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Observational Learning and Demand for Search Goods

Author

Listed:
  • Kenneth Hendricks
  • Alan Sorensen
  • Thomas Wiseman

Abstract

We develop a model of herds in which consumers observe only the aggregate purchase history, not the complete ordered history of search actions. We show that the purchasing information changes the conditions under which herds can occur for both low- and high-quality products. Inferior products are certain to be ignored; high quality products may be ignored, but complete learning may also occur. We obtain closed form solutions for the probabilities of these events and conduct comparative statics. We test the model's predictions using data from an online music market created by Salganik, Dodds, and Watts (2006). (JEL D11, D12, L82)

Suggested Citation

  • Kenneth Hendricks & Alan Sorensen & Thomas Wiseman, 2012. "Observational Learning and Demand for Search Goods," American Economic Journal: Microeconomics, American Economic Association, vol. 4(1), pages 1-31, February.
  • Handle: RePEc:aea:aejmic:v:4:y:2012:i:1:p:1-31
    Note: DOI: 10.1257/mic.4.1.1
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    Citations

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    Cited by:

    1. Herrera, Helios & Hörner, Johannes, 2013. "Biased social learning," Games and Economic Behavior, Elsevier, vol. 80(C), pages 131-146.
    2. Matthew Grennan & Ashley Swanson, 2016. "Transparency and Negotiated Prices: The Value of Information in Hospital-Supplier Bargaining," NBER Working Papers 22039, National Bureau of Economic Research, Inc.
    3. Ken Hendricks & Alan Sorensen, 2009. "Information and the Skewness of Music Sales," Journal of Political Economy, University of Chicago Press, vol. 117(2), pages 324-369, April.
    4. Jin-Hyuk Kim & Peter Newberry & Calvin Qiu, 2015. "An Empirical Analysis of a Crowdfunding Platform," Working Papers 15-12, NET Institute.
    5. Song, Yangbo, 2016. "Social learning with endogenous observation," Journal of Economic Theory, Elsevier, vol. 166(C), pages 324-333.
    6. Monzón, Ignacio & Rapp, Michael, 2014. "Observational learning with position uncertainty," Journal of Economic Theory, Elsevier, vol. 154(C), pages 375-402.
    7. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2016. "Empirical Models of Learning Dynamics: A Survey of Recent Developments," Economics Papers 2016-W12, Economics Group, Nuffield College, University of Oxford.
    8. Babur De los Santos & Sergei Koulayev, 2012. "Optimizing Click-through in Online Rankings for Partially Anonymous Consumers," Working Papers 2012-04, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    9. repec:eee:iepoli:v:40:y:2017:i:c:p:26-40 is not listed on IDEAS
    10. Kaufman, Noah, 2014. "Overcoming the barriers to the market performance of green consumer goods," Resource and Energy Economics, Elsevier, vol. 36(2), pages 487-507.
    11. Nakajima, Daisuke & Masatlioglu, Yusufcan, 2013. "Choice by iterative search," Theoretical Economics, Econometric Society, vol. 8(3), September.
    12. Sandro Shelegia & Daniel Garcia, 2015. "Consumer Search with Observational Learning," Vienna Economics Papers 1502, University of Vienna, Department of Economics.

    More about this item

    JEL classification:

    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media

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