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What’s in a Score? Differences in Consumers’ Credit Knowledge Using OLS and Quantile Regressions

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  • Angela Lyons
  • Mitchell Rachlis
  • Erik Scherpf
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    Abstract

    Credit literacy depends, in part, on understanding credit report information and scores. The US Government Accountability Office (GAO) conducted a study in 2004 to assess consumers’ knowledge of their credit report and credit score, and the dispute resolution process. This study uses the GAO data and estimates a series of OLS and quantile regressions to identify specific subgroups of the population that could benefit from more targeted consumer policies and financial education. The findings from this research have important implications for consumer educators, financial professionals, and policymakers, especially with respect to national strategies designed to improve consumers’ financial well-being.

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    File URL: http://indstate.edu/business/NFI/leadership/papers/2007-WP-01_Lyons-Rachlis-Scherpf.pdf
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    Bibliographic Info

    Paper provided by Indiana State University, Scott College of Business, Networks Financial Institute in its series NFI Working Papers with number 2007-WP-01.

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    Length: 36 pages
    Date of creation: Jan 2007
    Date of revision:
    Handle: RePEc:nfi:nfiwps:2007-wp-01

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    1. Eide, Eric & Showalter, Mark H., 1998. "The effect of school quality on student performance: A quantile regression approach," Economics Letters, Elsevier, Elsevier, vol. 58(3), pages 345-350, March.
    2. Bedard, Kelly, 2003. "School quality and the distribution of male earnings in Canada," Economics of Education Review, Elsevier, Elsevier, vol. 22(4), pages 395-407, August.
    3. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    4. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, Cambridge University Press, number 9780521608275.
    5. Jesse Levin, 2001. "For whom the reductions count: A quantile regression analysis of class size and peer effects on scholastic achievement," Empirical Economics, Springer, Springer, vol. 26(1), pages 221-246.
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