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Bayesian Analysis of Simultaneous Demand and Supply

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Author Info

  • Sha Yang

    ()

  • Yuxin Chen

    ()

  • Greg Allenby

    ()

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    Abstract

    In models of demand and supply, consumer price sensitivity affects both the sales of a good through price, and the price that is set by producers and retailers. The relationship between the dependent variables (e.g., demand and price) and the common parameters (e.g., price sensitivity) is typically non-linear, especially when heterogeneity is present. In this paper, we develop a Bayesian method to address the computational challenge of estimating simultaneous demand and supply models that can be applied to both the analysis of household panel data and aggregated demand data. The method is developed within the context of a heterogeneous discrete choice model coupled with pricing equations derived from either specific competitive structures, or linear equations of the kind used in instrumental variable estimation, and applied to a scanner panel dataset of light beer purchases. Our analysis indicates that incorporating heterogeneity into the demand model all but eliminates the bias in the price parameter due to the endogeneity of price. The analysis also supports the use of a full information analysis. Copyright Kluwer Academic Publishers 2003

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    File URL: http://hdl.handle.net/10.1023/B:QMEC.0000003327.55605.26
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    Bibliographic Info

    Article provided by Springer in its journal Quantitative Marketing and Economics.

    Volume (Year): 1 (2003)
    Issue (Month): 3 (September)
    Pages: 251-275

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    Handle: RePEc:kap:qmktec:v:1:y:2003:i:3:p:251-275

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    Web page: http://www.springerlink.com/link.asp?id=111240

    Related research

    Keywords: discrete choice model; endogeneity; heterogeneity; hierarchical Bayesian analysis;

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    Cited by:
    1. Sudarshan, Anant, 2013. "Deconstructing the Rosenfeld curve: Making sense of California's low electricity intensity," Energy Economics, Elsevier, vol. 39(C), pages 197-207.
    2. Jiang, Renna & Manchanda, Puneet & Rossi, Peter E., 2009. "Bayesian analysis of random coefficient logit models using aggregate data," Journal of Econometrics, Elsevier, vol. 149(2), pages 136-148, April.
    3. Timothy Gilbride & Sha Yang & Greg Allenby, 2005. "Modeling Simultaneity in Survey Data," Quantitative Marketing and Economics, Springer, vol. 3(4), pages 311-335, December.

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