Aux.zicklin.baruch.cuny.edu

T h e E f f e c t o f I n c o m e , E t h n i c i t y / R a c e a n dI n s t i t u t i o n a l F a c t o r s o n M o r t g a g eB o r r o w e r B e h a v i o r L . J i d e I w a r e r e a n d J o h n E . Wi l l i a m s Studies examining mortgage choice behavior generally assume africtionless mortgage market in which borrower decisions areinfluenced only by economic variables. This study explores theinterface between demographic and institutional factors inherentin mortgage market logistics and the information flow that affectsborrower behavior. The efficiency of these processes isparticularly important when studying inner city real estatemarkets, since these markets are disproportionately representedby low income and minority households. The effect ofinstitutional factors was examined by conducting a survey ofborrower behavior in metropolitan Washington, DC. Thesecondary data findings indicate that ethnicity / race and incomeare jointly sensitive to borrower decision, confirming theclientele effect. The primary data findings also indicate thatinstitutional factors influence mortgage choice. Similarly,borrowers are influenced by the channel chosen to evaluatemarket information. However, income was not found to be asignificant determinant of borrower behavior.
This study examines borrower behavior by ethnicity/race and income with respectto market conditions and institutional factors. Particular emphasis is placed onlow-to-moderate income minority residents found in inner city residential areas.
The premise is that a proper understanding of the effect of market conditions onborrower decisions requires the analysis of financial market conditions, as well asthe institutional environment underlying borrower choice.
The analysis of financial market conditions on borrower decisions involves aninvestigation of the clientele effect (ethnicity/race). Employing the thirty-yearfixed-rate mortgage as a proxy for financial market conditions, its effect onborrower behavior is examined through segmenting mortgage market participantsinto categories defined by ethnicity/race and income.
J R E R ͉ V o l . 2 5 ͉ N o . 4 – 2 0 0 3 5 1 0 ͉ I w a r e r e a n d W i l l i a m s An examination of the institutional framework for mortgage activity is undertakenby erecting a schema to chart the decision spectrum involved in mortgageorigination from the borrower’s perspective. This highlights the institutionalenvironment that exists when borrowers apply for a loan. A questionnaire isdeveloped and used to collect primary data to test for the impact of institutionalfactors on the minority borrowers’ decisions to finance a housing purchase. Theinstitutional effect on borrower decisions will be captured by using proxies thatreflect the events generated by the mortgage search, decision and processingactions. These influences should capture the market conditions that the economicand financial variables omit. These institutional variables are: mortgage searchagents, mortgage search intensity and mortgage choice approach (see thequestionnaire in the Appendix).
This study tests the following hypotheses about institutional effects: informational flow exert significant influence on borrower behavior.
2. Institutional factors interact with income and race in the determination of While studies on the determinants of mortgage choice continue unabated, thereseems to be some convergence on socioeconomic effects, loan price/attributes andmarket conditions as the major determinants (Sa-Aadu and Sirmans, 1995; andSa-Aadu and Megbolugbe, 1995). Both Sa-Aadu and Sirmans and Sa-Aadu andMegbolugbe posit a framework of mortgage choice in which utility-maximizingborrowers operate within the context of a residential mortgage market that isefficient. This implies that all borrowers are as equally knowledgeable about themarket conditions as other market participants, and incur limited transaction costsin the loan applications process. One difficulty with this premise is that there isno centrally-available medium of information that is accessible to all marketparticipants. The market has sought to mitigate this in recent years through theprovision of consumer education to some low-to-moderate income borrowers, aspart of the approval process, with a view towards enhancing their homeownershiprate, as well as diminishing their probability of default on mortgage loans.
The basic premise in this study is that the organization of the mortgage marketgives ample room for frictional cost. However, the magnitude of this cost appearsto be skewed against market segments that are dominated by low-income andminority borrowers. For these borrowers, the mortgage search process appears toexert significant influence on the ultimate choice of mortgage instrument.1 Thisconditioning operates partly via access to information about the mortgage lendingprocess and partly by the perceptions of minority borrowers. The informationconstraint could result from limited access due to cost or lack of knowledge. Itmay also be a result of the differential interpretation of available information about E f f e c t o f I n c o m e , E t h n i c i t y / R a c e o n B o r r o w e r ͉ 5 1 1 market phenomena by market participants. The Institutional Framework forMortgage Origination presented in this paper traces the decision path for thetypical borrower.
This framework highlights the preliminary steps for a loan application—fromtenure choice to ownership timing and the initiation of the purchase contract—thattriggers the mortgage search process. This process incorporates: mortgage search,borrowing decision (choice of mortgage) and application processing. Ratner’s(1996) ethnographic synthesis of homeownership behavior calibrates this processinto presearch, search, purchase-finance and post-purchase phases. He notes in hiscross-cultural, multi-ethnic analysis that ‘‘Researchers have found that somefamilies were not looking for homes because they believed that, even if they foundone they could afford, financing would not be available. . . More than any otheraspect of the loan process, community members saw credit approval process asmysterious and capricious.’’2 In the light of the most recent market developments, some caveats are in orderhere. First, the introduction of automated underwriting (AU) along with risk-basedpricing models have the potential to revolutionize information flow to marketparticipants. However, online originations are still a very small but growingproportion of total originations. LaCour-Little (2000) estimated this to be of theorder of 1% in 2000.3 McWilliams (2002) reported estimates of online originationsby the TowerGroup of Needham, Massachusetts as having risen from 0.8% or $11billion in 1999 to 4.6% or $110 billion in 2002. Beier (2002) also reported thelatter’s projection for 2003 and 2005 as 6.1% and 12.8%, respectively, whilenoting, ‘‘It turns out that consumers are increasingly visiting on-line mortgagesites to get pricing and product information, but at the end of the day not manyare buying online or even submitting an application.’’ Moreover, the ‘‘digitaldivide’’ is likely to preclude online participation by the majority of the inner cityresidents. Quercia and Wachter (1996) while observing that the efficacy ofconsumer education has been mixed also noted that ‘‘post-purchase’’ financingcounseling tend to produce positive effects on mortgage performance.
A cursory look at the home-buying process and the mortgage market segmentswill throw light on these issues. It appears that there is a segment of the marketfor which market rigidities inherent in the organization of the mortgage marketexert considerable influence on financing behavior. This latter aspect has notreceived adequate treatment in studies on mortgage choice. Sa-Aadu and Sirmans(1995) and Sa-Aadu and Megbolugbe (1995) found market conditions a significantdeterminant of mortgage choice and the level of income to be insignificant. Marketconditions were measured by two variables: the ‘‘yield curve’’ and ‘‘mortgagedifferential.’’ While observing that the level of income is not significant in mortgage choicedetermination, Sa-Aadu and Megbolugbe (1995) concluded that ‘‘Borrower J R E R ͉ V o l . 2 5 ͉ N o . 4 – 2 0 0 3 5 1 2 ͉ I w a r e r e a n d W i l l i a m s heterogeneity and affordability constraints create clientele effects in mortgagemarkets.’’ In analyzing the sensitivity of mortgage market participants to changesin the thirty-year fixed-rate mortgage, Iwarere and Williams (1997) observed thatthe 18.5% decline in the1993 mortgage rate produced differential responses byvarious income groups as well as among ethnic/racial groups in the low tomoderate income category relative to the overall response. This section extendstheir analysis to zero-in further on the clientele effect arising from the jointinfluence of income and ethnicity/race.
M o r t g a g e M a r k e t S e n s i t i v i t y A n a l y s i s Mortgage market sensitivity analysis is conducted using 2000 and 2001 HMDAdata that covers the Washington, DC metropolitan area. This geographic emphasisin the HMDA sample was made to achieve consistency with the geographical arearepresented by the survey. Specifically, the sample data include the District andits surrounding counties (Prince George, Montgomery, Fairfax and Arlington). Thedata set includes Asians (9%), Blacks (32%), Hispanics (6%) and Caucasians(53%). The breakdown by income class is: low-to-moderate income, 36%;moderate income, 26%; and upper income, 38%.
As shown in Exhibit 1, corresponding to an 8.2 percentage increase in the fixed-rate thirty-year mortgage (FRM) between 1999 and 2000, the total increase in thevolume of mortgage applications across racial groups was 4.3%. When the totalchange in volume is segmented by race and income class, the volume forCaucasian mortgage applicants declined (Ϫ9.5%) following the increase in theFRM, while the volume for Blacks, Asians and Hispanics increased by 17.1%,26.1% and 26.7%, respectively. Mortgage participation behavior by income classesrevealed that the upper income group only increased mortgage applications by4.5%, whereas the middle and lower-to-moderate income classes increased theirrespective mortgage volume by 14.5% and 14.9%. Moreover, within the lower-to-moderate income class, Caucasians (Ϫ11.1) and Asians (Ϫ15%) recorded adecease in applications, whereas, Blacks (33.3%) and Hispanics (26.1%) increasedtheir mortgage activity volume.
Analyses of mortgage activity data for 2001 shows that a negative (Ϫ13.42%)change in the FRM coincided with a negative (Ϫ9.3%) change in mortgagevolume. By racial comparison, the volume for Caucasians (Ϫ10.5%) and Blacks(Ϫ24.1%) decreased, whereas the volume for Asians (13.8%) and Hispanics(17.5%) increased. When viewed by income class, although by differentmagnitudes, the mortgage volume decreased for all income groups (lower-to-moderate income, Ϫ1.4%; middle income, Ϫ10.6%; upper income, Ϫ21.5%)following the decline in the FRM. While the 2001 percentage change (1.23%) inthe mortgage volume for lower-to-moderate income Asians indicates a very largeincrease; the magnitude of the percentage change reflects the affect of a modestabsolute change on the small representative sample of this racial group.
E f f e c t o f I n c o m e , E t h n i c i t y / R a c e o n B o r r o w e r ͉ 5 1 3 E x h i b i t 1 ͉ Volume of Conventional Home Purchase Loans by Race and Income Group;
Interest Rate MovementChange in 30-year conventional mortgage rates Loan Volume MovementChange in loan volume (all income groups)Asian Change in loan volume (low-to-moderate income group)Asian Sources: Federal Financial Institutions Examination Council (FFEIC), Home. Mortgage DisclosureAct Data (HMDA), Freddie Mac.
The total interest elasticity (Exhibit 2) for all races is less than unity (0.52) for2000. When segmented by race, however, only Caucasians (Ϫ1.16) exhibit interestelasticity of less than unity. Also, the upper income group recorded an interestelasticity of less than unity (0.55), whereas the elasticity for both the lower-to-moderate income (1.82) and middle income (1.77) classes was greater than unity.
An examination of the relative elasticity of mortgage applications as measured bythe racial sensitivity index, reveals a large dispersion from the total (0.52) for allracial groups: Asians, 6.12; Blacks, 4.0; Hispanics, 6.27; and Caucasians, Ϫ2.23.
The total interest rate elasticity for 2001 is less than unity (0.69). The less thanunity elasticity holds true for all races excepting Blacks (1.8). The upper incomegroup displayed a higher elasticity (1.6) than both the middle income (0.79) andlower-to-moderate income (0.1) groups. The racial sensitivity indexes calculatedfrom the 2001 data were higher for Blacks (2.6) and Hispanics (1.9) than forCaucasians (1.1) and Asians (Ϫ1.5).
J R E R ͉ V o l . 2 5 ͉ N o . 4 – 2 0 0 3 5 1 4 ͉ I w a r e r e a n d W i l l i a m s E x h i b i t 2 ͉ Responsiveness of the Volume of Conventional Home Purchase Loans to Movements in Interest
Index by Race (low-to-moderate income group)Asian Notes:a Interest-Elasticity Index (Racial Sensitivity Index). Interest Elasticity Index is a measure of thesensitivity of the loan application volume to changes in interest rates. It is calculated as apercentage change in the conventional mortgage rate to the percentage change in loan volume.
Racial Sensitivity Index is computed as the ratio of interest-elasticity for a racial category to theelasticity for all races.
Source: Authors’ computation from Exhibit 1.
Among the lower-to-moderate income group, an observation of the interestelasticity by race for the year 2000 reveals a wide variation from the total (1.82).
The elasticity measures for Asians (Ϫ1.82) and Caucasians (Ϫ1.4) were less thanunity, whereas the measures for Blacks (4.07) and Hispanics (3.18) were greaterthan unity. The corresponding (2000) racial sensitivity measures were Ϫ0.77 and Ϫ1.0 for Caucasians and Asians respectively, while Blacks (2.24) and Hispanics(1.75) exhibited greater and positive sensitivities.
Continuing with the lower-to-moderate income group, in 2001 the interestelasticity for Asians (Ϫ9.2) represented a large dispersion from the total (0.10).
The elasticity for Hispanics (-0.51) was nearer unity; Blacks (2.7) and Caucasians(1.13) recorded elasticity measures greater than unity. Accordingly, the racialsensitivity calculations for Asians (Ϫ88.21) and Blacks (25.5) were larger thanthose calculated for Hispanics (4.9) and Caucasians (10.83).
E f f e c t o f I n c o m e , E t h n i c i t y / R a c e o n B o r r o w e r ͉ 5 1 5 The above analyses examined 2000 and 2001 HMDA data and provide inter-temporal results that support the findings by Iwarere and Williams (1997), whichalso concluded that a change in volume of mortgage applications with respect tothe change in the cost of the thirty-year FRM is effected by race and income.
Whether or not other demand side factors inherent in the institutional forces withinthe mortgage market are manifest in the race and income variables is a researchquestion that is further explored below.
The thrust of this scheme is to trace the path of consumer decision making in thelower-to-moderate income mortgage submarket from its inception at the tenurechoice juncture to loan closing. The journey runs through the housing andmortgage market segments, although more emphasis is placed on the latter. Thedecisions are classified into primary, secondary and tertiary stages. This providesa measure of market conditions in terms of the institutional environment thatunderlies borrower choice. This metric for the institutional dimension of themortgage market environment is needed to test its effect on borrower choice.
B o r r o w e r D e c i s i o n s w i t h i n t h e H o u s i n g M a r k e t S e g m e n t The ‘‘primary decision 1,’’ which is a determination of whether to own or not ismade by the sub-population that has the potential for owning or is made eligibleby virtue of affordability schemes (see Exhibit 3). This segment is referred to asthe ‘‘True Mortgage Market’’ [Ct] largely because purchasers overwhelminglyutilize debt for housing purchase. Numeric reconfiguration occurs due to tenurechoice and timing decisions. Further leakages occur due to all-equity purchasesand non-market means of debt capital sourcing [MC5A]. The decision onownership timing, (primary decision 2), generates the Housing Search Pool (HC4)from which the pipeline Subpopulation for Loan Origination is established (seeMC5). Other decisions made along this path include which brokers to patronize(B1) and when.
D e c i s i o n s w i t h i n t h e M o r t g a g e M a r k e t S e g m e n t The borrowers ‘‘tertiary decision’’ involves the timing of loan application, thechannel for selecting the lender (shopping via brokers, direct lender shopping,others), the choice of mortgage instrument and the choice of closing agent. Thelatter is made in conjunction with the home purchase contract. Borrowers gothrough a search process that involves an investigation of the mortgage marketenvironment and mortgage instruments through formal and informal sources.
These were referred to earlier as mortgage search agents. In the formal arena, theborrower employs the help of agents who operate in the housing and mortgage J R E R ͉ V o l . 2 5 ͉ N o . 4 – 2 0 0 3 5 1 6 ͉ I w a r e r e a n d W i l l i a m s E x h i b i t 3 ͉ Institutional Framework for Mortgage Origination
SUBPOPULATION READY FOR LOAN ORIGINATION POOL L1A-F.Individual FirmsB.Brokerage Firms/ Industry markets. These include real estate brokers, mortgage brokers, financial institutions,etc. The informal sources include friends, neighbors, and more recently, creditcounseling agents. Most applicants for a loan, particularly those in the low-incomeor minority population, have limited knowledge of the process, making themvulnerable to aggressive merchandizing efforts of agents or the predatory lendingpractices of sub-prime lenders.
Based on the information gathered, borrowers proceed to acquire product-specificinformation from lenders directly or by tapping into a network of informationsources electronically or otherwise. This search is the mortgage search intensity.
The greater the number of borrowing choices consulted by the borrower, thegreater would be the scope of publicly-available information reflected in thedecision and hence the more informed the mortgage choice. The semi-strongmarket efficiency hypothesis presupposes that all publicly-available information isreflected in loan pricing. However, negotiated effective cost of the loan may differ E f f e c t o f I n c o m e , E t h n i c i t y / R a c e o n B o r r o w e r ͉ 5 1 7 from the quoted rates due to information asymmetry between the lender andborrower. The intensity of search becomes crucial for closing this gap.
Borrowers then evaluate this information to make a choice of mortgage instrumentand lender. The evaluation could be on their own accord, by reliance on informalagents, or by falling back to formal agents as real estate brokers, mortgage brokers,etc. The agent-advisors are capable of tilting borrower decisions sub-optimally.
This is the mortgage choice approach. Submission of an application to the lendercompletes the search process and ushers in the mortgage loan applicationprocessing stage.
S a m p l i n g D e s i g n a n d P r o c e d u r e The data for testing for the impact of the institutional factors on minority mortgageborrowers’ decision was generated through primary data collection from theDistrict of Columbia and four major counties in the Washington, D.C.
metropolitan area in March and April of 1996. These are Arlington and Fairfaxcounties in Northern Virginia; and Montgomery and Prince Georges Counties inMaryland. Based on the 1990 Census, the metropolitan population was 25.4%Black, 6.2% Asian and 6.8% Hispanic. Exhibit 4 gives the population distributionby ethnicity for these component counties. The sampling frame is defined ashomeowners in the five jurisdictions noted above. A stratified sampling procedurealong the jurisdictional lines was employed.
Sampling was done by a combination of door-to-door contacts and contacts inpublic places such as neighborhood centers. This is because the telephone list thatconstitutes the most comprehensive sampling frame available is orderedalphabetically by county thus obscuring desired lower level geographicalbreakdowns. Some respondents preferred to fill out the survey questionnaire ontheir own, in which case the interviewer made an appointment to pickup theresponse or have it mailed in. Mail-in responses were relatively fewer.
The results of the survey are presented in the summary statistics in the Appendixand the geographic distribution of the sample (Exhibit 5). One-hundred fiftyresponses were obtained in the final analysis, a 19% response rate. Blacks, whoconstitute about two-thirds of the minority population in the five jurisdictions atthat juncture, were over-represented in the sample at 75%. Prince Georges Countywas similarly over-represented in the sample (55%) relative to its share of minoritypopulation in the jurisdictions (38%) while Fairfax was under-represented at 4%relative to its share of minority population, 14.1%. The geographic coverage ofthe sample is very broad for the District of Columbia, Montgomery and PrinceGeorges counties but rather limited for Arlington and Fairfax counties. There aresignificant item non-responses as indicated by the summary in the Appendix.
J R E R ͉ V o l . 2 5 ͉ N o . 4 – 2 0 0 3 E x h i b i t 4 ͉ Washington D.C. Metropolitan Area (& MSA) Population Distribution
Notes:a The population of Washington, D.C. and vicinity reported here includes the District of Columbia and the abutting counties covered by our survey. It is asubset of Washington, D.C. Primary Metropolitan Statistical Area (DC PMSA), which also includes Calvert, Charles and Frederick Counties in Maryland;Loudon, Prince William and Stafford Counties in Virginia and Cumberland County in West Virginia.
b The Washington-Baltimore Metropolitan Statistical Area extends beyond the immediate focus. With a 1996 population of 7,164,519, it consists ofBaltimore PMSA (2,474,118), Hagerstown PMSA (127,278), and Washington (DC-MD-VA-WV) PMSA (4,563,123).
c AI stands for American Indian.
d The Hispanic population is reflected among the other races. Their percentages are not to be added to the percentages for other races in calculating theoverall total for each county. Their percentages are isolated for comparison purposes only.
Source: 1998 County and City Extra: Annual Metro, City and County Data Book. The numbers represent 1996 population estimates extrapolated from the1990 census.
E f f e c t o f I n c o m e , E t h n i c i t y / R a c e o n B o r r o w e r ͉ 5 1 9 E x h i b i t 5 ͉ Minority Population Distribution and the Geographic Distribution of the Sample
Hill, Chevy Chase, Congress Heights,Edgewood, Fort Lincoln, Palisade /Friendship, Shaw Gaithersburg, Germantown, Silver Spring,Wheaton Beltsville, Bowie, Capitol Heights, Forestville, Fort Washington, Glenn Dale, Greenbelt,Hyattsville, Landover, Lanham, Laurel, OxonHill, Riverdale, Temple Hills, Upper Malboro Source: 1998 County & City Extra: Annual Metro, City and County Data Book; Survey Results.
Nearly half of the respondents (46%) reported having selected their mortgageloans for reasons other than the lowest available rate. The 24% of respondentswhose choice of mortgage was a result of ‘‘convenience’’ could have done so tocircumvent the tedious search process while the 21% who responded as ‘‘My onlyoption’’ might either have had to deal with some credit problems, or beendissuaded by the frictions of the search process.
Thirty-two percent of the respondents obtained their loans directly fromcommercial banks, 50% through brokers and 6% from savings and loaninstitutions. The corresponding distribution reported in the total HMDA data setfor 1994 was 32.4%, 46.4% and 17.4%, respectively.
An average of two potential borrowing sources was consulted before making theborrowing decision, indicating a low mortgage search intensity. There does notappear to be a significant preference for any single mortgage search agent sinceinformation for advice on the mortgage market and loan search process wasdistributed fairly evenly among real estate brokers (20%), mortgage brokers (17%)and lending officers of financial institutions (17%) with slightly less proportionseeking advice from friends and neighbors (13%). Forty percent relied on realestate agents and friends/neighbors combined. About the same proportion also J R E R ͉ V o l . 2 5 ͉ N o . 4 – 2 0 0 3 E x h i b i t 6 ͉ Results of Chi-Square Tests of Independence Among the Variables
1. RACE(2), MCA(3), FRM(2) Reject Ho: VariablesStatistically Dependent 2. RACE(2), MSA(6), FRM(2) Accept Ho: VariablesIndependent Statistically 3. RACE(2), MSI(2), FRM(2) Accept Ho: VariablesIndependent Statistically 4. INCOM(3), MCA(3), FRM(2) Accept Ho: VariablesIndependent Statistically 5. INCOM(3), MSA(6), FRM(2) Accept Ho: VariablesIndependent Statistically 6. INCOM(3), MSI(2), FRM(2) Accept Ho: VariablesIndependent Statistically 7. INCOM(3), RACE(2), FRM(2) Accept Ho: VariablesIndependent Statistically 8. MCA(3), MSI(2), MSA(6), FRM(2) Reject Ho: VariablesStatistically Dependent Notes:a␣ ϭ significance level; d.f. ϭ degree of freedom.
* Significant at the 10% level.
** Significant at the 5% level.
E f f e c t o f I n c o m e , E t h n i c i t y / R a c e o n B o r r o w e r ͉ 5 2 1 relied on agents and brokers combined. Twenty percent employed three or moresearch agents.
The distribution of mortgage choice approaches, which reflect the channels bywhich borrowers evaluate market information to select the lender and mortgageinstrument, is split almost equally among mortgage institutions, real estate agentsand informal approaches (self, and friends/neighbors).
More borrowers appeared to select lenders and instruments through real estateagents (33%) than actually relied on their advice for garnering market information(20%). This suggests that the real estate agents have more influence on borrowers’ultimate choice of mortgage than their knowledge of the mortgage market woulddictate.
The test for the joint effect of race (RACE) or income (INCOM) and each of thethree institutional variables (MSA, MSI and MCA) on borrower choice betweenvariable or fixed-rate mortgage (FRM) employs the chi-square test, a non-parametric test of independence among variables. The hypothesis for each of thejoint tests typically is (e.g., for ethnicity, mortgage choice approach or mortgagechoice): RACE, MCA and FRM are independent (i.e., statistically unrelated).
RACE, MCA and FRM are statistically dependent.
H and H are the null and alternative hypotheses respectively for the chi-square statistic, ␹2(␣, dƒ), with a confidence level of ␣, and dƒ degree of freedom. Thetests for joint effect of race, institutional variables and mortgage choice were allat 10% confidence level as they were not found to be significant at the 5% level.
The degrees of freedom were determined as [(p.q.r.) Ϫ 1 Ϫ v] where p, q and rare the number of categories for the variables and v is the number of parametersestimated. The calculated values of chi-square The null hypothesis of independence among the variables is accepted. However,concluding statistical independence among the variables would imply that theindicated institutional effects do not affect mortgage choice.
The chi-square test is not as robust as parametric tests and yields only approximateresults. Its merit is in its simplicity and the fact that it does not require that itsunderlying population parameter follow any particular distribution. These premises J R E R ͉ V o l . 2 5 ͉ N o . 4 – 2 0 0 3 5 2 2 ͉ I w a r e r e a n d W i l l i a m s were most appropriate for the data due to the limitations surrounding the samplingprocedure.
V a r i a b l e D e f i n i t i o n s The six variables employed in the tests are: Mortgage Search Agents. The sources consulted for the purpose ofgathering information about the mortgage market. MSA is coded as: 1ϭ real estate agents; 2 ϭ friends and neighbors; 3 ϭ mortgage bankersand brokers; 4 ϭ depository institutions; and 5 ϭ multiple sources.
Mortgage Choice Approach. The sources relied upon for making thefinal decision about the mortgage instrument after informationevaluation. MCA is coded as: 1 ϭ mortgage institutions (lenders andbrokers); 2 ϭ informal sources (self, friends/neighbors); and 3 ϭ realestate agents Mortgage Search Intensity. The number of borrowing sources consultedprior to making the loan decision. An average of two sources wasconsulted. MSI is calibrated as: 0 ϭ 0–2 sources; and 1 ϭ Ͼ2 sources.
Ethnicity of the borrower. Due to sample size problem, this wasclassified as Black and non-Black with Caucasians dominating thelatter group. RACE is calibrated as: 1 ϭ Black; and 0 ϭ Other.
Borrower’s choice between fixed and variable rate mortgages. FRMis calibrated as 0 ϭ adjustable-rate mortgage; and 1 ϭ fixed-ratemortgage.
Income of borrower. This was broken into: 1 ϭ lower-to-moderateincome; 2 ϭ middle income; and 3 ϭ upper income. This nomenclaturewas built around the 1996 median income of $45,900 for the DC-PMSA. Lower-to-moderate income group consisted of borrowers withincomes less than 80% of this median (Ͻ$40,000). The middle incomegroup earned 80%–120% ($40,000–$55,000) and the rest were upperincome (Ͼ$55,000).
Te s t s f o r J o i n t - E f f e c t s o f E t h n i c i t y / R a c e ( o r I n c o m e ) a n dI n s t i t u t i o n a l V a r i a b l e s The results of the tests on the joint influence of borrower’s race (RACE) or income(INCOM) and the institutional variables (MCA, MSI and MSA) on mortgage choiceare tabulated in Exhibit 6. The test for the joint effect of race (RACE) andmortgage choice approach (MCA) on mortgage choice (FRM) was found to besignificant at the 10% level. The power of the test was 0.0697, indicating that theprobability of incorrectly rejecting the null hypothesis of dependence among thevariables is 6.97%. This implies that ethnicity (RACE) interacts with the channelsby which borrowers evaluate market information (MCA) in borrowers’ mortgage E f f e c t o f I n c o m e , E t h n i c i t y / R a c e o n B o r r o w e r ͉ 5 2 3 choice. These channels include mortgage institutions, real estate agents or informalapproaches. The joint effect of race and the other two institutional variables (MSIand MSA) were not found to be significant in this regard. Similarly, the hypothesisthat ‘institutional forces interact with income in the determination of mortgagechoice’ is rejected as indicated by the results of the tests relating income (INCOM)to the institutional variables (MCA, MSI and MSA). This latter result is contraryto the conclusions from the analysis of HMDA data. The test for the joint effectof race and income in mortgage choice determination also indicates an absenceof any relationship among the variables. This might be a consequence of thesampling distribution.
Te s t f o r t h e C o m p o s i t e E f f e c t o f I n s t i t u t i o n a l V a r i a b l e so n M o r t g a g e C h o i c e The test for the joint-effect of all three institutional variables (MCA, MSI andMSA) on borrower choice between FRM and VRM was found to be significant atthe 5% level. Individually, none of the variables exerted any influence on theborrowing decision while only the mortgage choice approach (MCA) influencedthis decision when interfaced with RACE.
This study examined the intricacies associated with the influence of demographicand institutional forces on mortgage choice through an inter-temporal analysis ofthe HMDA data coupled with 1996 survey data on borrowers in the WashingtonD.C. Primary Metropolitan Statistical Area. The exploration of the institutionalfactors inherent in the mortgage market logistics and information flow in this arealeads to the conclusion, based on a chi-square test at the 5% level of significance,that these forces exert a significant influence on borrower behavior. Race inconjunction with the channel by which borrowers evaluate market information toselect a lender and mortgage instrument was also found significant in this decisionwhile income alone or interfaced with the institutional forces was not significant.
The latter confirms earlier studies by Sa-Aadu and Sirmans (1995) and Sa-Aaduand Megbolugbe (1995).
Institutional variables were constructed after a close evaluation of the path thatborrowers in the mortgage market have to navigate in making borrowing decisions,providing another dimension to the measurement of market conditions. Thefindings indicate that the mortgage market is not frictionless. Cultural,demographic and institutional forces interact to affect the availability and use ofinformation. Hence, borrower choice, such as the choice between fixed andvariable rates, is made within the institutional context defined by the marketenvironment of the lending and borrower decision paths. The friction along thisdecision path (MSA, MSI and MCA) is able to filter out some of the availableinformation for borrower decision making, depriving them of utility-maximizing J R E R ͉ V o l . 2 5 ͉ N o . 4 – 2 0 0 3 5 2 4 ͉ I w a r e r e a n d W i l l i a m s outcomes. This will tend to occur more in the sub-prime mortgage market or underpredatory lending practices particularly for some low-to-moderate income,minority borrowers. This suggests that such borrowers face an imperfect marketand require assistance with clearing the frictions to information flow along theborrower’s decision path to optimize their borrowing decision. Automation andrisk-based pricing would help only as the wall of digital divide breaks down. Sincethis study is regional in scope, an expanded study of the broader, national audienceemploying more robust sampling techniques will be needed to validate the impactof the institutional constraints.
R e s i d e n t i a l M o r t g a g e S e a r c h S u r v e y 10. Your choice of lender was made through In your loan search, which of the following did you consult for advice or direction? d. Depository institutions (banks, S&L, Credit Union) h. Three or more sources (a. + b. + c. + d.) Why did you chose your current loan among others? 12. Potential borrowing sources considered 16. Length of time in current residence (years) 19. Number of Children under 18 yr. Living at home 20. Age of oldest child living at home (years) E f f e c t o f I n c o m e , E t h n i c i t y / R a c e o n B o r r o w e r ͉ 5 2 7 6. If adjustable, is it convertible? Yes ( 9. Your loan application was submitted to a: Commercial Bank ( 10. Your choice of lender was made through.(check all applicable) 11. In your loan search, which of the following did you consult for advice 12. How many potential borrowing sources did you consult prior to your 13. Why did you choose your current loan, among others? 16. How long have you lived in your current residence? 19. Number of children under age 18 living at home? J R E R ͉ V o l . 2 5 ͉ N o . 4 – 2 0 0 3 5 2 8 ͉ I w a r e r e a n d W i l l i a m s 1 Courchane, Nebhut and Nickerson (2000) explained this thus: ‘‘The decision to approve or deny a loan is based primarily on the applicant’s credit but also may includedemographic, economic and property-specific attributes.’’ 2 Ratner (1976), pages 121 and 125. Ignorance, cultural attitude to debt, lack of understanding of the application and mortgage finance system prompted theseperspectives.
3 In the light of the digital divide, this development potentially creates mortgage market frictions for low-to-moderate income minorities who have disproportionately lower accessto the information superhighway.
Beier, G., The Uber Loan Officer, Mortgage Banking, 2001, December, 36–44.
Courchane, M., D. Nebhut and D. Nickerson. Lessons Learned: Statistical Techniques andFair Lending, Journal of Housing Research, 2000, 11:2, 277–96.
Iwarere, L. J. and J. E. Williams, Revisiting the Effect of Income and Market Environmenton Mortgage Choice, Paper presented at the African Real Estate Society Conference,Johannesburg, South Africa, June 17–19, 1997.
LaCour-Little, M., The Evolving Role of Technology in Mortgage Finance, Journal ofHousing Research, 2000, 11:2, 173–205.
McWilliams, C. H., Booming WEB Business, Mortgage Banking, 2002, 2002, 22–9.
Quercia, R. G. and S. M. Wachter, Homeownership Counseling Performance: How Can ItBe Measured?, Housing Policy Debate, 1996, 7:1, 175–200.
Ratner, M. S., Many Routes to Homeownership: A Four-Site Ethnographic Study ofMinority and Immigrant Experiences, Housing Policy Debate, 1996, 7:1, 103–45.
J. Sa-Aadu and C .F. Sirmans, Differential Contracts, Heterogeneous Borrowers, and theMortgage Choice Decision, Journal of Money, Credit and Banking, 1995, 27, 498–510.
J. Sa-Aadu and I. F. Megbolugbe, Heterogeneous Mortgage Selection, and MortgagePricing, Journal of Housing Research, 1995, 6:2, 333–48.
L. Jide Iwarere, Howard University, Washington, DC 20059 or liwarere@fac.
howard.edu. John E. Williams, Morehouse College, Atlanta, GA 30014 or jwilliam@morehouse.
edu.

Source: http://aux.zicklin.baruch.cuny.edu/jrer/papers/pdf/past/vol25n04/08.509_528.pdf