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On the Identification of the Costs of Simultaneous Search

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 identification of the costs of simultaneous search in a class of (portfolio) problems studied by Chade and Smith (2006). We show that aggregate data from a single market, or disaggregate data from a single market segment, do not provide sufficient information to identify the costs of simultaneous search in any reasonable interval. We then show that by pooling aggregate data from multiple markets, or disaggregate data from multiple market segments, the econometrician can identify the costs of simultaneous search in a non-empty interval. Within the context of specific examples, we illustrate that identification of the search cost distribution in its full support may easily be obtained.

Suggested Citation

  • 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.
  • Handle: RePEc:iuk:wpaper:2010-10
    as

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    File URL: http://kelley.iu.edu/riharbau/RePEc/iuk/wpaper/bepp2010-10-moraga-sandor-wildenbeest.pdf
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    References listed on IDEAS

    as
    1. James Albrecht & Pieter A. Gautier & Susan Vroman, 2006. "Equilibrium Directed Search with Multiple Applications," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 73(4), pages 869-891.
    2. Hector Chade & Lones Smith, 2006. "Simultaneous Search," Econometrica, Econometric Society, vol. 74(5), pages 1293-1307, September.
    3. 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.
    4. Asher Wolinsky, 1986. "True Monopolistic Competition as a Result of Imperfect Information," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 101(3), pages 493-511.
    5. Jun B. Kim & Paulo Albuquerque & Bart J. Bronnenberg, 2010. "Online Demand Under Limited Consumer Search," Marketing Science, INFORMS, vol. 29(6), pages 1001-1023, 11-12.
    6. Simon P. Anderson & Regis Renault, 1999. "Pricing, Product Diversity, and Search Costs: A Bertrand-Chamberlin-Diamond Model," RAND Journal of Economics, The RAND Corporation, vol. 30(4), pages 719-735, Winter.
    7. Philipp Kircher, 2009. "Efficiency of Simultaneous Search," Journal of Political Economy, University of Chicago Press, vol. 117(5), pages 861-913, October.
    8. Burdett, Kenneth & Judd, Kenneth L, 1983. "Equilibrium Price Dispersion," Econometrica, Econometric Society, vol. 51(4), pages 955-969, July.
    9. José Luis Moraga‐González & Zsolt Sándor & Matthijs R. Wildenbeest, 2013. "Semi‐Nonparametric Estimation Of Consumer Search Costs," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1205-1223, November.
    10. 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.
    11. Kelso, Alexander S, Jr & Crawford, Vincent P, 1982. "Job Matching, Coalition Formation, and Gross Substitutes," Econometrica, Econometric Society, vol. 50(6), pages 1483-1504, November.
    12. Stephan Seiler, 2010. "The impact of search costs on consumer behavior: a dynamic approach," 2010 Meeting Papers 559, Society for Economic Dynamics.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Lu, Zhentong, 2022. "Estimating multinomial choice models with unobserved choice sets," Journal of Econometrics, Elsevier, vol. 226(2), pages 368-398.

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    More about this item

    Keywords

    search costs; portfolio choice; non-parametric identification;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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