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Mixed logit estimation of willingness to pay distributions: a comparison of models in preference and WTP space using data from a health-related choice experiment

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  • Arne Hole

    ()

  • Julie Kolstad

    ()

Abstract

Different approaches to modelling the distribution of WTP are compared using stated preference data on Tanzanian Clinical Officers’ job choices and mixed logit models. The standard approach of specifying the distributions of the coefficients and deriving WTP as the ratio of two coefficients estimation in preference space) is compared to specifying the distributions for WTP directly at the estimation stage (estimation in WTP space). The models in preference space fit the data better than the corresponding models in WTP space although the difference between the best fitting models in the two estimation regimes is minimal. Moreover, the willingness to pay estimates derived from the preference space models turn out to be unrealistically high for many of the job attributes. The results suggest that sensitivity testing using a variety of model specifications, including estimation in WTP space, is recommended when using mixed logit models to estimate willingness to pay distributions.

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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 42 (2012)
Issue (Month): 2 (April)
Pages: 445-469

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Handle: RePEc:spr:empeco:v:42:y:2012:i:2:p:445-469

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Related research

Keywords: WTP space; Stated preference methods; Discrete choice; Mixed logit; Willingness to pay; C5; I19; J4;

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References

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Citations

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Cited by:
  1. Anthony Scott & Julia Lane & John Humphreys & Catherine Joyce & Guyonne Kalb & Sung-Hee Jeon & Matthew McGrail, 2012. "Getting Doctors into the Bush: General Practitioners' Preferences for Rural Location," Melbourne Institute Working Paper Series wp2012n13, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  2. Godager, Geir & Wiesen, Daniel, 2011. "Profit or Patients' Health Benefit? Exploring the Heterogeneity in Physician Altruism," HERO On line Working Paper Series 2011:7, Oslo University, Health Economics Research Programme.
  3. Dikgang, Johane & Muchapondwa, Edwin, . "The Economic Valuation of Dryland Ecosystem Services in the South African Kgalagadi by the Local Communities," Discussion Papers dp-13-15-efd, Resources For the Future.
  4. Zhou, Guzhen & Hu, Wuyang & Schieffer, Jack & Robbins, Lynn, 2013. "Public Acceptance of and Willingness to Pay for Nanofood: Case of Canola Oil," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149662, Agricultural and Applied Economics Association.
  5. Crastes, Romain & Beaumais, Olivier & Arkoun, Ouerdia & Laroutis, Dimitri & Mahieu, Pierre-Alexandre & Rulleau, Bénédicte & Hassani-Taibi, Salima & Barbu, Vladimir Stefan & Gaillard, David, 2014. "Erosive runoff events in the European Union: Using discrete choice experiment to assess the benefits of integrated management policies when preferences are heterogeneous," Ecological Economics, Elsevier, vol. 102(C), pages 105-112.
  6. Zander, Kerstin K. & Signorello, Giovanni & De Salvo, Maria & Gandini, Gustavo & Drucker, Adam G., 2013. "Assessing the total economic value of threatened livestock breeds in Italy: Implications for conservation policy," Ecological Economics, Elsevier, vol. 93(C), pages 219-229.
  7. Probst, Lorenz & Houedjofonon, Elysée & Ayerakwa, Hayford Mensah & Haas, Rainer, 2012. "Will they buy it? The potential for marketing organic vegetables in the food vending sector to strengthen vegetable safety: A choice experiment study in three West African cities," Food Policy, Elsevier, vol. 37(3), pages 296-308.

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