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Modeling Simultaneity in Survey Data

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  • Timothy Gilbride
  • Sha Yang
  • Greg Allenby

Abstract

Responses to questions in a survey can reflect a behavior process that influences multiple response items. Respondent ratings of brand attributes, for example, can be affected by past purchases by making a brand more salient, or by respondents attributing higher performance to justify their purchases. When multiple response items are influenced by a common underlying process, there is simultaneity in the data. This paper proposes an approach to model the simultaneity in different survey responses by using common parameters and structural relationships motivated by behavioral theories on how consumers respond to surveys. Specifically, the proposed models show how brand usage and attribute perception responses are jointly determined by justification, order, and brand halo effects in two brand positioning studies. We detect a significant tendency for respondents to inflate their reported beliefs for particular brands as well as the selected brand across five countries in an international survey as well as in a domestic study. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Timothy Gilbride & Sha Yang & Greg Allenby, 2005. "Modeling Simultaneity in Survey Data," Quantitative Marketing and Economics (QME), Springer, vol. 3(4), pages 311-335, December.
    • Handle: RePEc:kap:qmktec:v:3:y:2005:i:4:p:311-335
    DOI: 10.1007/s11129-005-0333-3
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    References listed on IDEAS

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    1. Peter E. Rossi & Robert E. McCulloch & Greg M. Allenby, 1996. "The Value of Purchase History Data in Target Marketing," Marketing Science, INFORMS, vol. 15(4), pages 321-340.
    2. Rossi P. E & Gilula Z. & Allenby G. M, 2001. "Overcoming Scale Usage Heterogeneity: A Bayesian Hierarchical Approach," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 20-31, March.
    3. Simonson, Itamar, 1989. "Choice Based on Reasons: The Case of Attraction and Compromise Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(2), pages 158-174, September.
    4. Pettibone, Jonathan C. & Wedell, Douglas H., 2000. "Examining Models of Nondominated Decoy Effects across Judgment and Choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 81(2), pages 300-328, March.
    5. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
    6. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
    7. Peter E. Rossi & Greg M. Allenby, 2003. "Bayesian Statistics and Marketing," Marketing Science, INFORMS, vol. 22(3), pages 304-328, July.
    8. Sha Yang & Yuxin Chen & Greg Allenby, 2003. "Bayesian Analysis of Simultaneous Demand and Supply," Quantitative Marketing and Economics (QME), Springer, vol. 1(3), pages 251-275, September.
    9. Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996. "Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134.
    10. G. S. Maddala & Lung-Fei Lee, 1976. "Recursive Models with Qualitative Endogenous Variables," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 525-545, National Bureau of Economic Research, Inc.
    11. Janiszewski, Chris & Silk, Tim & Cooke, Alan D J, 2003. "Different Scales for Different Frames: The Role of Subjective Scales and Experience in Explaining Attribute-Framing Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(3), pages 311-325, December.
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    Cited by:

    1. Wuyang Hu & Wiktor L. Adamowicz & Michele M. Veeman, 2009. "Consumers' Preferences for GM Food and Voluntary Information Access: A Simultaneous Choice Analysis," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 57(2), pages 241-267, June.
    2. Sha Yang & Yi Zhao & Ravi Dhar, 2010. "Modeling the Underreporting Bias in Panel Survey Data," Marketing Science, INFORMS, vol. 29(3), pages 525-539, 05-06.
    3. Wuyang Hu, 2008. "Modeling discrete choices with augmented perception hurdles," Agricultural Economics, International Association of Agricultural Economists, vol. 39(2), pages 257-267, September.

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