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1.5.3 MODELOS DE SECUENCIACIÓN
Full Test # __________
______ ______ ______ ______ ______ ______ ______ ______ Site Test # Test Part NIC Type Purp R/NO T/V
Lender Name _____________________________________________________________________________________________ Lender Address ___________________________________________________________________________________________ ___________________________________________________________________________________________________________ Date of Contact ____ /____ /____
Type of Contact _____ (a = telephone, b = site visit) Length of in-person contact _____ (enter in minutes)
Type of site visit _______ (a = appointment, b = approved walk-in, c = cold walk-in, d = other) Wait time to be interviewed (in minutes) _______
Name of person who interviewed _______
Race/ethnicity of person who interviewed ________
Type of transaction for this test ______ (enter letter of response checked on form)
For the following items enter
A = asked, R = recorded, V = volunteered, N = not asked Source of income ________
Amount of income _______ Debts/liabilities ________ Credit standing ________
Types of loans discussed and/or recommended by lender
(Check responses from test form)
Discussed Recommended Fixed-rate mortgage _____ _____ Adjustable rate mortgage _____ _____ Balloon mortgage _____ _____ FHA mortgage _____ _____ VA mortgage _____ _____ Community homebuyers program _____ _____ First-time homebuyers program _____ _____ Other ___________________________ _____ _____ Other ___________________________ _____ _____
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Information on each loan recommended
______ (Check here if no loans recommended)
Recommendation #1 Recommendation #2 Type of loan ________________ ________________ Amount of loan $_______________ $_______________ Loan term in years ________________ ________________ Interest rate ________________ ________________ Points ________________ ________________ Monthly principal plus interest $_______________ $_______________ Monthly taxes $_______________ $_______________ Monthly homeowners insurance $_______________ $_______________ Monthly PMI $_______________ $_______________ Other monthly expense $_______________ $_______________ Total monthly expense $_______________ $_______________ Other _____________________ ________________ ________________
Information provided about closing and other costs
_____________________ Type/term of loan these costs refer to _____________________ Interest rate for this loan
$____________________ Points (at ___ points)
$____________________ Homeowners insurance premium $____________________ PMI premium
$____________________ Interest adjustment $____________________ Monthly payment reserve $____________________ Document preparation
$____________________ Title examination/title insurance $____________________ Real estate tax escrow
$____________________ Attorneys’ fees $____________________ Down payment $____________________ Appraisal
$____________________ Other _______________________________ $____________________ Other _______________________________ $____________________ Total closing/other costs
Closing costs provided in writing ________
a = good faith estimate, b = lending institution’s form, c = computer printout, d = written on blank paper, e = other, n = no answer checked)
Amount of application fee $_________
How long did lender say application process would take (in days)? _______ Status of written application _____
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Did test include evidence of phone or mail follow-up by lender after test?
_____ No
_____ Phone follow-up _____ Mail follow-up
_____ Both phone and mail follow-up _____ Other
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Notes
1. There has been a limited amount of lender testing by regulatory agencies and private fair housing organizations and self-testing by lenders. Most data sources either are not available for public review or are not large enough for statistical analysis. NFHA’s test information pre- sents a unique opportunity for independent statistical review of test data. The authors greatly appreciate NFHA’s willingness and cooperation in giving us access to its data.
2. Most lending tests have stopped at the pre-application stage because federal law makes it ille- gal to knowingly provide false information on a credit application with intent to defraud. However, some testing advocates argue that submitting false information on a mortgage appli- cation as part of a paired test does not violate this law because the tester will not actually bor- row money and therefore does not intend to defraud. The question has not yet been settled through litigation or regulatory rulings.
3. Testing is also referred to as auditing when used in a research context. This report uses the term testing for tests (or audits) conducted for either enforcement or research purposes. 4. For a more complete discussion, see Fix, Galster, and Struyk (1993).
5. The NFHA tests were conducted by private fair housing organizations working in conjunc- tion with NFHA. NFHA developed all tester training manuals, protocols, and forms for the lender tests under FHIP and worked directly with a fair housing group in each city to recruit and train testers and locate test homes. Staff from NFHA and the local fair housing organi- zations jointly managed the tests. NFHA analyzed all tests.
6. The Urban Institute does not have detailed information on tester scenarios used in NFHA’s tests, including on the actual income assigned to test partners within a pair. The FHIP test coordinator for NFHA, Cathy Cloud, reports that income was directly correlated to loan amount (see footnote below) and that, depending on the desired ratio, partners were matched as closely as possible in actual income.
7. The Urban Institute does not have information on the prices of homes used in the NFHA tests. However, the requested loan amounts were recorded on the test report form and are indicative of home price. Details on the median values of requested loan amounts by city are in annex B at the end of this chapter. For the two largest sites, requested loan values were the same (Oakland) or higher for minorities (Chicago).
8. Since results are not generalizable, no overall incidence measure is given across sites for the entire reanalysis sample.
9. The statistical test used for the reanalysis is the paired t-test, which looks at the relationship between pairs across tests. This statistical tool does not look at the relationship between three or more parts at one time.
10. To review NFHA’s analysis of the full data set, refer to Smith and Cloud (1996).
11. The extraction form includes some data elements not analyzed here. This is because unavail- able data reduced sample sizes in some cases, particularly when further divided by city, to the point where statistical analysis became impossible.
12. While narratives may be part of research test forms, in the research context they are used only as a secondary source of information for missing items or to corroborate items recorded elsewhere. 13. It is accepted in many areas of civil rights enforcement (housing, education, employment) that statistics showing serious racial disparities may indicate illegal differential treatment (Ritter 1996). However, the small amount of mortgage testing research available to date does not provide definitive evidence on how to collect and interpret statistical testing evidence appropriately in this field.
14. Ninety-five percent of the tests in the data set included a white tester linked with a home in a white neighborhood and an African American tester purchasing a home in an African American neighborhood. This test structure does not separate discrimination against indi- viduals and neighborhoods, and subsequent analysis captures the combined differential treatment against both individuals and neighborhoods. Some tests included test parts with
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other tester scenarios such as a minority tester in a white neighborhood or a white tester in an integrated or changing neighborhood. Given the small sample sizes, the most common test type is presented in this analysis.
15. Dallas is not represented because no data were available on the relatively few tests conducted there. Most analysis also excludes Detroit because of the small number of tests done there. 16. While the reanalysis data set includes 150 tests, the small sample sizes in individual cities
and missing data for some items (particularly because all types of activity did not occur in each test) limit our ability to analyze individual variables. Sample sizes are listed where appropriate.
17. Given the nature of this sample and the inability to generalize from the findings, the data set has not been adjusted to account for lender clustering.
18. The test report form captured a total monthly payment and individual parts of that total payment including monthly principal, interest, taxes, and insurance costs. A lender may or may not give a tester each of these items and a total. For this analysis, a test included a quote if it had an estimate of a total monthly mortgage payment OR an estimate that included at least the principal and interest portion of a total monthly payment (but no total recorded on the test form).
19. As noted earlier, the Urban Institute reanalysis data set did not include tester identifiers connected to each test. Therefore, analysis of the data set was conducted by pooling the tests without adjusting for tester clustering or homogeneity across pairs. For a fuller discus- sion of the merits of adjusting for tester effects, see Heckman and Siegelman (1993).
20. Mean differences in minutes between the white and black test pairs in each city are presented in annex A at the end of this chapter.
21. In this analysis, a tester is considered to have two quotes if the test form included quotes with different monthly payments. The type of loan for each of these payments is not known. The different monthly payments could reflect two calculations on the same loan product at dif- ferent interest rates or completely different loan products (with a different mix of require- ments, benefits, etc.). The level of “additional” information provided by the second quotes may not be equal. This analysis does not have enough information to judge the relative and comparable desirability and usability of the quotes received. It considers more information of any type to be favorable treatment.
22. In California, the prices of most of the homes made them too expensive to be eligible for FHA. 23. Advocates have long contended that FHA in Chicago has been an agent of neighborhood decline in minority communities; see Bradford (1979). In our analysis, the trend in Chicago for minorities to be told about FHA to a greater degree than whites was consistent regardless of the race of the neighborhood. When analyzing test pairs that included a white tester in a white neighborhood and a minority tester in a white neighborhood, the minority tester was told about FHA in 25 percent more cases. When whites with homes in integrated neighbor- hoods were paired with minorities in minority neighborhoods, the minority tester was still told about FHA in 57 percent more cases.
24. While this analysis is not definitive or generalizable, it does offer important insights for future testing on how the market works, the types of quotes possible, and how to construct a test instrument to capture loan information that can be statistically analyzed.
25. Monthly payment costs were standardized to be cost per $10,000 of loan amount to account for differences in loan amounts across testers. Differences in monthly payment costs were determined using a range of ±1 percent of the standardized monthly payment cost. Without this range, no test pair had exactly equal standardized monthly payments, but a good por- tion of the tests were within 1 percent of each other.
26. Again, the Urban Institute reanalysis does not have information on coaching or exceptions that might have been part of tests where similar product quotes were offered.
27. In more than two-thirds of the tests, minority testers preceded their white counterparts. However, the staggered nature of the tests led to white testers in different pairs conducting their tests on the same day or week as minority testers at different banks.
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28. It would be interesting to analyze test results by lender across cities to see if differences are consistent within a given lender regardless of city. This is not possible with the Urban Institute reanalysis data set, because the already small sample sizes are reduced further by the different information collected in each test (for example, not all tests have a quote that can be compared).
29. NFHA believes that analysis by lender across cities is critical for enforcement purposes. However, for the Urban Institute reanalysis small sample sizes make such an analysis highly problematic.
30. For a fuller discussion, see Galster (1993). In 1998, HUD commissioned the Urban Institute to conduct a new paired testing study of potential lending discrimination at the pre-application stage. This study will explore and develop sampling methods, test scenarios, and testing pro- tocols in order to advance paired testing methodologies for both enforcement and research. 31. NFHA found that in-depth knowledge gained during its scouting efforts was critical to suc-
cessful testing and analysis.
32. Research testing differs from testing done for enforcement purposes and as such may have different test structures and test report forms. For example, in research testing, the selection of the lender and the issues being tested are determined by a research design, not by an actual complaint. Suggestions made here specifically target research testing.
33. NFHA notes that the most serious types of differential treatment it found in its testing pro- gram occurred in these types of tests.
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