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Capturing Preference Heterogeneity in Stated Choice Models: A Random Parameter Logit Model of the Demand for GM Food

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  • Rigby, Dan
  • Burton, Michael P.

Abstract

Analyses of data from random utility models of choice data have typically used fixed parameter representations, with consumer heterogeneity introduced by including factors such as the age, gender etc of the respondent. However, there is a class of models that assume that the underlying parameters of the estimated model (and hence preferences) are different for each individual within the sample, and that choices can be explained by identifying the parameters of the distribution from which they are drawn. Such a random parameter model is applied to stated choice data from the UK, and the results compared with standard fixed parameter models. The results provide new evidence of preferences for various aspects of the UK food system, particularly in relation to GM food but other environmental and technical aspects also. Indications of how random parameter models might be developed further are discussed on the basis of these results.

Suggested Citation

  • Rigby, Dan & Burton, Michael P., 2003. "Capturing Preference Heterogeneity in Stated Choice Models: A Random Parameter Logit Model of the Demand for GM Food," 2003 Conference (47th), February 12-14, 2003, Fremantle, Australia 58200, Australian Agricultural and Resource Economics Society.
  • Handle: RePEc:ags:aare03:58200
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    File URL: http://ageconsearch.umn.edu/record/58200/files/2003_rigbyburton.pdf
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    References listed on IDEAS

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    1. Rousu, Matthew C. & Huffman, Wallace E. & Shogren, Jason F. & Tegene, Abebayehu, 2002. "The Value Of Verificable Information In A Controversial Market: Evidence From Lab Auctions Of Genetically Modified Food," Working Papers 18212, Iowa State University, Department of Economics.
    2. Lusk, Jayson L. & Daniel, M. Scott & Mark, Darrell R. & Lusk, Christine L., 2001. "Alternative Calibration And Auction Institutions For Predicting Consumer Willingess To Pay For Nongenetically Modified Corn Chips," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 0(Number 1), pages 1-18, July.
    3. Baker, Gregory A. & Burnham, Thomas A., 2001. "Consumer Response To Genetically Modified Foods: Market Segment Analysis And Implications For Producers And Policy Makers," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 26(2), pages 1-17, December.
    4. Huffman, Wallace E. & Tegene, Abebayehu, 2002. "Public Acceptance of and Benefits from Agricultural Biotechnology: A Key Role for Verifiable Information," Staff General Research Papers Archive 10430, Iowa State University, Department of Economics.
    5. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    6. Boccaletti, Stefano & Nardella, Michele, 2000. "Consumer Willingness To Pay For Pesticide-Free Fresh Fruit And Vegetables In Italy," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 3(3), pages 1-14.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, August.
    8. Peter Boxall & Wiktor Adamowicz, 2002. "Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(4), pages 421-446, December.
    9. Huffman, Wallace E. & Shogren, Jason F. & Rousu, Matthew & Tegene, Abe, 2001. "The Value of Consumers of Genetically Modified Food Labels in a Market with Diverse Information: Evidence from Experimental Auctions," ISU General Staff Papers 200112010800001346, Iowa State University, Department of Economics.
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    Cited by:

    1. Camarena-Gomez, Dena M. & Sanjuan, Ana Isabel, 2005. "Walnut Preferences in Spain: Is the Spanish Consumer Ready for New Varieties?," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24749, European Association of Agricultural Economists.
    2. repec:gam:jsusta:v:9:y:2017:i:9:p:1672-:d:112599 is not listed on IDEAS
    3. Mike Fitzpatrick & Christos D. Maravelias & Ole Ritzau Eigaard & Stephen Hynes & David Reid, 2014. "Modelling FIshers' preferences for alternative management options under the Common Fisheries Policy," Working Papers 262565, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
    4. repec:oup:revage:v:30:y:2008:i:4:p:692-710. is not listed on IDEAS
    5. Jesús Barreiro-Hurlé & José Gómez-Limón, 2008. "Reconsidering Heterogeneity and Aggregation Issues in Environmental Valuation: A Multi-attribute Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 40(4), pages 551-570, August.
    6. Edel Doherty & Brendan Kennelly & Darragh Flannery & Stephen Kynes & John Considine, 2013. "Student preferences for assignment systems: Results from a discrete choice experiment in Irish universities," Working Papers WP052013, University of Limerick, Department of Economics, revised Sep 2013.
    7. Kaye-Blake, William & Bicknell, Kathryn & Saunders, Caroline M., 2005. "Process versus product: which determines consumer demand for genetically modified apples?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 49(4), pages 1-15.
    8. Doherty, Edel & Campbell, Danny, 2011. "Demand for improved food safety and quality: a cross-regional comparison," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108791, Agricultural Economics Society.
    9. William H. Kaye-Blake & Caroline M. Saunders & Selim Cagatay, 2008. "Genetic Modification Technology and Producer Returns: The Impacts of Productivity, Preferences, and Technology Uptake," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 30(4), pages 692-710.

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