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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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    Cited by:

    1. 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.
    2. 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.
    3. Jason R. Blevins & Garrett T. Senney, 2014. "Dynamic Selection and Distributional Bounds on Search Costs in Dynamic Unit-Demand Models," Working Papers 14-02, Ohio State University, Department of Economics.
    4. Yankov, Vladimir, 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.).
    5. 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.

    More about this item

    Keywords

    consumer search; oligopoly; search costs; semi-nonparametric estimation;

    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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