Financial Services for Low‐ and Moderate‐Income Households Michael S. Barr, Law School, University of Michigan This paper was delivered at a National Poverty Center conference, “Access, Assets, and Poverty,” in October, 2007. This project was supported in part by funds provided by the Ford Foundation and in part by funds provided by the U.S. Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation, #5 U01 PE000001‐05 and #1 U01 AE000002‐01. The opinions and conclusions expressed herein are solely those of the author(s) and should not be construed as representing the opinions or policy of any agency of the Federal government. Financial Services for Low- and Moderate-Income Households
Michael S. Barr
Introduction
This paper presents new empirical evidence documenting the financial services
behavior of low- and moderate-income (LMI) households. 1 The Detroit Area Household
Financial Services (DAHFS) study is the first survey using a random, stratified sample to
explore the full range of financial services used by LMI households, together with
systematic measures of household preference parameters, demographic characteristics,
and households' balance sheets. Results from over 1,000 interviews in the DAHFS study
suggest that the financial services, credit and payments systems "technology" in the
formal and informal sectors imposes an efficiency cost to LMI households. Like their
higher-income counterparts, LMI households regularly conduct financial transactions:
they convert income to a fungible medium, make payments, save, borrow, seek
insurance, and engage in economic decision-making. Yet the financial services system is
not designed to serve them well.
Contrary to popular belief, being unbanked is not a fixed state and the line
between formal and informal financial services systems is not impermeable. Most of the
1
This paper is based on joint work with Jane Dokko and Benjamin Keys. Any errors are the author’s
alone. Data are from Michael S. Barr, Principal Investigator, Detroit Area Household Financial Services
(DAHFS) Study, Survey Research Center, University of Michigan (2006). The DAHFS was supported by
the Ford Foundation, the MacArthur Foundation, the Annie E. Casey Foundation, the Fannie Mae
Foundation, the Mott Foundation, the Community Foundation of Southeast Michigan, the National Poverty
Center, CLOSUP, and the Provost, Vice President for Research and Law School of the University of
Michigan. The views presented here are those of the authors and not of the supporting organizations.
unbanked previously had a bank account, and a good number of banked households were
recently unbanked. While the unbanked are much more likely to turn to alternative
providers than banked households, even banked individuals often use some alternative
financial services providers. In fact, one type of alternative credit provider, payday
lenders, exclusively serve banked households. Though associated with high fees, both
banked and unbanked sample members often describe AFS transactions as "convenient"
and "easy to use." Bank accounts are usually not well structured to serve LMI
households. Bank fees are quite high, and over half of banked LMI households reported
paying minimum balance or overdraft or insufficient fund fees in the previous year. The
financial services mismatch means that LMI households must choose among the fees
associated with bank account ownership or the fees of AFS providers, and that the
highest fees for basic financial services are concentrated among those least able to pay.
The paper first describes the financial services marketplace for low- and
moderate-income households. The following section describes the source of data for the
paper. Next, the paper analyzes the mix of banking and alternative financial services
used by banked and unbanked households. The paper then turns to alternative credit
markets, and explores the relationship between payday borrowing and other credit.
Lastly, the paper suggests directions for financial services policy, and then concludes.
The Financial Services Marketplace for LMI Households
Low-income households often lack access to bank accounts and face high costs
for transacting basic financial services through check cashers and other alternative
financial service providers. 2 These families find it more difficult to save and plan
financially for the future. Living paycheck to paycheck leaves them vulnerable to
medical or job emergencies that may endanger their financial stability, and the lack of
longer-term savings undermines their ability to invest in improving their skills,
purchasing a home, or sending their children to college. High-cost financial services and
inadequate access to bank accounts may undermine widely shared societal goals of
reducing poverty, moving families from welfare to work, and rewarding work through
incentives such as the Earned Income Tax Credit (EITC). 3
Nearly 25% of low-income American families – those earning under $18,900 per
year -- are “unbanked”: they do not have either a checking or savings account. 4 Even
among moderate-income households earning between $18,000 and $33,900 per year,
nearly 13% of households lack any bank account. 5 Beyond the “unbanked,” moreover,
many additional low- and moderate-income families have bank accounts, but also rely on
high-cost non-bank providers to conduct much of their financial business—such as
cashing checks, buying money orders, or taking out payday loans.
In lieu of bank-based transactions, savings, and credit products, LMI households
often rely on the more costly alternative financial sector (AFS). AFS providers offer a
wide range of services, including short-term loans, check cashing, bill payment, tax
preparation, and rent-to-own products, most often in low-income urban neighborhoods.
These AFS providers are currently the only means available for many low-income
persons to access basic financial services, but they often come at a high price.
2
See generally, Barr, Banking the Poor (2004).
See 26 U.S.C. § 32 (2006).
4
Brian K. Bucks, et al., Recent Changes in U.S. Family Finances: Evidence from the 2001 and 2004
Survey of Consumer Finances, FEDERAL RESERVE BULLETIN A1-38, at A13(March 22, 2006).
5
Id.
3
For example, while check cashers offer essential services, the fees involved in
converting paper checks into cash are high, relative both to income and to analogous
services that middle- and upper-income families use, such as depositing a check into a
bank account or electronic direct deposit. Check-cashing fees vary widely across the
country, and between types of checks, but typically range from 1.5% to 3.5% of face
value. The industry reports that it processes 180 million checks totaling $55 billion
annually, generating $1.5 billion in fees. 6 Almost all of these checks are low-risk payroll
(80%) or government-benefit (16%) checks. 7 While even payroll checks are not without
some credit and fraud risk, average losses from “bad” checks at check-cashing firms are
low and compare favorably with inter-bank rates. 8
The high costs of alternative financial services raise several concerns. First, the
costs of these basic financial transactions reduce take-home pay. A worker earning
minimum wage, working full time, and making under $12,000 a year would pay $250 to
$500 annually just to cash payroll checks at a check-cashing outlet, in addition to fees for
money orders, wire transfers, bill payments, and other common transactions. 9 High fees
for tax preparation, filing, check-cashing, and refund anticipation loans reduce the value
of EITC payments by over 10%. 10 Bringing low- and moderate-income families into the
6
Fin. Serv. Ctrs. of Am, (FiSCA), About FiSCA, http://www.fisca.org/about.htm (last visited Nov. 14,
2006); Barr, Banking the Poor, at 142.
7
ED BACHELDER & SAM DITZION, DOVE CONSULTING, SURVEY OF NON-BANK FINANCIAL INSTITUTIONS 9,
34 (2000), available at http://www.ustreas.gov/press/releases/reports/nbfirpt.pdf.
8
Banking the Poor.
9
See Arthur B. Kennickell et al., Recent Changes in U.S. Family Finances: Results from the 1998 Survey of
Consumer Finances, 86 FED. RES. BULL. 1, 9 - 11 (2000); BACHELDER & DITZION, supra note 7, at 34
fig.6.5.
10
ALAN BERUBE ET AL., BROOKINGS INST., THE PRICE OF PAYING TAXES: HOW TAX PREPARATION AND
REFUND LOAN FEES ERODE THE BENEFITS OF THE EITC (2002), available at
http://www.brookings.edu/es/urban/publications/berubekimeitc.pdf.
banking system can help reduce these high transaction costs, substantially increasing the
purchasing power of these families.
Second, without a bank account, low-income households face key barriers to
increased saving. Promoting low-income household savings is critical to lowering
reliance on high-cost, short-term credit, lowering risk of financial dislocation resulting
from job loss or injury, and improving prospects for longer-term asset building through
homeownership, skills development, and education.
Third, without a bank account, it is more difficult and more costly to establish
credit or qualify for a loan. A bank account is a significant factor -- more so, in fact, than
household net worth, income, or education level -- in predicting whether an individual
also holds mortgage loans, automobile loans, and certificates of deposit. 11
While there are many reasons for the lack of bank account ownership among LMI
households, their preferences interact with the financial and non-pecuniary costs of
account ownership in their decisions to become and remain unbanked. Uncovering the
tradeoffs households are willing to make between the costs and benefits of bank account
ownership is paramount to ascertaining how to integrate the unbanked into the financial
mainstream. In addition, preferences determine whether varying account features will
induce increases in account ownership. Despite the need to understand the role of
preferences, there is little research to inform us of households’ preferences for bank
account ownership, as well as the kinds of products that they would find attractive
enough to open some type of bank account.
11
Jeanne M. Hogarth & Kevin A. O’Donnell, Banking Relationships of Lower-Income Families and the
Government Trend Toward Electronic Payment, 85 FED. RES. BULL. 459, 463 (1999).
For many LMI households, checking accounts are ill-suited to their needs and for
many financial institutions, checking accounts are expensive to offer for low-balance
accounts. (See Barr, 2004.) Living paycheck to paycheck, LMI households face a
significant risk of over-drafting their checking accounts and paying high fees. Many LMI
households have had a bank account in the past, but were unable to manage their finances
or unwilling to pay high fees. Minimum balance requirements may also be a significant
barrier for low-income households. By contrast, electronically based bank accounts and
payment cards might provide a more efficient and effective means of serving the
financial services needs of these households.
To explore the range of financial services needs, behaviors and attitudes of LMI
households, collecting additional field data was imperative. The Detroit study, conducted
with the University of Michigan’s Survey Research Center, attempted to fill that gap.
Description of Survey, Sampling, and Data
The data for this paper are from a survey we designed, which was administered by
the Survey Research Center (SRC) at the University of Michigan. The survey focuses on
LMI individuals’ experiences with formal and informal financial institutions, in addition
to their socio-economic characteristics. Because there is no such comprehensive survey
about the financial services experiences and attitudes of low- and moderate-income
households, the questionnaire required extensive development, pretesting, and validation.
There were numerous challenges in tailoring a survey for LMI households. We built on
the work of the OCC and Shorebank, which had conducted more limited surveys
regarding low-income households’ banking status, as well as the Survey of Consumer
Finance, Panel Study on Income Dynamics, and the Health and Retirement surveys,
which are not focused on low-income households and are not tailored to their
experiences. We adapted questions for LMI households, developed a wide range of new
questions to cover the broad range of financial services of interest, and vetted the survey
instrument with our advisory board and a wide range of outside experts in financial
services, low-income communities, survey methodology, psychology, sociology,
economics and related disciplines, as well as with practitioners.
SRC’s Survey Methods Group provided invaluable assistance in working with us
on question wording and ordering. We also conducted extensive pretesting on a
representative subsample of LMI households to validate our methodology and
instrument. Moreover, we were concerned about the overall literacy level and the ability
of LMI households to provide reliable responses to seemingly difficult questions about
financial behavior and individual preference parameters. To address these concerns, we
conducted cognitive interviews regarding the most difficult questions and modified the
instrument based on how these subjects processed the questions. The final survey was
programmed for computer-assisted, in-person interviewing, and then the programmed
survey was tested again multiple times. The conjoint analysis focuses on a payment card
intended to facilitate the receipt of income, storage of value, and payment of bills. We
chose this type of an account for two main reasons. First, as noted above, electronically
based bank accounts and payment cards can be offered by financial institutions, payment
card providers, employers and government agencies at lower cost and lower risk to LMI
households, as compared to checking accounts. But little is known about whether such
products provide sufficient utility to LMI households to generate scale. Second, given
the inefficiencies in the payments system, such as those from an over- reliance on paper
checks, that impose costs on the national economy, we felt that exploring the potential
take-up of a payment card would be useful for policy. Increasing the efficiency in the
payments system for the poor could have modest positive effects on the economy as a
whole. Because of positive network externalities, funds spent converting the poor to
electronic payment might speed conversion to electronic payments more generally.
After a year’s work on sample design and survey development, we were in the
field interviewing households from July 2005 through March 2006. In addition to our
field staff, the SRC’s Survey Design Group aided in monitoring and adjusting our field
strategy. The final survey instrument is, on average, approximately 76 minutes in length,
and required nearly 9 hours of effort for each completed interview. All interviews were
conducted in person, usually in the home of the respondent.
Our sample consists of 1,003 interviews, with a response rate of 65 percent. The
sample members are selected to form a stratified random sample of the Detroit
metropolitan area (Wayne, Oakland, and Macomb counties). We drew sample members
from census tracts with median incomes that are 0-60% (“low”), 61-80% (“moderate”),
and 81-120% (“middle”) of the Detroit area’s median income of $49,057. The sample
frame includes more census tracts from the LMI strata than the middle one. Hence
sample members are more likely to be drawn from the low- and moderate-income strata.
Stratum definitions do not, however, restrict the income levels of the sample members to
fall within these ranges. For purposes of this paper, data are reported restricted to only
LMI strata and are weighed to represent these LMI communities.
The Unbanked and Underbanked
Overall, the demographic characteristics of our sample reflect the average
characteristics of LMI households in the Detroit metropolitan area. Our sample is socioeconomically disadvantaged relative to the average American household. The sample is
more two-thirds African-American and two-thirds female. Only 20% of respondents are
currently married, and 46% have never been married. Nearly 30% have less than a high
school diploma, but 47% have some education beyond high school. While most of the
respondents are of working age, only 56% were employed at the time of interview. The
median household income of the sample is $20,000, which is much lower than the Detroit
metropolitan area’s median income of $49,057 and the national median of $44,684.
Some 33% of these households lived below the poverty line in 2004, and 29% percent do
not have a bank account. The modal respondent to the survey is an African-American
working-age woman, without children, who has lived in the Detroit area for a long time.
Her income from work is low and close to the federal poverty line, and she likely
receives some assistance from the government.
Twenty-nine percent of individuals in our sample do not have a bank account.
While 29% of individuals in our sample are unbanked, 6% of respondents live with
another adult with a bank account, leaving 23% of all households in the DAHFS sample
unbanked. This sample proportion is consistent with previous large-scale surveys of the
low- and moderate-income population, which have estimated the proportion unbanked as
20-30% of households and 28-37% of individuals (Aizcorbe, 2003; Dunham, 1998;
Seidman, 2005). Evidence from nationally-representative surveys suggests that the
number is close to 10% of the overall population (Aizcorbe, 2003).
The unbanked subpopulation of our sample is younger (47% between the ages 2140), predominantly African-American (78%), and with relatively less education (37% did
not finish high school). The unbanked are much more likely to be unemployed and much
more likely to live below the poverty line. Fully 40% of the unbanked are unemployed,
and 50% of the unbanked live in poverty. The unbanked are economically isolated and
have worse permanent job prospects than those with bank accounts.
There is significant interest among the unbanked population to entering the
mainstream financial services sector. Of the unbanked respondents, 75% say they would
like to open a bank account in the next year, and 33% say they have looked into getting a
bank account. However, 17% report that a bank denied their application to open a bank
account.
To address which financial barriers were most important to the unbanked, they
were asked what improved feature of a bank account would make them most likely to
open an account. For 29% of the sample, lower fees were perceived as the primary
facilitator to opening an account, while 20% considered more convenient bank hours and
locations as their chief motivation. Respondents cite less confusing fees (16%), lower
minimum balances (14%), and the ability to get money faster (10%) as the other main
obstacles they’d like to see removed. Table [x] reports the distribution of responses of
the unbanked regarding the feature that would make them most likely to open a bank
account.
Don't have enough money
Unemployed
Reasons Why Unbanked
Can't save
13%
15%
Bad credit
5%
Don't trust banks
5%
10%
4%
Don't need one
High bank fees
7%
8%
3%
8%
Owes bank money
Inconvenient
Bank accounts are not secure
6%
Easier without bank account; more
control
Other reasons
16%
Don't have enough money
Unemployed
Reasons Why Unbanked
All Respondents
Can't save
13%
15%
Bad credit
11%
5%
Don't trust banks
29%
5%
10%
Don't need one
Lower
High
bankFees
fees
4%
Less Confusing Fees
20%
7%
8%
Owes
bank
money
Lower
Min
Balance
Get Money Faster
3%
8%
10%
6%
16%
14%
16%
Inconvenient
Convenience
Bank
accounts areNone;
not secure
If volunteered;
Nothing
Easier without bank account; more
control
Other reasons
Notably, being “unbanked” is a not a permanent state of the world. Of the subsample of unbanked respondents, 70% previously had a bank account of some form, and
66% of these individuals had an account within the last 5 years. The formerly-banked
report that 70% of them chose to close the account themselves, citing moving, worrying
about bouncing checks, and excessive fees as their reasons for closing the account. The
remaining formerly-banked, 30%, report that the bank closed the account. The majority
of cases of bank accounts closed by the bank were due to bounced checks and overdrafts.
Without bank-based transactions, the first option for the formerly-banked is a grocery or
liquor store (55%), though many turned to check cashing outlets (17%) for their financial
services.
Not only are some of the unbanked formerly bank account holders, but the reverse
is true as well. Despite currently being “banked”, 12% of account holders had a previous
bank account closed by the bank (not due to a move). Nearly 2/3 of the banked say the
accounts were closed by the bank due to a low balance or an inactive account (63%), or
bounced checks or overdrafts (51%). In addition, 55% of the banked sub-population
closed a previous bank account, most commonly due to the convenience of another bank
(27%) or excessive fees (21%). Far from the belief that “unbanked” status is an
absorbing state, in fact there appears to be a great deal of cycling in and out of being
banked.
Banked respondents use a variety of services offered by their banks. With respect
to income receipt, 63% use direct deposit when receiving income, and 14% report that
they purchased a money order from a bank. During the 12 months prior to the interview,
banks played an important role in facilitating bill payments. Among the banked, 62%
paid bills by check and 41% used a credit or debit card over the phone. Thirty-two
percent used automated bill payment, and 22% paid their bills online, most likely by
allowing the recipient to access their bank accounts electronically.
Despite their access to checks and automated payment systems, the banked are
likely to use AFS for their financial transactions. A surprisingly large fraction of the
banked population, 65%, purchased a money order as well. While 42% of all
respondents paid a bill in cash, 38% of the banked population also paid a bill in cash.
Fifty-two percent of all respondents paid a bill via money order, and 48% of banked
respondents used a money order to pay a bill.
Not surprisingly, the use of alternative financial services is a common response to
the lack of availability of mainstream banking services, either due to proximity, denial of
access, or lack of information. Over two-thirds of the DAHFS sample purchased a money
order in the last 12 months. In the last 3 years, 26% bought on layaway, 11% pawned
something for cash, and 22% received a refund anticipation loan (RAL) from a paid tax
preparer.
The unbanked are much more likely to use AFS than their banked counterparts.
In the 12 months prior to the interview, 77% of the unbanked purchased a money order.
During the three years prior to the interview, 21% of the unbanked pawned something for
cash and 29% received an RAL (v. 7% and 19% for the banked).
During the month prior to the interview, 54% of sample received a check of some
sort, 21% received cash, 5% received income from an electronic transfer to a place that is
not a bank (e.g. check cashing outlet). The electronic benefit transfer movement has
replaced most food stamps and welfare checks in Michigan; 22% of respondents have a
Bridge card, which provides cash benefits to low-income households. Yet only 1% have
a payroll card from their employer.
The DAHFS sample of low- and moderate-income households faces numerous
obstacles to financial and physical well-being. Out of the full set of respondents, 27%
feel that it is “very difficult” to live on their household’s income. In addition, 27% of the
sample has had a major illness or paid a significant medical expense in the last 12
months. In the last 12 months, 6% of the respondents were evicted, 10% had a utility
shut off, 18% had their phone disconnected, and 4% filed for bankruptcy, a rate far above
the national average.
The unbanked are characterized by a much greater likelihood of facing financial
hardships. Over one-third of the unbanked (38%) say that it is very difficult to live on the
household’s current income, compared to 23% of those with bank accounts. The
unbanked are nearly three times more likely to be evicted; 11% of the unbanked sample
was evicted in the last 12 months, in contrast to 4% of the banked sample.
The unbanked are twice as likely to have a phone connection or utility shut off as
the banked sample, 29% and 16% compared to 14% and 8%, respectively. The banked
and unbanked are comparably likely to have had a major illness or suffered a significant
medical expense in the last twelve months. However, the unbanked are much more likely
to classify themselves as in poor health; 11% of the unbanked consider themselves in
poor health, compared to 7% of banked respondents. This could be the result of different
subjective self-classification scales between the groups, or a different view of what a
“significant medical expense” entails. Either way, the unbanked consider themselves to
be significantly less healthy than the banked population.
Financial Services and Savings
In the Detroit Survey, 32% of respondents contributed to financial savings at least
every month. A larger portion of respondents never contributed to savings (42%), while
11% contributed once or twice a year. Respondents who contributed to savings have a
higher mean and median income than respondents who do not contribute. More than
3/4ths of respondents who save are above the poverty line, while a ¼ of respondents
remain below the poverty line.
“Savers” are in some ways different from those who do not save. Savers tend to
be more educated. There were also differences in the employment of savers and nonsavers. When looking at working status, a higher proportion of savers are currently
employed as compared to non-savers. Roughly 60% of savers are employed compared to
40% of non-savers. There were no evident differences between African Americans,
Whites and other races when looking at savers and non-savers. Bank account ownership
is an important factor which may distinguish savers from non-savers. Savers are more
likely to have a bank account compared to non-savers. About 80% of savers have bank
accounts while 50-60% of non-savers do not have an account. Poor credit history,
surprisingly, is not related to savings outcomes.
Income plays a significant role in the amount contributed to savings. Of those
who contributed to savings in the past 12 months of the interview, the average amount of
savings was $2,628 and the median amount was $1,000. When exclusively looking at
savers who are below the poverty level, the average amount contributed falls
dramatically. For those below the poverty level, the average amount was $1,317 and
median amount was $300. Savers above the poverty level contributed an average amount
of $2,852 and a median amount of $1000.
Households may save for investment, precautionary reasons, future consumption
and debt repayment. In the Detroit Survey, the majority of households are saving for
precautionary reasons. About 78% save to feel financially secure, 70% save for
emergency and medical expenses, and 51% save for unanticipated job loss. Many
respondents also save for future consumption in order to make purchases this year or the
next. This includes special events (53%), house or home improvements (49%),
retirement (48%), or furniture and household appliance (33%). In the Detroit Study,
47% of respondents are saving to pay off existing debt. A portion of respondents also
save for investment purposes. About 40% are saving to invest in education or training
while roughly 60% are saving to invest in business.
Saving is challenging for many low and moderate income households. LMI
households are more subject to income volatility, debt service burden, and have informal
financial obligations, such as helping a family or friend in need. One of the main reasons
that families find asset development a challenge is that they are simply poor and saving is
difficult with little income. As shown from the Detroit Survey, roughly 86% of
respondents find it hard to save because most of their money goes towards basic
necessities. About 27% of respondents find it very difficult to live on current household
income while 44% of respondents find it somewhat difficult. Many respondents have
experienced some sort of financial hardship (65.5%), such as having utilities or phone
shut off, food insufficiency, or eviction, and about 18% of respondents view themselves
as being in deep financial trouble.
Poor health and major illness can also negatively affect a household’s ability to
save. During the time of the interview, 28% had a health condition inhibiting work. In the
12 months prior to the interview, 23% have experienced job loss while 27% faced a
major illness or medical expense. About 20% of respondents don’t have insurance, and
therefore, may be extremely vulnerable to major medical expenses if an illness occurred.
A significant portion of households (37%) anticipate some big expense over the
next 5-10 years for which they are unable to save. More than a quarter of the sample has
monthly expenses which exceed income during most of the year. For these households,
family and friends play a significant role in contributing to basic living expenses. If they
can not rely on family or friends, 23% of respondents will spend down assets while 13%
will borrow from the bank or use their credit card. Of those with a credit card, 86% owe
money. While 45% are always able to cover expenses, about 40% of households are in
debt.
The high cost of credit and borrowing presents another obstacle towards savings
for low and moderate income households. For example, in the Detroit Survey, 24% of
respondents take out refund anticipation loans. By receiving their income a couple of
weeks early, they are subject to high interest. For those who have credit cards, the median
APR is relatively high at 12.9%. Housing payments are also significant for LMI
households with a median mortgage APR of 7.4%.
Though difficult, asset accumulation is important for many low and moderate
income households. About 90% of the LMI households accumulate physical and financial
assets in both formal and informal ways. Of the 75% of respondents who have financial
assets, 48% have savings accounts, 36% have retirement savings, and 29% have life
insurance. A smaller portion of respondents hold other financial assets, such as money
market funds, bonds, CDs, as well as more tangible assets, such as cash, jewelry, gold,
appliances, and electronics. For LMI households, these assets consist of 17% and 15%
respectively. Similar to saving contributions, income is strongly connected to net worth.
The mean and median net worth of respondents is significantly higher for those above the
poverty level as compared to those below. The median amount of those above is about
$38,000 while those below hold about a $1000.
When examining asset holdings, non-financial assets appear to be more valuable
than financial assets for LMI households. Owning a car and home significantly increases
the median value of assets for respondents. Roughly 75% of respondents own a car while
45% own a home. For those who have either of these assets, the mean amount is roughly
$95,000 for households above the poverty line and $45,000 for those below the poverty
line. However, non-financial assets fall drastically when excluding both home and auto
owners; the mean amount drops to $3,619 for those above the poverty line, and $1,058
for those below.
LMI households often need liquid assets in case of emergencies. Immediately
liquid assets are held by a higher proportion of households as compared to assets with
other liquidity levels. For households above the poverty line, the median amount of asset
holdings is $1000, which may be helpful towards an unexpected emergency. However,
with only a median asset holding of $400, households below the poverty line may not be
able to cover an emergency with immediately liquid assets. Lower proportions of poor
households hold assets that are not immediately liquid. While the average amount of
asset holdings increases from $1,636 to $4,277, the proportion of those who holds these
assets drops from 44% to 13.7%. However, for those who hold assets which have higher
rates of return, the mean and median amount drastically increases. With highly valued
assets, respondents who hold stocks, bonds, or mutual funds are more likely to be in a
better financial position.
With respect to attitudes towards saving, about 67% of respondents strongly
agreed that it is hard to save because most of their money goes towards basic necessities,
such as food, rent, or housing. When asked if it is hard to resist the temptation to spend
money, 41% strongly agreed and only 8% strongly agreed that savings just isn’t worth it.
For those who have a bank account, 48% believe that it helps them to save. For those
who are “un-banked”, 37% strongly agree that it will help them to save while 30%
somewhat agree.
Alternative Credit Markets Among the Banked and Unbanked
The responses from the DAHFS indicate that households use a variety of
alternative financial service providers to meet their various needs, based in part on
whether or not they have a bank account, and on their available collateral. Rather than
viewing each alternative service as a substitute, low-income borrowers use payday loans,
pawnshops, refund anticipation loans, and other services as complementary products.
Many low- and moderate-income households use payday loans, tax refund
anticipation loans, pawnshops, rent-to-own products and other formal and informal credit
products. Why do households take on high-cost debt? What credit constraints do they
face? Are these credit products complements or substitutes for each other and for credit
cards? What are the consequences of taking on such debt, in terms of rates of bankruptcy
filing, financial hardship and other measures?
A few recent studies have examined repayment and rollover rates for payday
loans, and separate research has looked at rates of refund anticipation lending. Yet
household survey data has been lacking that permits an extensive comparison of the
financial services behaviors, attitudes, and economic outcomes of low-, moderate-, and
middle-income households, who may use the array of credit products from credit cards to
payday loans and beyond. In this section, I use the Detroit study to explore the function
of these alternative credit products and their relationship to credit card borrowing. The
paper investigates the extent to which these credit products are complements or
substitutes for each other and for credit card borrowing. The paper examines the costs
and benefits of this array of credit products and analyzes the links between borrowing and
financial distress, including bankruptcy. The paper also explores how consumer attitudes
and preferences, risk tolerance and time preference, and levels of financial education
relate to usage of different credit products.
Low- and moderate-income households pay high prices to obtain credit outside of
the mainstream banking sector (Barr 2004, 2005). Alternative financial service (AFS)
providers have designed products that provide high-cost, short-term credit to low-income
households. Among these, payday lending services has driven growth in the AFS sector
over the last fifteen years. Yet payday loan services are still a lending practice on the
financial fringe. As Table 2 provides, only 4.4 percent of DAHFS respondents say they
"looked into getting a loan of $100 or more from a check casher, payday loan store, or
other place that gives you a payday loan" in the last 3 years. And only 3.4% reported
actually taking a loan or cash advance from a payday lender or check casher in the
previous 12 months. Part of the reason that so few respondents approached payday
lenders may be because of the restrictive qualifications to be eligible for a loan. As a
general requirement, a source of steady income is necessary to qualify for a payday loan.
Table 3a shows that while 6% of the currently employed and 5% of those employed in
the last year (but not currently employed) looked into a payday loan, an additional 2% of
those neither currently nor recently employed also considered payday borrowing. It is
possible that these individuals had employment in the two years previous, had spouses
with regular sources of income, or were borrowing based on a regular income source
other than from employment, including borrowing against a pension, social security,
government benefit, or disability check. Overall, however, payday loan users were more
likely to have earned income in the past month and have a job in the last month than other
LMI respondents.
Given the low use of payday loans among LMI households, it is unlikely that
borrowing among LMI households was the driving engine of the growth in the payday
lending industry. If 4.5% of an estimated 30 million LMI households were borrowing
$40 billion annually, this would amount to nearly $30,000 of debt per payday borrower,
which is an order of magnitude larger than available estimates of what payday users
borrow (Skiba and Tobacman 2006a). In addition, 100 million individual transactions
spread out over 4.5% of 30 million LMI borrowers suggests that each payday household
takes out, on average, 74 loans, which is an implausibly large number. It may be that
other types of households are largely responsible for the growth in the payday lending
industry, that sample members under-reported payday loan usage, or that aggregate data
on the industry are incorrect.
The demographics of payday borrowers are by and large similar to those of the
overall sample in the DAHFS, but LMI payday borrowers are more likely to be employed
than their non-borrowing LMI counterparts (Table 3). While 72% of the sample is
working age (25-60), 81% of payday borrowers are in that age category. The median
household size is the same for both the full sample and payday borrowers, with two
family members. In addition, men and women are equally likely to have looked into
getting a loan from a payday lender. (Data not shown).
However, African-Americans are much more likely to use payday lenders.
Eighty-nine percent of those who used a payday loan are black, compared to 69% of the
sample. Only 10% of payday borrowers are white, compared to 20% of the overall
sample. This difference in part reflects differences in average incomes (data not shown),
as well as proximity to payday lenders.
LMI households who borrow from payday lenders also differ in the average level
of education attained: they are more educated than non-payday-borrowers who are LMI
households. Fully 73% of payday loans were made to those with more than a HS
diploma (who comprise 47% of the respondents). Payday borrowers constitute 7% of all
“more than high school” respondents. The connection between education and payday
loan use derives in part from the requirements needed to obtain a payday loan,
particularly having a steady income. Those with a high school diploma are more likely to
be employed in the sample (64% vs. 52%), but, as their payday usage patterns suggest,
are not solely users of mainstream financial services.
An open question in the literature on alternative financial services (AFS) is
whether these services act as substitutes for one another, and for formal sector financial
services, or whether borrowers use a range of services depending on the situation. The
DAHFS suggests that the services are inter-related in most cases. Table 4a shows that,
overall, individuals seeking and using other types of credit are also more likely to use
payday loans. For instance, those using a pawnshop are much more likely to use a
payday loan (16% vs. 3%). Those who used a credit card for a cash advance are much
more likely to use a payday loan (14% vs. 4%). Households who took out a Refund
Anticipation Loan (RAL) at tax time (see Barr & Dokko 2007) are much more likely to
use a payday loan (9% vs. 3%), as are rent-to-own users (16% vs. 4%), and those who
cashed out a pension or insurance policy in the last three years (12% vs. 4%).
Respondents who used an overdraft from their bank account are over five times more
likely to use a payday lender (12.5% vs. 2.4%). Table 4a suggests that a comparison of
payday users and non-users will also reflect differences in both these two groups’ needs
and preferences for borrowing.
Among those using other AFS/not using other AFS, what % use payday?
AFS
What % of users
use payday?
What % of
non-users use
payday?
Pawnshop*
16%
3%
Cash Advance*
14%
4%
9%
3%
Rent-to-Own*
16%
4%
Cash out Pension*
12%
4%
Overdraft*
13%
2%
RAL*
Among those using payday/not using payday, what % use other AFS.
AFS
Payday users
Non users
Pawnshop*
40%
10%
Cash Advance*
24%
7%
RAL*
45%
21%
Rent-to-Own*
20%
5%
Cash out Pension*
19%
6%
Secured Card*
37%
9%
CC Late Fee
43%
21%
Overdraft*
57%
19%
*Significant difference at 10% level after controlling for age, race, gender and income.
The use of these alternative financial services is interconnected among each other
as well as with respect to payday borrowing. Table 1 shows a correlation matrix of
alternative financial services. The highest correlation is between pawnshop use and
payday borrowing. Payday borrowing is also correlated with using an overdraft from a
bank account. Nearly every entry in the table is positive, suggesting that individuals who
use one are more likely to use another. Although usage appears complementary, most of
the correlations are not large, implying relatively weak direct relationships within the
network of financial services outside of the mainstream banking sector. Surprisingly, the
banked are only slightly more likely to have looked into a payday loan than the unbanked
(4.9% vs. 3.4%). 12
In addition, the data show no significant difference in payday loan use for those
with and without a credit card. However, certain credit card behaviors are related to
payday borrowing. Those who have paid late fees on a credit card are more likely to
have used a payday loan than those who have a credit card and have not missed payments
(9.2% vs. 3.4%). Nearly 8% of those who say they never pay off the entire balance on
their credit card have looked into using a payday loan, compared to less than 4% of those
who pay off their entire credit card balance each month. Payday loans were used by
12.5% of those who pay only the minimum amount due. In addition, the least creditworthy cardholders, those whose cards require a deposit—known as “secured” credit
cards—are much more likely to use payday lending: 17.4% compared with 3.3% of the
rest of credit card users. These relationships to credit suggest that payday borrowers have
a history of credit problems, which make it difficult for payday borrowers to acquire
short-term credit elsewhere. Also, the higher rate of credit problems among payday
borrowers also suggests that this group exhibits riskier borrowing behavior.
12
It is surprising that those without bank accounts would even look into payday loans, given that most
lenders require having a checking account. It may be the case that individuals are unaware of the
underwriting standards in payday lending. In addition, we measure loan usage over the 3 years prior to the
survey interview, while bank account status is measured at the time of the interview.
Riskier credit card behavior also translates into difficulty acquiring loans from
mainstream providers. Slightly more payday users have been denied credit or offered
smaller loans in the previous year, as compared to non-payday users (39% vs. 35%).
Over 10% of those who were rejected by mainstream loan providers (banks, savings &
loan, credit union, finance and mortgage companies) sought payday loans. In short,
payday users tend to seek more borrowing opportunities than non-users, exhibit riskier
credit behavior, and face higher rates of rejection from mainstream lenders.
Furthermore, financial difficulties are common among payday loan users (Table
5). More than 90% of payday borrowers report that they are in “some” or “deep”
financial trouble. Over 12% have been evicted in the last 12 months, nearly 40% have
had their phone cut off, and over a quarter have had their utilities shut off. Nearly 30%
have suffered a major medical illness or expense in the past 12 months. In addition, more
than 11% have filed for bankruptcy in the last year, and more than 41% have ever filed
for bankruptcy. In comparison, in our sample as a whole, the filing rate last year as 4%,
and 14% had ever filed for bankruptcy.
Moreover, hardships appear well correlated with choosing to use payday loans
(Table 5a). More than 9% of those who say they are in “deep financial trouble” have
looked into a payday loan, compared to only 1.5% of those who say they are “financially
secure.” Those who have filed for bankruptcy in the last year are much more likely to
have used payday lenders (13% vs. 4%), as are those who have ever filed for bankruptcy
(10% vs. 3%). Those who said that they sometimes did not have enough food to eat are
more likely to use payday lenders (7% vs. 4%). Those respondents who were evicted (9%
sought payday loans) had their utility shut off (11.5%), or phone shut off (9.3%) were all
much more likely to use payday lenders than those without these hardships. Those who
suffered a major illness or expense in the last year are only slightly more likely to have
used a payday lender (5.0% vs. 4.3%). The evidence overall suggests a strong and
consistent relationship between facing financial difficulties and using payday loans.
This evidence on the hardships of payday borrowers suggests that they may have
a greater need for borrowing than non-users. Their financial difficulties, however, make
them a riskier group from the perspective of mainstream and alternative lenders, and may
in part explain that they are turned down at a higher rate as well as the higher costs of
borrowing they face. Furthermore, without knowing the underlying cause of their
financial difficulties, it is difficult to assess whether their hardships are the cause of
payday borrowing or whether they are a manifestation of some other behavior or attitude.
More specifically, payday borrowers, who are more likely to borrow from other sources,
may do so for myriad reasons, including greater hardships, poorer financial planning
ability, uncontrollable spending habits, or less access to more mainstream and less costly
sources of credit.
Our evidence on the reasons for taking out a payday loan suggests that individuals
use them to pay for necessities. As Table 6b shows, of those who most recently looked
into getting a payday loan, 60% said they needed the money for everyday expenses such
as food, gasoline or regular bills. No other response came close, though 11% said they
borrowed against their paycheck to pay off credit card or bank debts and 8% said they
needed the funds for car expenses; 8% needed the funds for education expenses; and 6%
needed the funds for medical or dental expenses. While this evidence is consistent with
the view that payday borrowers take out loans when their income cannot meet their
expenses, it is not sufficient to preclude that payday borrowers’ spending on nonnecessities crowds out spending on necessities, which then leads to high-cost borrowing.
In future work, building in data on consumption patterns, we hope to be able to better
understand the decision to take out a payday loan.
Payday borrowers generally do not have many assets or savings to provide as
collateral for other types of loans, or to spend down in the event of a financial difficulty.
The median amount in their checking and savings accounts is only $200. Only 13% of
payday borrowers own their homes, compared to 47% of non-borrowers. Overall,
median net asset holdings of payday borrowers are $48,500, including the value of the
home (compared to over $63,000 for non-users). There are no notable differences in
payday lending take-up based on savings frequency. Those who save every month are
actually very slightly (though not significantly) more likely to be payday lenders than
those who aren’t. In summary, payday borrowers have few assets and saving, seek loans
at a higher rate, and face higher rates of loan denials than other respondents.
Payday borrowers expect to meet the requirements of a payday lender. Of
respondents who looked into getting a loan from a payday lender most recently, 90.4%
requested or applied for a loan. Among the currently employed, the application rate
among those who looked into the loan was 87.5%. Although acceptance rates are high,
not all of those who apply for a payday loan are approved. Some 72.1% of payday
borrowers received the loan that the respondent wanted, 7.3% received a smaller loan
than requested, and 17.2% were turned down for the loan. The median size of the most
recent payday loan was $300, and the mean was $342.
Respondents who use payday lenders often use them multiple times. The most
common number of loans or cash advances (for those with at least one) in the past year
was two (31%), with three and four times being the next most common (19.9%, 14.2%).
Our estimates regarding repeat loans are far smaller than other studies. The median
number of loans in our sample was three in the past year, in stark contrast to studies such
as Elliehausen and Lawrence (2001), which report a median between five and six loans
(pg. 39, table 5-11). It is possible our measure did not fully capture rollovers when we
asked “how many times have you taken a loan….” Separately, we asked specifically
about rollovers: Of those who used a payday lender, 40.2% paid a fee to postpone paying
back the loan, but we do not know how many times. An additional 14.3% took a loan
from one payday lender to pay back a loan to a different payday lender. Overall, the
rollover experiences of the payday borrowers in the DAHFS sample suggest that the costs
of repeated borrowing may be high. Nonetheless, we did not find evidence that rollovers
are as extensive as reported elsewhere, and, from the view of borrowers, payday lenders
appear to fulfill a unique niche in the credit market. The most important reasons given
for going to payday lenders among other credit options were the convenience and
accessible hours of the payday outlet (23.6%), the expectation of being approved for the
loan (22%), and the need a small amount or to pay a bill (19.2%).
Respondents who have different reasons for borrowing money also have different
tendencies to use payday lenders. Not surprisingly, those who are less averse to debt are
more likely to take out payday loans, which is consistent with our view that payday users
tend to seek loans at a higher rate than non-users. For instance, among those who agree
that it is “alright for someone…to borrow to cover rent and food when income is cut,”
5.2% have looked into a payday loan, whereas only 2.2% of those who disagree have
inquired about payday borrowing.
Those who think it is acceptable to borrow for a car or to pay for educational
expenses are three times more likely to use payday lenders (6.5% vs. 1.9%, 5.4% vs.
1.6%). Survey respondents who would borrow to cover the costs of an illness are also
more likely to use payday lenders, 4.9% vs. 2.1%. Those who are willing to borrow to
finance the purchase of goods they cannot currently afford are also much more likely to
use payday loans (13.6% vs. 4.0%). In general, those who feel that it is acceptable to
borrow for any reason are also more likely to borrow using payday loans. Respondents
who would not feel ashamed or embarrassed if they had to file for bankruptcy are three
times more likely to have used payday lenders (7.6% vs. 2.4%), although it is hard to
interpret the causality here, given that those who do not identify a bankruptcy stigma are
also much more likely to previously have filed for bankruptcy.
The DAHFS also asks questions about individuals’ reasons for saving. Those
who said that they save is to pay down loans or get out of debt were more than twice as
likely to have looked into a payday lender (8.4% vs. 3.2%). Those saving for furniture or
appliances were also much more likely to use payday lenders (10.8% vs. 3.0%).
When asked whether it was hard to save because of the expenses of necessities,
those who said they did find it hard to save used payday lenders much more often than
those who did not find it difficult to save (strongly agree: 5.4%, strongly disagree: 0.0%).
There was no difference in payday lending usage based on the opinions that saving isn’t
worth it or that it is hard to resist the temptation to spend money. The respondents’ low
actual savings levels suggest that the inability to save is one of the driving forces in the
demand for payday loans.
Despite the high costs, customers choose payday lenders over other possible
sources of credit because they recently have been turned down by other, lower-priced
alternatives, and are confident that they will be approved for a payday loan. Serving as a
“lender of last resort” fills a critical need, but allows payday lenders to charge high fees
to a segment of the population that is in some ways disconnected from the financial
mainstream, is credit-constrained, and finds it difficult to save regularly. After obtaining
a payday loan, many borrowers fall into a debt trap, often paying fees to postpone or
“rollover” payments, or borrowing from one payday lender to pay back another.
The results of the DAHFS suggest the need for policies to reduce the need for
payday loans by helping low-income households create savings cushions to reduce the
impact of monthly variation in income. Direct deposit programs and automatic savings
plans are two straightforward measures which would reduce the demand for payday loans
and alleviate part of the strain of living “paycheck to paycheck.” In addition, the demand
for short-term loans among the low- and moderate-income population is largely not being
met by banks and other loan providers. Policy makers should encourage the financial
sector to provide better-structured alternatives to payday loans (Bair 2005), including
direct debit, longer-term, self-amortizing consumer loans with a savings feature (see Barr
2004, 2007).
Directions for Policy
The primary goal of public policy changes to strengthen financial security for
American families needs to begin with a safe and affordable bank account. Such an
account would be federally insured, and carry low, and straightforward, fees. Rather than
promoting traditional checking accounts, which often are high-cost and high-risk for
these households, the initiative will encourage debit-card based bank accounts with no
overdraft and no hidden or back-end fees. The accounts would not require a minimum
balance or account opening balance, and would not require complicated reviews to open.
Funds could be accessed at ATMs and point-of-sale. Over time, the accounts could
provide bill payment, an automatic savings plan or reasonable consumer credit options.
For example, banks could offer a six-month, self-amortizing consumer loan up to $500
with direct debit from the account; such a loan would be relatively low-risk and paid
automatically, could be offered without the need for labor-intensive interaction with the
customer, and thus could be offered at reasonable interest rates.
A New Tax Credit for Safe and Affordable Accounts for Working Americans. To
overcome the financial services mismatch, Congress should enact a tax credit for
financial institutions to offer safe and affordable accounts. The tax credit would be payfor-performance, with financial institutions able to claim tax credits for a fixed amount
per account opened. The tax credit program would be administered by the Financial
Management Service in cooperation with the IRS. This would be coupled with outreach
to employers to encourage direct deposit and automatic savings plans.
A New Opt-Out, Direct Deposit Tax Refund Account. Congress should enact a new
direct deposit tax refund account to encourage savings and expanded access to banking
services, while reducing reliance on costly refund loans. Unbanked low-income
households who file their tax returns would be able to have their tax refunds directlydeposited into a new account. Under this initiative, banks agreeing to offer safe and
affordable bank accounts would register to offer the accounts and a fiscal agent for the
IRS would draw from a roster of banks offering these services in the taxpayer’s
geographic area in assigning the new accounts. On receiving the account number, the
IRS would directly deposit EITC (and other tax refunds) into those accounts. Taxpayers
could choose to opt-out of the system if they did not want to directly deposit their refund.
State Strategies to Move Families into the Financial Mainstream.
States can
integrate access to financial services as a core element of welfare-to-work strategies.
Many states use card-based products for state benefits, but many of these do not permit
direct deposit of other sources of income, and are not owned by the customer and thus
cannot be retained when benefits end. The household does not develop any transactional
or credit history. Instead, states should increasingly use individually-owned, safe and
affordable bank accounts to receive direct deposit of TANF and related state benefit
payments as an essential component of their EBT programs. Many states are considering
linked deposit programs, using their fiscal relationships and leverage with banks, to
encourage more responsible banking products.
Conclusion
High cost financial services, barriers to saving, the lack of insurance and credit
constraints may contribute to poverty and other socio-economic problems. Low-income
individuals often lack access to financial services from banks and thrifts and turn to
expensive alternative financial service providers such as check cashers, payday lenders
and money transmitters. Many low-income households live paycheck to paycheck, and
are vulnerable to emergencies that may endanger their financial stability. Often lacking
access to insurance, reasonably priced credit, or regular savings plans, low-income
households suffering such emergencies suffer worse outcomes. Moreover, the lack of
longer-term savings options tailored to low-income households may undermine their
ability to invest in human capital or to build assets over time. More generally, heavy
reliance on alternative financial services reduces the value of take-home pay as well as
government assistance programs, such as the Earned Income Tax Credit.
By showing the extent to which LMI households are badly served by the financial
marketplace, results from the DAHFS motivate a necessary debate about the effect of
high-fee transactions on the well-being of low-income households. In our study, LMI
households face severe supply constraints. Our study quantifies whether high-fee
transactions hinder the effectiveness of redistribution policies, such as the EITC, as well
as other mechanisms affecting the economic mobility of low-income households. It also
provides new evidence on the role of transaction costs and limited financial service
options in altering the incentives and capacity for LMI households to save for
emergencies or long-term goals. Finally, results from the study inform the current policy
debate about the appropriate regulatory response to the AFS sector. Our results suggest,
on the one hand, that regulating AFS independently of one another and of the banking
sector is likely to have perverse consequences and, on the other hand, that market
mechanisms alone will likely be ineffective in improving the welfare of unbanked and
underbanked LMI households. The policy response needed on both efficiency and equity
grounds is change the financial services marketplace, to align the AFS and banking
sectors' incentives with those of LMI households.
References [Incomplete]
Barr, Michael S., “Banking the Poor,” Yale Journal on Regulation, 121, 2004.
Barr, Michael S., “Detroit Area Study on Financial Services (Overview),” 2005.
http://www-personal.umich.edu/~msbarr/
Berry, Christopher, “To Bank or Not to Bank? A Survey of Low-Income Households,”
Harvard Joint Center for Housing Studies Working Paper Series BABC 04-3, 2004.
http://www.jchs.harvard.edu/publications/finance/babc/babc_04-3.pdf
Bertrand, Marianne, Sendhil Mullainathan, and Eldar Shafir, “A Behavioral-Economics
View of Poverty,” American Economic Review, 94(2), May 2004.
Caskey, John, Fringe Banking: Check-Cashing Outlets, Pawnshops, and the Poor,
Russell Sage Foundation Press, 1994.
Dunham, Constance R., “The Role of Banks and Nonbanks in Serving Low- and ModerateIncome Communities,” in J. L. Blanton, S. L. Rhine, and A. Williams, eds., Changing
Financial Markets and Community Development: A Federal Reserve System Research
Conference (2001) Federal Reserve Bank of Richmond, pp. 31-58.
http://www.occ.treas.gov/SFAA/role_bks_nonbks.pdf
Dunham, Constance R., Fritz J. Scheuren, and Douglas J. Willson, “Methodological
Issues in Surveying the Nonbanked Population in Urban Areas,” in Proceedings of the
Survey Research Methods Section, American Statistical Association (1998), pp. 611-16.
http://www.occ.treas.gov/SFAA/Method.pdf
Office of the Comptroller of the Currency (OCC), “Survey of Financial Activities and
Attitudes: Questionnaire in English and Spanish,” Washington, D.C., December 2000.
http://www.occ.treas.gov/SFAA/Quest.pdf
Seidman, Ellen, Moez Hababou, and Jennifer Kramer, “A Financial Services Survey of
Low- and Moderate-Income Households,” Center for Financial Services Innovation, July
2005.
http://www.cfsinnovation.com/document/threecitysurvey.pdf
Seidman, Hababou, and Kramer, “Getting to Know Underbanked Consumers: A
Financial Services Analysis,” Center for Financial Services Innovation, September 2005.
http://www.cfsinnovation.com/managed_documents/seg.pdf
Toussaint-Comeau, Maude, and Sherrie L.W. Rhine, “Access to Credit and Financial
Services Among Black Households,” Federal Reserve Bank of Chicago, Consumer Issues
Research Series, June 2000.
http://www.chicagofed.org/publications/publicpolicystudies/ccapolicystudy/pdf/cca2000-1.pdf
Toussaint-Comeau, Maude, and Sherrie L.W. Rhine, “Increasing Participation in
Mainstream Financial Markets by Black Households,” Federal Reserve Bank of Chicago,
Consumer Issues Research Series, December 2000.
http://www.chicagofed.org/publications/publicpolicystudies/ccapolicystudy/pdf/cca2000-4.pdf
Tables [To Be Added]