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Estimating demand in search markets: the case of online hotel bookings

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  • Sergei Koulayev

Abstract

In this paper, we emphasize that choice sets generated by a search process have two properties: first, they are limited; second, they are endogenous to preferences. Both factors lead to biased estimates in a static demand framework that takes choice sets as given. To correct for this bias, we estimate a structural model of search for differentiated products, using a unique dataset of consumer online search for hotels. Within a nested logit utility model, we show that the mean utility function and the search cost distribution of a representative consumer are non-parametrically identified, given our data. Using our model's estimates, we quantify both sources of bias: they lead to overestimation of price elasticity by a factor of five and four, respectively. The median search cost is about 38 dollars per 15 hotels; we also present some evidence on multi-modality of search cost distribution.

Suggested Citation

  • Sergei Koulayev, 2009. "Estimating demand in search markets: the case of online hotel bookings," Working Papers 09-16, Federal Reserve Bank of Boston.
  • Handle: RePEc:fip:fedbwp:09-16
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    References listed on IDEAS

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    1. Eric J. Johnson & Wendy W. Moe & Peter S. Fader & Steven Bellman & Gerald L. Lohse, 2004. "On the Depth and Dynamics of Online Search Behavior," Management Science, INFORMS, vol. 50(3), pages 299-308, March.
    2. Costinot, Arnaud & Komunjer, Ivana, 2006. "What Good Do Countries Trade? New Ricardian Predictions," University of California at San Diego, Economics Working Paper Series qt9t9818ng, Department of Economics, UC San Diego.
    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. Hernán A. Bruno & Naufel J. Vilcassim, 2008. "—Structural Demand Estimation with Varying Product Availability," Marketing Science, INFORMS, vol. 27(6), pages 1126-1131, 11-12.
    5. Mark Armstrong & John Vickers & Jidong Zhou, 2009. "Prominence and consumer search," RAND Journal of Economics, RAND Corporation, vol. 40(2), pages 209-233.
    6. Christopher T. Conlon & Julie Holland Mortimer, 2013. "Demand Estimation under Incomplete Product Availability," American Economic Journal: Microeconomics, American Economic Association, vol. 5(4), pages 1-30, November.
    7. Babur De Los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2012. "Testing Models of Consumer Search Using Data on Web Browsing and Purchasing Behavior," American Economic Review, American Economic Association, vol. 102(6), pages 2955-2980, October.
    8. Mariuzzo, Franco & Walsh, Patrick Paul & Whelan, Ciara, 2010. "Coverage of retail stores and discrete choice models of demand: Estimating price elasticities and welfare effects," International Journal of Industrial Organization, Elsevier, vol. 28(5), pages 555-578, September.
    9. Sergei Koulayev, 2008. "Estimating search with learning," Working Papers 08-29, NET Institute, revised Oct 2008.
    10. Ali Hortaçsu & Chad Syverson, 2004. "Product Differentiation, Search Costs, and Competition in the Mutual Fund Industry: A Case Study of S&P 500 Index Funds," The Quarterly Journal of Economics, Oxford University Press, vol. 119(2), pages 403-456.
    11. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    12. Babur De los Santos, 2008. "Consumer Search on the Internet," Working Papers 08-15, NET Institute, revised Sep 2008.
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    Cited by:

    1. Timothy J. Richards & Stephen F. Hamilton & Koichi Yonezawa, 2017. "Variety and the Cost of Search in Supermarket Retailing," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 50(3), pages 263-285, May.
    2. Richards, Timothy J. & Hamilton, Stephen F. & Empen, Janine, 2015. "Attribute Search in Online Retailing," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 202968, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    3. Angela De Carlo & Angela Stefania Bergantino & Andrea Morone, 2013. "Experiments in transport related choices: the influence of risk and uncertainty in determining workers' behaviour with respect to parking alternatives," ERSA conference papers ersa13p407, European Regional Science Association.
    4. Babur De los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2012. "Search with Learning," Working Papers 2012-03, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    5. Navid Mojir & K. Sudhir, 2014. "Price Search Across Stores and Across Time," Cowles Foundation Discussion Papers 1942, Cowles Foundation for Research in Economics, Yale University, revised Mar 2016.
    6. Richards, Timothy J. & Hamilton, Stephen F. & Allender, William, 2016. "Search and price dispersion in online grocery markets," International Journal of Industrial Organization, Elsevier, vol. 47(C), pages 255-281.
    7. Timothy Richards & Stephen Hamilton, 2015. "Attribute Search in Online Retail Grocery Markets," Working Papers 1505, California Polytechnic State University, Department of Economics.

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    Keywords

    Consumer behavior ; Consumers' preferences ; Electronic commerce;

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