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The Varying Effects of Predatory Lending Laws on High-Cost Mortgage Applications

Resource Type
Dataset : survey data
  • Ho, Giang (University of California-Los Angeles)
  • Pennington-Cross, Anthony (Marquette University)
Other Title
  • Version 1 (Subtitle)
Publication Date
Funding Reference
  • Federal Reserve Bank of St. Louis. Research Division
Free Keywords
mortgages; loans; financial policy
  • Abstract

    Federal, state, and local predatory lending laws are designed to restrict and in some cases prohibit certain types of high-cost mortgage credit in the subprime market. Empirical evidence using the spatial variation in these laws shows that the aggregate flow of high-cost mortgage credit can increase, decrease, or be unchanged after these laws are enacted. Although it may seem counterintuitive to find that a law that prohibits lending could be associated with more lending, it is hypothesized that a law may reduce the cost of sorting honest loans from dishonest loans and lessens borrowers' fears of predation, thus stimulating the high-cost mortgage market.
  • Table of Contents


    • DS1: Dataset
Geographic Coverage
  • United States
Collection Mode
  • These data are part of ICPSR's Publication-Related Archive and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigators if further information is desired.

This study is freely available to the general public via web download.
Alternative Identifiers
  • 1342 (Type: ICPSR Study Number)
  • Ho, Giang, Pennington-Cross, Anthony. The varying effects of predatory lending laws on high-cost mortgage applications. Federal Reserve Bank of St. Louis Review.89, (1), 39-59.2007.

Update Metadata: 2015-08-05 | Issue Number: 6 | Registration Date: 2015-06-15

Ho, Giang; Pennington-Cross, Anthony (2007): The Varying Effects of Predatory Lending Laws on High-Cost Mortgage Applications. Version 1. Version: v1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset.