IDEAS home Printed from https://ideas.repec.org/a/kap/qmktec/v3y2005i4p311-335.html
   My bibliography  Save this article

Modeling Simultaneity in Survey Data

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11129-005-0333-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11129-005-0333-3?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    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. 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.
    2. Wuyang Hu, 2008. "Modeling discrete choices with augmented perception hurdles," Agricultural Economics, International Association of Agricultural Economists, vol. 39(2), pages 257-267, September.
    3. 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.

    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. Peter E. Rossi & Greg M. Allenby, 2003. "Bayesian Statistics and Marketing," Marketing Science, INFORMS, vol. 22(3), pages 304-328, July.
    2. Rinus Haaijer & Michel Wedel & Marco Vriens & Tom Wansbeek, 1998. "Utility Covariances and Context Effects in Conjoint MNP Models," Marketing Science, INFORMS, vol. 17(3), pages 236-252.
    3. Timothy J. Gilbride & Greg M. Allenby, 2004. "A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules," Marketing Science, INFORMS, vol. 23(3), pages 391-406, October.
    4. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    5. Geweke, J. & Joel Horowitz & Pesaran, M.H., 2006. "Econometrics: A Bird’s Eye View," Cambridge Working Papers in Economics 0655, Faculty of Economics, University of Cambridge.
    6. Geweke, John F. & Keane, Michael P. & Runkle, David E., 1997. "Statistical inference in the multinomial multiperiod probit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 125-165, September.
    7. Susan Athey & Guido W. Imbens, 2007. "Discrete Choice Models With Multiple Unobserved Choice Characteristics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1159-1192, November.
    8. Kim, Jung Seek & Ratchford, Brian T., 2013. "A Bayesian multivariate probit for ordinal data with semiparametric random-effects," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 192-208.
    9. Marc R. Dotson & Joachim Büschken & Greg M. Allenby, 2020. "Explaining Preference Heterogeneity with Mixed Membership Modeling," Marketing Science, INFORMS, vol. 39(2), pages 407-426, March.
    10. Lynd Bacon & Peter Lenk, 2012. "Augmenting discrete-choice data to identify common preference scales for inter-subject analyses," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 453-474, December.
    11. 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.
    12. Raghuram Iyengar & Asim Ansari & Sunil Gupta, 2003. "Leveraging Information Across Categories," Quantitative Marketing and Economics (QME), Springer, vol. 1(4), pages 425-465, December.
    13. Andrés Musalem & Marcelo Olivares & Eric T. Bradlow & Christian Terwiesch & Daniel Corsten, 2010. "Structural Estimation of the Effect of Out-of-Stocks," Management Science, INFORMS, vol. 56(7), pages 1180-1197, July.
    14. Cohen, Michael, 2010. "A Structured Covariance Probit Demand Model," Research Reports 149970, University of Connecticut, Food Marketing Policy Center.
    15. Tatiana Dyachenko & Rebecca Walker Reczek & Greg M. Allenby, 2014. "Models of Sequential Evaluation in Best-Worst Choice Tasks," Marketing Science, INFORMS, vol. 33(6), pages 828-848, November.
    16. Jorge Silva-Risso & Irina Ionova, 2008. "—A Nested Logit Model of Product and Transaction-Type Choice for Planning Automakers' Pricing and Promotions," Marketing Science, INFORMS, vol. 27(4), pages 545-566, 07-08.
    17. Brownstone, David, 2001. "Discrete Choice Modeling for Transportation," University of California Transportation Center, Working Papers qt29v7d1pk, University of California Transportation Center.
    18. Gould, Brian W. & Dong, Diansheng, 2000. "The Decision Of When To Buy A Frequently Purchased Good: A Multi-Period Probit Model," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-17, December.
    19. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    20. repec:cup:judgdm:v:8:y:2013:i:2:p:136-149 is not listed on IDEAS
    21. Troske, Kenneth R. & Voicu, Alexandru, 2010. "Joint estimation of sequential labor force participation and fertility decisions using Markov chain Monte Carlo techniques," Labour Economics, Elsevier, vol. 17(1), pages 150-169, January.

    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:kap:qmktec:v:3:y:2005:i:4:p:311-335. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.