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  • Babur De los Santos

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

  • Ali Hortacsu

    (University of Chicago and NBER)

  • Matthijs R. Wildenbeest

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

This paper provides a method to estimate search costs in an environment in which consumers are uncertain about the price distribution. Consumers learn about the price distribution by Bayesian updating their prior beliefs. The model provides bounds on the search costs that can rationalize observed search and purchasing behavior. Using individual-specific data on web browsing and purchasing behavior for electronics sold online we show how to use these bounds to estimate search costs. Estimated search costs are sizable and are found to relate to consumer characteristics in intuitive ways. The model outperforms a standard sequential search model in which the price distribution is known to consumers.

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File URL: http://kelley.iu.edu/riharbau/RePEc/iuk/wpaper/bepp2012-03-DelosSantos-Hortacsu-Wildenbeest.pdf
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Paper provided by Indiana University, Kelley School of Business, Department of Business Economics and Public Policy in its series Working Papers with number 2012-03.

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Date of creation: Aug 2012
Date of revision:
Handle: RePEc:iuk:wpaper:2012-03
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Web page: http://kelley.iu.edu/bepp/
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  1. Philip A. Haile & Han Hong & Matthew Shum, 2004. "Nonparametric Tests for Common Values in First-Price Sealed-Bid Auctions," Working Papers 2004.149, Fondazione Eni Enrico Mattei.
  2. Gabriel Talmain & Chien-Fu Chou, 1990. "Non-Parametric Search," Discussion Papers 92-01, University at Albany, SUNY, Department of Economics.
  3. Babur de los Santos, 2008. "Consumer Search on the Internet," Working Papers 2008-06, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
  4. Babur De los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2009. "Testing Models of Consumer Search using Data on Web Browsing and Purchasing Behavior," Working Papers 2009-05, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
  5. S. Bikhchandani & S. Sharma, 1990. "Optimal Search with Learning," UCLA Economics Working Papers 580, UCLA Department of Economics.
  6. Matthijs R. Wildenbeest, 2011. "An empirical model of search with vertically differentiated products," RAND Journal of Economics, RAND Corporation, vol. 42(4), pages 729-757, December.
  7. Sergei Koulayev, 2009. "Estimating demand in search markets: the case of online hotel bookings," Working Papers 09-16, Federal Reserve Bank of Boston.
  8. repec:rje:randje:v:37:y:2006:2:p:257-275 is not listed on IDEAS
  9. Han Hong & Matthew Shum, 2006. "Using price distributions to estimate search costs," RAND Journal of Economics, RAND Corporation, vol. 37(2), pages 257-275, 06.
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