IDEAS home Printed from https://ideas.repec.org/p/cwl/cwldpp/2224.html
   My bibliography  Save this paper

Search, Information, and Prices

Author

Listed:

Abstract

Consider a market with many identical firms offering a homogeneous good. A consumer obtains price quotes from a subset of firms and buys from the firm offering the lowest price. The "price count" is the number of firms from which the consumer obtains a quote. For any given ex ante distribution of the price count, we obtain a tight upper bound (under first-order stochastic dominance) on the equilibrium distribution of sale prices. The bound holds across all models of firms' common-prior higher-order beliefs about the price count, including the extreme cases of complete information ( firms know the price count exactly) and no information ( firms only know the ex ante distribution of the price count). A qualitative implication of our results is that even a small ex ante probability that the price count is one can lead to dramatic increases in the expected price. The bound also applies in a wide class of models where the price count distribution is endogenized, including models of simultaneous and sequential consumer search.

Suggested Citation

  • Dirk Bergemann & Benjamin Brooks & Stephen Morris, 2020. "Search, Information, and Prices," Cowles Foundation Discussion Papers 2224, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:2224
    as

    Download full text from publisher

    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d22/d2224.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dirk Bergemann & Stephen Morris, 2013. "Robust Predictions in Games With Incomplete Information," Econometrica, Econometric Society, vol. 81(4), pages 1251-1308, July.
    2. Varian, Hal R, 1980. "A Model of Sales," American Economic Review, American Economic Association, vol. 70(4), pages 651-659, September.
    3. Geoffroy de Clippel & Kfir Eliaz & Kareen Rozen, 2014. "Competing for Consumer Inattention," Journal of Political Economy, University of Chicago Press, vol. 122(6), pages 1203-1234.
    4. Benjamin Lester & Ali Shourideh & Venky Venkateswaran & Ariel Zetlin-Jones, 2019. "Screening and Adverse Selection in Frictional Markets," Journal of Political Economy, University of Chicago Press, vol. 127(1), pages 338-377.
    5. Abrantes-Metz, Rosa M. & Froeb, Luke M. & Geweke, John & Taylor, Christopher T., 2006. "A variance screen for collusion," International Journal of Industrial Organization, Elsevier, vol. 24(3), pages 467-486, May.
    6. Narasimhan, Chakravarthi, 1988. "Competitive Promotional Strategies," The Journal of Business, University of Chicago Press, vol. 61(4), pages 427-449, October.
    7. Baye, Michael R. & Kovenock, Dan & de Vries, Casper G., 1992. "It takes two to tango: Equilibria in a model of sales," Games and Economic Behavior, Elsevier, vol. 4(4), pages 493-510, October.
    8. repec:cwl:cwldpp:1821rrr is not listed on IDEAS
    9. Hanming Fang & Stephen Morris, 2012. "Multidimensional Private Value Auctions," World Scientific Book Chapters, in: Robust Mechanism Design The Role of Private Information and Higher Order Beliefs, chapter 9, pages 319-356, World Scientific Publishing Co. Pte. Ltd..
    10. Rothschild, Michael, 1973. "Models of Market Organization with Imperfect Information: A Survey," Journal of Political Economy, University of Chicago Press, vol. 81(6), pages 1283-1308, Nov.-Dec..
    11. Laura Doval & Jeffrey C. Ely, 2020. "Sequential Information Design," Econometrica, Econometric Society, vol. 88(6), pages 2575-2608, November.
    12. Helmuts Āzacis & Péter Vida, 2015. "Collusive communication schemes in a first-price auction," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 58(1), pages 125-160, January.
    13. Michael R. Baye & John Morgan, 2001. "Information Gatekeepers on the Internet and the Competitiveness of Homogeneous Product Markets," American Economic Review, American Economic Association, vol. 91(3), pages 454-474, June.
    14. Patrick Bajari & Lixin Ye, 2003. "Deciding Between Competition and Collusion," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 971-989, November.
    15. Babur De Los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2012. "Testing Models of Consumer Search Using Data on Web Browsing and Purchasing Behavior," American Economic Review, American Economic Association, vol. 102(6), pages 2955-2980, October.
    16. David P. Myatt, 2019. "A Theory of Stable Price Dispersion," Economics Series Working Papers 873, University of Oxford, Department of Economics.
    17. Ilya Segal & Michael D. Whinston, 2003. "Robust Predictions for Bilateral Contracting with Externalities," Econometrica, Econometric Society, vol. 71(3), pages 757-791, May.
    18. Stahl, Dale O, II, 1989. "Oligopolistic Pricing with Sequential Consumer Search," American Economic Review, American Economic Association, vol. 79(4), pages 700-712, September.
    19. Janssen, Maarten C.W. & Moraga-Gonzalez, Jose Luis & Wildenbeest, Matthijs R., 2005. "Truly costly sequential search and oligopolistic pricing," International Journal of Industrial Organization, Elsevier, vol. 23(5-6), pages 451-466, June.
    20. Glenn Ellison & Alexander Wolitzky, 2012. "A search cost model of obfuscation," RAND Journal of Economics, RAND Corporation, vol. 43(3), pages 417-441, September.
    21. Armstrong, Mark & Vickers, John, 2001. "Competitive Price Discrimination," RAND Journal of Economics, The RAND Corporation, vol. 32(4), pages 579-605, Winter.
    22. Glenn Ellison & Sara Fisher Ellison, 2009. "Search, Obfuscation, and Price Elasticities on the Internet," Econometrica, Econometric Society, vol. 77(2), pages 427-452, March.
    23. Burdett, Kenneth & Judd, Kenneth L, 1983. "Equilibrium Price Dispersion," Econometrica, Econometric Society, vol. 51(4), pages 955-969, July.
    24. Michael R. Baye & John Morgan & Patrick Scholten, 2006. "Information, Search, and Price Dispersion," Working Papers 2006-11, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    25. Diamond, Peter A., 1971. "A model of price adjustment," Journal of Economic Theory, Elsevier, vol. 3(2), pages 156-168, June.
    26. Han Hong & Matthew Shum, 2006. "Using price distributions to estimate search costs," RAND Journal of Economics, RAND Corporation, vol. 37(2), pages 257-275, June.
    27. Gerard R. Butters, 1977. "Equilibrium Distributions of Sales and Advertising Prices," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 44(3), pages 465-491.
    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. Mark Armstrong & Jidong Zhou, 2022. "Consumer Information and the Limits to Competition," American Economic Review, American Economic Association, vol. 112(2), pages 534-577, February.
    2. Bonatti, Alessandro & Bergemann, Dirk, 2022. "Data, Competition, and Digital Platforms," CEPR Discussion Papers 17544, C.E.P.R. Discussion Papers.
    3. Mark Armstrong & John Vickers, 2022. "Patterns of Competitive Interaction," Econometrica, Econometric Society, vol. 90(1), pages 153-191, January.
    4. Vickers, John, 2021. "Competition for imperfect consumers," International Journal of Industrial Organization, Elsevier, vol. 79(C).
    5. Dirk Bergemann & Benjamin Brooks & Stephen Morris, 2020. "Competition and Public Information: A Note," Cowles Foundation Discussion Papers 2234, Cowles Foundation for Research in Economics, Yale University.
    6. Brian C. Albrecht & Mark Whitmeyer, 2023. "Comparison Shopping: Learning Before Buying From Duopolists," Papers 2302.06580, arXiv.org, revised Apr 2023.
    7. Groh, Carl-Christian, 2023. "Search, Data, and Market Power," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277701, Verein für Socialpolitik / German Economic Association.

    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. Xulia González & Daniel Miles-Touya, 2018. "Price dispersion, chain heterogeneity, and search in online grocery markets," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(1), pages 115-139, March.
    2. Hämäläinen, Saara, 2018. "Competitive search obfuscation," Journal of Economic Dynamics and Control, Elsevier, vol. 97(C), pages 38-63.
    3. Wilson, Chris M., 2010. "Ordered search and equilibrium obfuscation," International Journal of Industrial Organization, Elsevier, vol. 28(5), pages 496-506, September.
    4. Mark Armstrong & John Vickers, 2022. "Patterns of Competitive Interaction," Econometrica, Econometric Society, vol. 90(1), pages 153-191, January.
    5. Backus, Matthew R. & Podwol, Joseph Uri & Schneider, Henry S., 2014. "Search costs and equilibrium price dispersion in auction markets," European Economic Review, Elsevier, vol. 71(C), pages 173-192.
    6. David Ronayne, 2021. "Price Comparison Websites," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(3), pages 1081-1110, August.
    7. Maarten Janssen & Paul Pichler & Simon Weidenholzer, 2009. "Sequential Search with Incompletely Informed Consumers: Theory and Evidence from Retail Gasoline Markets," Vienna Economics Papers 0914, University of Vienna, Department of Economics.
    8. Rauh, Michael T., 2009. "Strategic complementarities and search market equilibrium," Games and Economic Behavior, Elsevier, vol. 66(2), pages 959-978, July.
    9. Monica Giulietti & Michael Waterson & Matthijs Wildenbeest, 2014. "Estimation of Search Frictions in the British Electricity Market," Journal of Industrial Economics, Wiley Blackwell, vol. 62(4), pages 555-590, December.
    10. Natalia Fabra & Juan-Pablo Montero, 2022. "Product Lines and Price Discrimination in Markets with Information Frictions," Management Science, INFORMS, vol. 68(2), pages 981-1001, February.
    11. Florian Morath & Johannes Münster, 2018. "Online Shopping and Platform Design with Ex Ante Registration Requirements," Management Science, INFORMS, vol. 64(1), pages 360-380, January.
    12. Glenn Ellison & Alexander Wolitzky, 2012. "A search cost model of obfuscation," RAND Journal of Economics, RAND Corporation, vol. 43(3), pages 417-441, September.
    13. Chen, Yongmin & Zhang, Tianle, 2011. "Equilibrium price dispersion with heterogeneous searchers," International Journal of Industrial Organization, Elsevier, vol. 29(6), pages 645-654.
    14. Johannes Johnen & David Ronayne, 2021. "The only Dance in Town: Unique Equilibrium in a Generalized Model of Price Competition," Journal of Industrial Economics, Wiley Blackwell, vol. 69(3), pages 595-614, September.
    15. Donna, Javier D. & Schenone, Pablo & Veramendi, Gregory F., 2020. "Networks, frictions, and price dispersion," Games and Economic Behavior, Elsevier, vol. 124(C), pages 406-431.
    16. Sandro Shelegia & Chris M. Wilson, 2021. "A Generalized Model of Advertised Sales," American Economic Journal: Microeconomics, American Economic Association, vol. 13(1), pages 195-223, February.
    17. Atayev, Atabek, 2022. "Uncertain product availability in search markets," Journal of Economic Theory, Elsevier, vol. 204(C).
    18. Obradovits, Martin, 2015. "Going to the Discounter: Consumer Search with Local Market Heterogeneities," MPRA Paper 66613, University Library of Munich, Germany.
    19. Atabek Atayev, 2021. "Nonlinear Prices, Homogeneous Goods, Search," Papers 2109.15198, arXiv.org.
    20. Jason R. Blevins & Garrett T. Senney, 2019. "Dynamic selection and distributional bounds on search costs in dynamic unit‐demand models," Quantitative Economics, Econometric Society, vol. 10(3), pages 891-929, July.

    More about this item

    Keywords

    Search; Price Competition; Bertrand Competition; Law of One Price; Price Count; Price Quote; Information Structure; Bayes Correlated Equilibrium;
    All these keywords.

    JEL classification:

    • D41 - Microeconomics - - Market Structure, Pricing, and Design - - - Perfect Competition
    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cwl:cwldpp:2224. 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: Brittany Ladd (email available below). General contact details of provider: https://edirc.repec.org/data/cowleus.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.