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Information Technology and Consumer Search for Health Insurance

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  • Mark Pauly
  • Bradley Herring
  • David Song

Abstract

We explore the impact of information technology on the level of premiums paid for individual health insurance by asking which kinds of buyers will have larger gains from the use of new technology. We compare 'asking price' data posted on an electronic insurance exchange with survey data on premiums actually paid before the advent of exchange and examine whether the pattern of differences between asking prices and transactions prices can be explained using a simple search theory. We hypothesize that older consumers, expecting to pay higher premiums for a given policy, had engaged in more intensive search than younger consumers, given the same distribution of prices and search costs. Therefore, the introduction of an electronic exchange that lowers the cost of search should have a larger effect on decreasing the level of premiums paid for those who previously searched less (i.e., younger consumers). We find evidence consistent with this hypothesis.

Suggested Citation

  • Mark Pauly & Bradley Herring & David Song, 2006. "Information Technology and Consumer Search for Health Insurance," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 13(1), pages 45-63.
  • Handle: RePEc:taf:ijecbs:v:13:y:2006:i:1:p:45-63
    DOI: 10.1080/13571510500519970
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    References listed on IDEAS

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    1. Karen Clay & Ramayya Krishnan & Eric Wolff, 2001. "Prices and Price Dispersion on the Web: Evidence from the Online Book Industry," Journal of Industrial Economics, Wiley Blackwell, vol. 49(4), pages 521-539, December.
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    4. Jeffrey R. Brown & Austan Goolsbee, 2002. "Does the Internet Make Markets More Competitive? Evidence from the Life Insurance Industry," Journal of Political Economy, University of Chicago Press, vol. 110(3), pages 481-507, June.
    5. Steven Salop & Joseph Stiglitz, 1977. "Bargains and Ripoffs: A Model of Monopolistically Competitive Price Dispersion," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 44(3), pages 493-510.
    6. Stigler, George J., 2011. "Economics of Information," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 35-49.
    7. Salop, S & Stiglitz, J E, 1982. "The Theory of Sales: A Simple Model of Equilibrium Price Dispersion with Identical Agents," American Economic Review, American Economic Association, vol. 72(5), pages 1121-1130, December.
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    Cited by:

    1. Benlagha, Noureddine & Hemrit, Wael, 2020. "Internet use and insurance growth: evidence from a panel of OECD countries," Technology in Society, Elsevier, vol. 62(C).
    2. K.T. Thomas & R. Sakthivel, 2015. "Retail Participation in Health Insurance: A Model of Consumer Preferences," Global Business Review, International Management Institute, vol. 16(6), pages 997-1011, December.
    3. Bolhaar J & Lindeboom M & van der Klaauw B, 2009. "Insurance Search and Switching Behaviour at the time of the Dutch Health Insurance Reform," Health, Econometrics and Data Group (HEDG) Working Papers 09/14, HEDG, c/o Department of Economics, University of York.
    4. Lindeboom, Maarten & van der Klaauw, Bas & Bolhaar, Jonneke, 2010. "Insurance Search and Switching Behavior," CEPR Discussion Papers 7942, C.E.P.R. Discussion Papers.

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    More about this item

    Keywords

    Consumer Search; Price Dispersion; Information Technology; Health Insurance; JEL Classifications: L1; D83; I11;
    All these keywords.

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets

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