Giang Ho & Anthony Pennington-Cross Federal Reserve Bank of St. Louis Disclaimer

1. The Impact of Local Predatory Lending Laws: North Carolina and Beyond (not all laws are created equal) Giang Ho & Anthony Pennington-Cross Federal Reserve Bank of St. Louis Disclaimer The views expressed in this research are those of the individual author(s) and do not necessarily reflect the official positions of the Federal Reserve Bank of St. Louis, the Federal Reserve System, and the Board of Governors.

2. Outline • Introduction • Spread of local laws • HOEPA style • Why Do the Laws Focus on Subprime? • Research Questions • Measuring the Strength of the Laws • Empirical Approach • Does Law Strength Matter? • Conclusions

3. IntroductionSpread of Local Laws

4. IntroductionFederal Regulations • Home Ownership and Equity Protection Act (HOEPA) • Regulation Z • Refinance and 2nd mortgages only • Coverage Triggers • APR • 8% 1st lien • 10% 2nd lien • Points and fees • Indexed to inflation • Restrictions • Short-term balloon notes • Prepayment penalties greater than 5-years • Non-amortizing schedules • Refinance HOEPA to HOEPA in 1st 12 months • Impose higher interest rate upon default • No-documentation loans

5. IntroductionLocal Predatory Lending Laws • State, county, and city • States most successful in surviving legal challenges • At least 24 states w/ HOEPA style (end of 2004) • Arkansas, California, Colorado, Connecticut, Florida, • Georgia, Illinois, Kentucky, Maine, Maryland, • Massachusetts, Nevada, New Jersey, New Mexico, • New York, North Carolina, Ohio, Oklahoma, Pennsylvania, • South Carolina, Texas, Utah, and Wisconsin • Typically extends coverage • Purchase loans • Lower triggers • APR & Fees • Typically extends restrictions • Prepayment penalties • Balloons • Require counseling • For details see http://research.stlouisfed.org/wp/2005/2005-049.pdf • Appendix A • Butera and Andrews WDC law firm • www.butera-andrews.com

6. Why Do The Laws Focus On Subprime?

7. Source: The 2004 Mortgage Market Statistical Annual

8. Source: Freddie Mac’s Primary Mortgage Market Survey for Prime loans and author’s calculations using LoanPerformance ABS data set for Subprime loans (fixed rate loans only).

9. Prime 90-Day Delinquency Rates(MBAA,not seasonally adjusted)

10. Subprime 90-Day Delinquency Rates(MBAA, not seasonally adjusted)

11. Foreclosure In-Progress Rate

12. Why Focus on Subprime? • Interviews • HUD, • Treasury, and • the Federal Reserve Board • Some, perhaps many, • borrowers using high-cost loans may not have understood • rights and the terms of the mortgage • Makes it possible to • take advantage of the borrower

13. Why Focus on Subprime? • Great Promise & Great Peril • Opportunity for Homeownership • Asset Building • Typical household holds no corporate equity (Tracy, et al 1999) • Positive Effects • Neighborhood & Children • Risky Loans • High default & high prepayment (Pennington-Cross, 2003) • Costly • Higher than prime loss severity (Capozza and Thomson, 2005) • Vulnerable Population • Less educated (Courchane, Surette, and Zorn, 2004) • Less knowledgeable about mortgages (Courchane, Surette, and Zorn, 2004) • Geographically Concentrated • Low income and minority areas (Calem, Gillen, and Wachter, 2004) • Economically challenged areas (Pennington-Cross, 2002) • What is a Socially Acceptable Failure Rate? • Predatory Lending Laws

14. Research Questions

15. Did the North Carolina Law(Ernst, Farris, and Stein 2002; Quercia, Stegman, and Davis 2003 & 2004; Harvey and Nigro 2004; and Elliehausen and Staten 2004) • Reduce originations of subprime loans? • Yes • Reduce applications for subprime loans? • Yes • Increase or decrease rejections? • No impact / mixed • Similar findings for Chicago and Philadelphia(Harvey and Nigro 2003) • Research Questions • Do the findings in NC apply to other laws? • Does the strength of the law matter? • Restrictions and coverage • Is there a regulatory cost? • Passed onto consumers (future work)

16. Measuring the Strength of the Laws

17. Coverage Index • Loan Purpose • HOEPA equivalent=0 • all loans except -- no government loans=1 • all loans except -- no reverse, or no open ended loans=2 • all loans except -- no reverse, business, or construction loans =3 • all loans with no exceptions=4 • APR Trigger 1st Lien • 8%, HOEPA equivalent =0, • 7%=1, • 6%=2, and • no trigger=3 • APR Trigger Higher Lien • 10%, HOEPA equivalent =0, • 9%=1, • 8%=2, • 7%=3, and • no trigger=4 • Points and Fees Trigger • 8%,HOEPA equivalent =0, • 6%-7%=1, • 5%=2 , • <5%=3, and • no trigger=4

18. Restrictions Index • Prepayment Penalty Prohibitions • No restriction=0 • prohibition or percent limits after 60 months=1 • prohibition or percent limits after 36 months=2 • prohibition or percent limits after 24 months=3 • no penalties allowed=4 • Balloon Prohibitions • No restriction =0 • no balloon if term<7 years (all term restrictions) =1 • no balloon in first 10 years of mortgage =2 • no balloon in first 15 years of mortgage and Cleveland=3 • no balloons allowed=4 • Counseling Requirements • Not required=0 • Required=1 • Mandatory Arbitration Limiting Judicial Relief • Allowed=0 • partially restricted=1 • prohibited =2

19. Describing the Laws

20. Scaled Index

21. Empirical Approach

22. Natural Experiment • Neighbor A in state A has law introduced and it becomes in effect or effective • Neighbor B, across the street in state B, does not have a law introduced • Compare market conditions • Pre-law • Neighborhood A • Neighborhood B • Post-law • Neighborhood A (in effect) • Neighborhood B

23. Natural Experiment • Border counties • One state introduces a law and the other doesn’t • “nearest neighbor” approach • HMDA (applications, rejections, & originations) • Year before and year after law become effective • Subprime loans defined by HUD lender list • All border county loans (not a matched sample)

24. Estimation Approach • Estimate probit specification • Each law sample & each outcome (30 models & 300 coefficients) • Probability of outcome • Applying for a subprime loan • Being rejected on a subprime application • Originating a subprime loan • Identifying the impact • Law Dummy • 1 if a location has a law at some point, 0 otherwise • Postlaw Dummy • 1 if the post-legislation time period, 0 otherwise • Ineffect = Law*Postlaw • Interaction variable • The borrower/applicant is from a location with a law in effect • Law Index • Restrictions & Coverage • Control for • Location & Borrower/Loan characteristics • Missing credit scores

25. Control Variables

26. Mean of Outcome Variables

27. Marginal Effects – Ineffect Variable

28. Does Law Strength Matter?

29. Heterogeneity of Market ResponseCorrelation of Law Strength & %Change of Outcome

30. Pooled Sample • Include law strength measures • Scaled indexes • Full • Coverage • Restrictions • Outcome & Law Dummy (treatment location) Jointly Determined? • Political propensity • Dem/Rep ratio in state legislatures 2000 • HUD-Treasury (2000) report • Urban areas • State percent of population urban (2000 census) • In subprime lending • State mkt share subprime, t-1 (HMDA) • Nonwhite populations • State percent non-white (2000 census) • Estimate bivariate probit

31. Descriptive StatisticsDependent and Control Variables

32. A Lot of Identification VariablesLaw, Postlaw, Ineffect (Law*Postlaw) • Need to control for • Law sample location • Treatment location • Pre/post law time period • LawSample dummies • ca, ct, fl, ga, ma, md, oh, pa, tx • Law dummy for each Law Sample • Law*ca, Law*ct, Law*ga, Law*ma, Law*md, Law*oh, Law*pa, Law*tx • Postlaw dummy for Law Sample • Postlaw*ca, Postlaw*ct, Postlaw*ga, Postlaw*ma, Postlaw*md, Postlaw*oh, Postlaw*pa, Post law*tx • Pooled Ineffect dummy

33. Results – Treatment (Law) Equation

34. Results – Outcome Equations (control variables)

35. Results – Outcome Equations (control variables)

36. Results – Outcome Equations

37. Results – Scaled Law Index

38. Impact of Law Strength

39. Results – Scaled Law Index

40. Impact of Law Restrictions

41. Impact of Law Coverage

42. Conclusions • Typical Laws have little impact • Possible to design a local predatory lending law to • Increase the flow of high cost credit • coverage • Reduce the flow of high cost credit • restrictions • No impact on the flow of credit • typical law • Typically reduce rejection rates • Is there an impact on cost of credit?