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Modeling Disinterest and Dislike: A Bounded Bayesian Mixed Logit Model of the UK Market for GM Food

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  • Dan Rigby
  • Mike Burton

Abstract

Mixed logit models represent a powerful discrete choice analytical model but require assumptions about the functional form of the parameter distributions. The use of unbounded distributions, such as the normal distribution, may be regarded as unsuitable where theory indicates that all are negatively affected by increases in an attribute, such as price. Bounded distributions such as the triangular and log-normal are unable to model the case where a section of the population is indifferent towards an attribute, while the remainder are negatively disposed toward it. Train and Sonnier’s bounded mixed logit model accommodates these features and is employed in this paper. A censored normal and Johnson’s S b distribution are used to model preferences in the UK for food attributes, including price and GM technology. Bi-modal distributions are identified regarding GM food: some are unlikely to ever consume it, some are close to indifference and willing to consume at relatively small discounts while the remainder are fairly unresponsive to further price reductions. Copyright Springer 2006

Suggested Citation

  • Dan Rigby & Mike Burton, 2006. "Modeling Disinterest and Dislike: A Bounded Bayesian Mixed Logit Model of the UK Market for GM Food," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 33(4), pages 485-509, April.
  • Handle: RePEc:kap:enreec:v:33:y:2006:i:4:p:485-509
    DOI: 10.1007/s10640-005-4995-9
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    References listed on IDEAS

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    2. Herriges, Joseph A. & Kling, Catherine L., 1999. "Valuing Recreation and the Environment: Revealed Preference Methods in Theory and Practice, New Horizons in Environmental Economics," Staff General Research Papers Archive 12330, Iowa State University, Department of Economics.
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    Cited by:

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    9. Hasing, Tomas & Carpio, Carlos E. & Willis, David B. & Sydorovych, Olha & Marra, Michele, 2012. "The Effect of Label Information on U.S. Farmers' Herbicide Choices," Agricultural and Resource Economics Review, Cambridge University Press, vol. 41(2), pages 200-214, August.
    10. 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.
    11. David Hensher, 2014. "Attribute processing as a behavioural strategy in choice making," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 12, pages 268-289, Edward Elgar Publishing.
    12. Pluske, Jo & Burton, Michael & Rigby, Dan & Vercoe, Phil, 2013. "Cattle breeding in Northern Australia: Revealing how consumers react to alternative technologies," Australasian Agribusiness Review, University of Melbourne, Department of Agriculture and Food Systems, vol. 21, pages 1-15.
    13. Sarah Wheeler, 2009. "Exploring the influences on Australian agricultural professionals’ genetic engineering beliefs: an empirical analysis," The Journal of Technology Transfer, Springer, vol. 34(4), pages 422-439, August.
    14. Jorge Araña & Carmelo León, 2007. "Repeated Dichotomous Choice Formats for Elicitation of Willingness to Pay: Simultaneous Estimation and Anchoring Effect," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(4), pages 475-497, April.
    15. Bazzani, Claudia & Palma, Marco A. & Nayga, Rodolfo M., Jr., 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), April.
    16. Fontana, Magda & Iori, Martina & Nava, Consuelo Rubina, 2019. "Switching behavior in the Italian electricity retail market: Logistic and mixed effect Bayesian estimations of consumer choice," Energy Policy, Elsevier, vol. 129(C), pages 339-351.
    17. Riccardo Scarpa & Mara Thiene & David A. Hensher, 2010. "Monitoring Choice Task Attribute Attendance in Nonmarket Valuation of Multiple Park Management Services: Does It Matter?," Land Economics, University of Wisconsin Press, vol. 86(4), pages 817-839.
    18. Riccardo Scarpa & Mara Thiene & Francesco Marangon, 2008. "Using Flexible Taste Distributions to Value Collective Reputation for Environmentally Friendly Production Methods," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 56(2), pages 145-162, June.
    19. Michelle Queally & Edel Doherty & Francis Finucane & Ciaran O’Neill, 2020. "Preferences for Weight Loss Treatment Amongst Treatment-Seeking Patients with Severe Obesity: A Discrete Choice Experiment," Applied Health Economics and Health Policy, Springer, vol. 18(5), pages 689-698, October.
    20. Rocamora, Beatriz & Colombo, Sergio & Glenk, Klaus, 2014. "El impacto de las respuestas inconsistentes en las medidas de bienestar estimadas con el método del experimento de elección," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 14(02), pages 1-22, December.
    21. Abildtrup, Jens & Garcia, Serge & Olsen, Søren Bøye & Stenger, Anne, 2013. "Spatial preference heterogeneity in forest recreation," Ecological Economics, Elsevier, vol. 92(C), pages 67-77.
    22. Campbell, Danny & Doherty, Edel & Gibson, Vikki, 2011. "Choosing ‘buy none’ in food choice analysis: the role of utility balance," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108951, Agricultural Economics Society.
    23. Scarborough, Helen & Bennett, Jeff, 2008. "Estimating intergenerational distribution preferences," Ecological Economics, Elsevier, vol. 66(4), pages 575-583, July.
    24. Fosgerau, Mogens & Hess, Stephane, 2009. "A comparison of methods for representing random taste heterogeneity in discrete choice models," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 42, pages 1-25.

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    More about this item

    Keywords

    Bayesian; bounded mixed logit; choice modeling; food safety; GMOs; C11; C24; C25; D12; Q18;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy

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