IDEAS home Printed from https://ideas.repec.org/p/ags/aaea05/19296.html
   My bibliography  Save this paper

Bayesian Analysis of Consumer Choices with Taste, Context, Reference Point and Individual Scale Effects

Author

Listed:
  • Hu, Wuyang
  • Adamowicz, Wiktor L.
  • Veeman, Michele M.

Abstract

This paper adopts an approach based on the concepts of random utility maximization and builds on the general theoretical framework of Lancaster and on the conceptual and econometric innovations of McFadden. Recent research in this area explores models that account for context effects, as well as methods for characterizing heterogeneity, response variability and decision strategy selection by consumers. This makes it possible to construct much richer empirical models of individual consumer behavior. A Bayesian approach provides a useful way to estimate and interpret models that are difficult to accomplish by conventional maximization/minimization algorithms. The application reported in the paper involves analysis of reference dependence and product labeling as context effects and the assessment of heterogeneity and response variability.

Suggested Citation

  • Hu, Wuyang & Adamowicz, Wiktor L. & Veeman, Michele M., 2005. "Bayesian Analysis of Consumer Choices with Taste, Context, Reference Point and Individual Scale Effects," 2005 Annual meeting, July 24-27, Providence, RI 19296, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea05:19296
    DOI: 10.22004/ag.econ.19296
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/19296/files/sp05hu02.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.19296?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643.
    3. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    5. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    6. Brock,W.A. & Durlauf,S.N., 2003. "Multinomial choice with social interactions," Working papers 1, Wisconsin Madison - Social Systems.
    7. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    8. McFadden, Daniel, 1999. "Rationality for Economists?," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 73-105, December.
    9. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth & Börsch-Supan, Axel, 2002. "Hybrid Choice Models: Progress and Challenges," Sonderforschungsbereich 504 Publications 02-29, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    10. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    11. Hu, Wuyang & Adamowicz, Wiktor L. & Veeman, Michele M., 2004. "Decomposing Unobserved Choice Variability In The Presence Of Consumers' Taste Heterogeneity," 2004 Annual meeting, August 1-4, Denver, CO 19954, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    12. Bera, Anil K. & Bilias, Yannis, 2002. "The MM, ME, ML, EL, EF and GMM approaches to estimation: a synthesis," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 51-86, March.
    13. Charles F. Manski, 2000. "Economic Analysis of Social Interactions," Journal of Economic Perspectives, American Economic Association, vol. 14(3), pages 115-136, Summer.
    14. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
    15. Elrod, Terry & Keane, Michael, 1995. "A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data," MPRA Paper 52434, University Library of Munich, Germany.
    16. Daniel McFadden, 2001. "Economic Choices," American Economic Review, American Economic Association, vol. 91(3), pages 351-378, June.
    17. Louviere, Jordan J, 2001. "What If Consumer Experiments Impact Variances as Well as Means? Response Variability as a Behavioral Phenomenon," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(3), pages 506-511, December.
    18. Kenneth A. Baerenklau, 2005. "Toward an Understanding of Technology Adoption: Risk, Learning, and Neighborhood Effects," Land Economics, University of Wisconsin Press, vol. 81(1).
    19. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    20. John A. List, 2004. "Neoclassical Theory Versus Prospect Theory: Evidence from the Marketplace," Econometrica, Econometric Society, vol. 72(2), pages 615-625, March.
    21. Allenby, Greg M. & Rossi, Peter E., 1998. "Marketing models of consumer heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 57-78, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mahmud, Asif & Gayah, Vikash V. & Paleti, Rajesh, 2022. "A latent choice model to analyze the role of preliminary preferences in shaping observed choices," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 95-108.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    2. Michael P. Keane & Nada Wasi, 2013. "The Structure of Consumer Taste Heterogeneity in Revealed vs. Stated Preference Data," Economics Papers 2013-W10, Economics Group, Nuffield College, University of Oxford.
    3. Hu, Wuyang & Adamowicz, Wiktor L. & Veeman, Michele M., 2004. "Decomposing Unobserved Choice Variability In The Presence Of Consumers' Taste Heterogeneity," 2004 Annual meeting, August 1-4, Denver, CO 19954, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Michael P. Keane, 2013. "Panel data discrete choice models of consumer demand," Economics Papers 2013-W08, Economics Group, Nuffield College, University of Oxford.
    5. Yoo, Do-il, 2012. "Individual and Social Learning in Bio-technology Adoption: The Case of GM Corn in the U.S," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124975, Agricultural and Applied Economics Association.
    6. Joan L. Walker & Moshe Ben-Akiva, 2011. "Advances in Discrete Choice: Mixture Models," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 8, Edward Elgar Publishing.
    7. Keane, Michael P. & Wasi, Nada, 2016. "How to model consumer heterogeneity? Lessons from three case studies on SP and RP data," Research in Economics, Elsevier, vol. 70(2), pages 197-231.
    8. Stephane Hess & Andrew Daly & Richard Batley, 2018. "Revisiting consistency with random utility maximisation: theory and implications for practical work," Theory and Decision, Springer, vol. 84(2), pages 181-204, March.
    9. Daniel L. McFadden, 2013. "The New Science of Pleasure," NBER Working Papers 18687, National Bureau of Economic Research, Inc.
    10. Andy S. Choi & Kelly S. Fielding, 2016. "Cultural Attitudes as WTP Determinants: A Revised Cultural Worldview Scale," Sustainability, MDPI, vol. 8(6), pages 1-18, June.
    11. Choi, Andy S., 2013. "Nonmarket values of major resources in the Korean DMZ areas: A test of distance decay," Ecological Economics, Elsevier, vol. 88(C), pages 97-107.
    12. Jianhua Wang & Jiaye Ge & Yuting Ma, 2018. "Urban Chinese Consumers’ Willingness to Pay for Pork with Certified Labels: A Discrete Choice Experiment," Sustainability, MDPI, vol. 10(3), pages 1-14, February.
    13. Johanna Lena Dahlhausen & Cam Rungie & Jutta Roosen, 2018. "Value of labeling credence attributes—common structures and individual preferences," Agricultural Economics, International Association of Agricultural Economists, vol. 49(6), pages 741-751, November.
    14. Daziano, Ricardo A., 2015. "Inference on mode preferences, vehicle purchases, and the energy paradox using a Bayesian structural choice model," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 1-26.
    15. Hong Fu & Yuehua Zhang & Yinuo An & Li Zhou & Yanling Peng & Rong Kong & Calum G. Turvey, 2022. "Subjective and objective risk perceptions and the willingness to pay for agricultural insurance: evidence from an in-the-field choice experiment in rural China," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 47(1), pages 98-121, March.
    16. William Greene, 2007. "Discrete Choice Modeling," Working Papers 07-6, New York University, Leonard N. Stern School of Business, Department of Economics.
    17. Krucien, Nicolas & Ryan, Mandy & Hermens, Frouke, 2017. "Visual attention in multi-attributes choices: What can eye-tracking tell us?," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 251-267.
    18. Daniel McFadden, 2014. "The new science of pleasure: consumer choice behavior and the measurement of well-being," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 2, pages 7-48, Edward Elgar Publishing.
    19. Daniel Ackerberg, 2009. "A new use of importance sampling to reduce computational burden in simulation estimation," Quantitative Marketing and Economics (QME), Springer, vol. 7(4), pages 343-376, December.
    20. Thomas Lundhede & Jette Bredahl Jacobsen & Nick Hanley & Niels Strange & Bo Jellesmark Thorsen, 2015. "Incorporating Outcome Uncertainty and Prior Outcome Beliefs in Stated Preferences," Land Economics, University of Wisconsin Press, vol. 91(2), pages 296-316.

    More about this item

    Keywords

    Consumer/Household Economics;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea05:19296. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.