of DCE estimates?," Working Papers 2020-20, Faculty of Economic Sciences, University of Warsaw.
    13. Caputo, Vincenzina & Scarpa, Riccardo & Nayga, Rodolfo M. & Ortega, David L., 2018. "Are preferences for food quality attributes really normally distributed? An analysis using flexible mixing distributions," Journal of choice modelling, Elsevier, vol. 28(C), pages 10-27.

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