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Semi-Nonparametric Estimation of Consumer Search Costs

Author

Listed:
  • Jose Luis Moraga-Gonzalez

    (University of Groningen and CESifo)

  • Zsolt Sandor

    (Universidad Carlos III de Madrid)

  • Matthijs R. Wildenbeest

    (Department of Business Economics and Public Policy, Indiana University Kelley School of Business)

Abstract
This paper studies the estimation of the cost of non-sequential search. We provide a new method based on semi-nonparametric (SNP) estimation that allows us to pool price data from different consumer markets with the same underlying search cost distribution but di erent valuations or selling costs. We show that pooling data from di erent markets increases the number of estimated critical search cost cuto s at all quantiles of the search cost distribution, which increases the precision of the estimates. A Monte Carlo study shows that the method works well in small samples. We apply our method to a data set of online prices for memory chips and nd that the search cost density is essentially bimodal such that a large fraction of consumers searches very little, while a smaller fraction of consumers samples a relatively large number of stores.

Suggested Citation

  • Jose Luis Moraga-Gonzalez & Zsolt Sandor & Matthijs R. Wildenbeest, 2007. "Semi-Nonparametric Estimation of Consumer Search Costs," Working Papers 2007-20, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy, revised Jun 2010.
    • Handle: RePEc:iuk:wpaper:2007-20
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    File URL: http://kelley.iu.edu/riharbau/RePEc/iuk/wpaper/bepp2007-20-moraga-sandor-wildenbeest.pdf
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    Citations

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    Cited by:

    1. Myśliwski, Mateusz & Rostom, May, 2022. "Value of information, search, and competition in the UK mortgage market," Bank of England working papers 967, Bank of England.
    2. Florez-Acosta, Jorge & Herrera-Araujo, Daniel, 2020. "Multiproduct retailing and consumer shopping behavior: The role of shopping costs," International Journal of Industrial Organization, Elsevier, vol. 68(C).
    3. De los Santos, Babur, 2018. "Consumer search on the Internet," International Journal of Industrial Organization, Elsevier, vol. 58(C), pages 66-105.
    4. Hämäläinen, Saara, 2022. "Multiproduct search obfuscation," International Journal of Industrial Organization, Elsevier, vol. 85(C).
    5. Vladimir Yankov, 2014. "In Search of a Risk-free Asset," Finance and Economics Discussion Series 2014-108, Board of Governors of the Federal Reserve System (U.S.).
    6. 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.
    7. Ratchford, Brian & Soysal, Gonca & Zentner, Alejandro & Gauri, Dinesh K., 2022. "Online and offline retailing: What we know and directions for future research," Journal of Retailing, Elsevier, vol. 98(1), pages 152-177.
    8. 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.
    9. Jorge Florez-Acosta & Daniel Herrera-Araujo, 2017. "Multiproduct retailing and buyer power: The effects of product delisting on consumer shopping behavior," PSE Working Papers halshs-01518146, HAL.
    10. 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.
    11. Bart J. Bronnenberg & Jun B. Kim & Carl F. Mela, 2016. "Zooming In on Choice: How Do Consumers Search for Cameras Online?," Marketing Science, INFORMS, vol. 35(5), pages 693-712, September.
    12. Moraga-González, José Luis & Sándor, Zsolt & Wildenbeest, Matthijs R., 2017. "Nonsequential search equilibrium with search cost heterogeneity," International Journal of Industrial Organization, Elsevier, vol. 50(C), pages 392-414.
    13. 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.
    14. Choudhary, Vidyanand & Currim, Imran & Dewan, Sanjeev & Jeliazkov, Ivan & Mintz, Ofer & Turner, John, 2017. "Evaluation Set Size and Purchase: Evidence from a Product Search Engine," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 16-31.

    More about this item

    Keywords

    consumer search; oligopoly; search costs; semi-nonparametric estimation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets

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