IDEAS home Printed from https://ideas.repec.org/p/red/sed010/559.html
   My bibliography  Save this paper

The impact of search costs on consumer behavior: a dynamic approach

Author

Listed:
  • Stephan Seiler

    (London School of Economics)

Abstract

Prices for grocery items differ across stores and time because of promotion periods. Consumers therefore have an incentive to search for the lowest price. When a product is purchased infrequently though, the hassle of checking the price on every shopping trip might outweigh the benefit of spending less. I propose a structural model for storable goods, that takes inventory holdings and search into account. The model is estimated using data on laundry detergent purchases. I find that search costs play a large role in explaining purchase behavior, with a large proportion of consumers not being aware of the price of detergent in a given time period. Trip characteristics such as the amount of money spent on other items and the number of products purchased in the same product category cause the search cost to vary across shopping trips. I also compute between-store price elasticities and find that temporary promotions have little impact on competing stores. There is no post-promotion dip in sales. Permanent price reductions lead to a significant shift in market share towards the store that lowered its price. The adjustment of market shares is almost immediate.

Suggested Citation

  • Stephan Seiler, 2010. "The impact of search costs on consumer behavior: a dynamic approach," 2010 Meeting Papers 559, Society for Economic Dynamics.
  • Handle: RePEc:red:sed010:559
    as

    Download full text from publisher

    File URL: https://red-files-public.s3.amazonaws.com/meetpapers/2010/paper_559.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gautam Gowrisankaran & Marc Rysman, 2012. "Dynamics of Consumer Demand for New Durable Goods," Journal of Political Economy, University of Chicago Press, vol. 120(6), pages 1173-1219.
    2. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    3. Pasquale Schiraldi, 2011. "Automobile replacement: a dynamic structural approach," RAND Journal of Economics, RAND Corporation, vol. 42(2), pages 266-291, June.
    4. João L. Assunção & Robert J. Meyer, 1993. "The Rational Effect of Price Promotions on Sales and Consumption," Management Science, INFORMS, vol. 39(5), pages 517-535, May.
    5. van Nierop, J.E.M. & Paap, R. & Bronnenberg, B. & Franses, Ph.H.B.F. & Wedel, M., 2005. "Retrieving unobserved consideration sets from household panel data," Econometric Institute Research Papers EI 2005-49, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Salop, S & Stiglitz, J E, 1982. "The Theory of Sales: A Simple Model of Equilibrium Price Dispersion with Identical Agents," American Economic Review, American Economic Association, vol. 72(5), pages 1121-1130, December.
    7. Nitin Mehta & Surendra Rajiv & Kannan Srinivasan, 2003. "Price Uncertainty and Consumer Search: A Structural Model of Consideration Set Formation," Marketing Science, INFORMS, vol. 22(1), pages 58-84, June.
    8. David Bell & Christian Hilber, 2006. "An empirical test of the Theory of Sales: Do household storage constraints affect consumer and store behavior?," Quantitative Marketing and Economics (QME), Springer, vol. 4(2), pages 87-117, June.
    9. Hoyer, Wayne D, 1984. "An Examination of Consumer Decision Making for a Common Repeat Purchase Product," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(3), pages 822-829, December.
    10. Martin Pesendorfer, 2002. "Retail Sales: A Study of Pricing Behavior in Supermarkets," The Journal of Business, University of Chicago Press, vol. 75(1), pages 33-66, January.
    11. Andrew Ching & Tülin Erdem & Michael Keane, 2009. "The price consideration model of brand choice," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(3), pages 393-420, April.
    12. John R. Hauser, 1978. "Testing the Accuracy, Usefulness, and Significance of Probabilistic Choice Models: An Information-Theoretic Approach," Operations Research, INFORMS, vol. 26(3), pages 406-421, June.
    13. Tülin Erdem & Susumu Imai & Michael Keane, 2003. "Brand and Quantity Choice Dynamics Under Price Uncertainty," Quantitative Marketing and Economics (QME), Springer, vol. 1(1), pages 5-64, March.
    14. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    15. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    16. Michelle Sovinsky Goeree, 2008. "Limited Information and Advertising in the U.S. Personal Computer Industry," Econometrica, Econometric Society, vol. 76(5), pages 1017-1074, September.
    17. Daniel A. Ackerberg, 2003. "Advertising, learning, and consumer choice in experience good markets: an empirical examination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(3), pages 1007-1040, August.
    18. Igal Hendel & Aviv Nevo, 2003. "The Post-Promotion Dip Puzzle: What do the Data Have to Say?," Quantitative Marketing and Economics (QME), Springer, vol. 1(4), pages 409-424, December.
    19. 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.
    20. Alan T. Sorensen, 2000. "Equilibrium Price Dispersion in Retail Markets for Prescription Drugs," Journal of Political Economy, University of Chicago Press, vol. 108(4), pages 833-862, August.
    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. Jose Luis Moraga-Gonzalez & Zsolt Sandor & Matthijs R. Wildenbeest, 2010. "On the Identification of the Costs of Simultaneous Search," Working Papers 2010-10, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    2. Pradeep K. Chintagunta & Harikesh S. Nair, 2011. "Structural Workshop Paper --Discrete-Choice Models of Consumer Demand in Marketing," Marketing Science, INFORMS, vol. 30(6), pages 977-996, November.

    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. Stephan Seiler, 2013. "The impact of search costs on consumer behavior: A dynamic approach," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 155-203, June.
    2. Stephan Seiler, 2013. "The impact of search costs on consumer behavior: A dynamic approach," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 155-203, June.
    3. Victor Aguirregabiria & Margaret Slade, 2017. "Empirical models of firms and industries," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(5), pages 1445-1488, December.
    4. Victor Aguirregabiria & Victor Aguirregabiria & Aviv Nevo & Aviv Nevo, 2010. "Recent Developments in Empirical IO: Dynamic Demand and Dynamic Games," Working Papers tecipa-419, University of Toronto, Department of Economics.
    5. Tiago Pires, 2016. "Costly search and consideration sets in storable goods markets," Quantitative Marketing and Economics (QME), Springer, vol. 14(3), pages 157-193, September.
    6. Navid Mojir & K. Sudhir, 2014. "A Model of Multi-pass Search: Price Search across Stores and Time," Cowles Foundation Discussion Papers 1942R2, Cowles Foundation for Research in Economics, Yale University, revised Feb 2020.
    7. Gonca P. Soysal & Lakshman Krishnamurthi, 2012. "Demand Dynamics in the Seasonal Goods Industry: An Empirical Analysis," Marketing Science, INFORMS, vol. 31(2), pages 293-316, March.
    8. Javier D. Donna, 2021. "Measuring long‐run gasoline price elasticities in urban travel demand," RAND Journal of Economics, RAND Corporation, vol. 52(4), pages 945-994, December.
    9. Victor Aguirregabiria, 2023. "Dynamic demand for differentiated products with fixed-effects unobserved heterogeneity," The Econometrics Journal, Royal Economic Society, vol. 26(1), pages 1-25.
    10. Sofronis Clerides & Pascal Courty, 2017. "Sales, Quantity Surcharge, and Consumer Inattention," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 357-370, May.
    11. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2020. "How much do consumers know about the quality of products? Evidence from the diaper market," The Japanese Economic Review, Springer, vol. 71(4), pages 541-569, October.
    12. Jean‐Pierre Dubé & Günter J. Hitsch & Peter E. Rossi, 2010. "State dependence and alternative explanations for consumer inertia," RAND Journal of Economics, RAND Corporation, vol. 41(3), pages 417-445, September.
    13. Navid Mojir & K. Sudhir, 2014. "Price Search Across Time and Across Stores," Cowles Foundation Discussion Papers 1942R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2019.
    14. Gautam Gowrisankaran & Marc Rysman, 2012. "Dynamics of Consumer Demand for New Durable Goods," Journal of Political Economy, University of Chicago Press, vol. 120(6), pages 1173-1219.
    15. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Invited Paper ---Learning Models: An Assessment of Progress, Challenges, and New Developments," Marketing Science, INFORMS, vol. 32(6), pages 913-938, November.
    16. Masakazu Ishihara & Andrew T. Ching, 2019. "Dynamic Demand for New and Used Durable Goods Without Physical Depreciation: The Case of Japanese Video Games," Marketing Science, INFORMS, vol. 38(3), pages 392-416, May.
    17. Avery Haviv, 2022. "Consumer Search, Price Promotions, and Counter-Cyclic Pricing," Marketing Science, INFORMS, vol. 41(2), pages 294-314, March.
    18. Elisabeth Honka, 2014. "Quantifying search and switching costs in the US auto insurance industry," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 847-884, December.
    19. Brett R. Gordon, 2009. "A Dynamic Model of Consumer Replacement Cycles in the PC Processor Industry," Marketing Science, INFORMS, vol. 28(5), pages 846-867, 09-10.
    20. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.

    More about this item

    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:red:sed010:559. 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: Christian Zimmermann (email available below). General contact details of provider: https://edirc.repec.org/data/sedddea.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.