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Testing Models of Consumer Search Using Data on Web Browsing Behavior

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Abstract

Using a large data set on consumers' web browsing and purchasing behavior we contrast various classical search models. We find that the benchmark model of sequential search with a known distributions of prices can be rejected based on the recall patterns we observe in the data. Moreover, we show that even if consumers are initially unaware of the price distribution and have to learn the price distribution, observed search behavior for given consumers over time is more consistent with non-sequential search than sequential search with learning. Our findings suggest non-sequential search provides a more accurate description of observed consumer search behavior. We then utilize the non-sequential search model to estimate the price elasticities and markups of online book retailers.

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File URL: http://www.netinst.org/DelosSantos_Hortacsu_Wildenbeest_09-23.pdf
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Bibliographic Info

Paper provided by NET Institute in its series Working Papers with number 09-23.

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Length: 34 pages
Date of creation: Aug 2009
Date of revision: Aug 2009
Handle: RePEc:net:wpaper:0923

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Web page: http://www.NETinst.org/

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Keywords: search costs; sequential search; fixed-sample search; non-sequential search; online browsing; online book industry; consumer search;

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References

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  1. Manning, R & Morgan, Peter B, 1982. "Search and Consumer Theory," Review of Economic Studies, Wiley Blackwell, vol. 49(2), pages 203-16, April.
  2. Mortensen, Dale T, 1970. "Job Search, the Duration of Unemployment, and the Phillips Curve," American Economic Review, American Economic Association, vol. 60(5), pages 847-62, December.
  3. Jose Luis Moraga-Gonzalez & Matthijs R. Wildenbeest, 0000. "Maximum Likelihood Estimation of Search Costs," Tinbergen Institute Discussion Papers 06-019/1, Tinbergen Institute.
  4. Kogut, Carl A., 1990. "Consumer search behavior and sunk costs," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 381-392, December.
  5. 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.
  6. Schotter, Andrew & Braunstein, Yale M, 1981. "Economic Search: An Experimental Study," Economic Inquiry, Western Economic Association International, vol. 19(1), pages 1-25, January.
  7. 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.
  8. McCall, John J, 1970. "Economics of Information and Job Search," The Quarterly Journal of Economics, MIT Press, vol. 84(1), pages 113-26, February.
  9. Weitzman, Martin L, 1979. "Optimal Search for the Best Alternative," Econometrica, Econometric Society, vol. 47(3), pages 641-54, May.
  10. repec:rje:randje:v:37:y:2006:2:p:257-275 is not listed on IDEAS
  11. Michael Rothschild, 1974. "Searching for the Lowest Price When the Distribution of Prices Is Unknown: A Summary," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 1, pages 293-294 National Bureau of Economic Research, Inc.
  12. Gabriel Talmain & Chien-Fu Chou, 1990. "Non-Parametric Search," Discussion Papers 92-01, University at Albany, SUNY, Department of Economics.
  13. Rosenfield, Donald B. & Shapiro, Roy D., 1981. "Optimal adaptive price search," Journal of Economic Theory, Elsevier, vol. 25(1), pages 1-20, August.
  14. Harrison, Glenn W & Morgan, Peter, 1990. "Search Intensity in Experiments," Economic Journal, Royal Economic Society, vol. 100(401), pages 478-86, June.
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