IDA and Asset-Building Strategies:
Lessons and Directions
Michael Sherraden
Youngdahl Professor of Social Development
Director, Center for Social Development
Washington University in St. Louis, USA
Conference on Access, Assets, and Poverty
University of Michigan and Brookings Institution
October 11-12, 2007
Center for Social Development
Washington University in St. Louis
Overview of IDA Research:
Results to Date, Lessons, Directions
On-going body of work on IDAs and inclusive asset building.
Asked by the organizers to cover several IDA research
methods: non-experimental, cost assessment, experimental.
Will attempt to do that, and put the work in context of
research directions.
This is an opportunity for a mid-course assessment. Your
comments, questions, and suggestions are very welcome.
Center for Social Development
Washington University in St. Louis
Motivation: Why Assets?
Key to Household Development
Basic income and consumption are essential, and in
any wealthy and decent society basic income and
consumption should be supported.
But development of households and families occurs
over the long term through asset accumulation and
investment -- in education, experience, careers, homes,
businesses, and financial instruments.
This applies to all families, rich and poor alike.
Center for Social Development
Washington University in St. Louis
Why Assets?
Millions in the US Have Little or None
About 20% of US households have zero or negative
net worth (Mischel et al., 2007).
Between 1983 and 2001, the average net worth of the
poorest 40% of US household declined by 44%,
falling to $2,900 in 2001 (Wolff, 2004).
Center for Social Development
Washington University in St. Louis
Why Assets?
Basis of Racial Inequality
(Oliver & Shapiro, 2006; Kochhar, 2004; Shapiro, 2004)
Ratio of white to non-white income is about
1.5:1
Ratio of white to non-white net worth is about
10.0:1
(Nonwhite here refers to the largest groups of color:
Blacks and Hispanics)
Asset inequality by race is much greater than income
inequality, and has different meaning. If assets are a
foundation for household development, then asset
inequality may be more fundamental in the long term.
Center for Social Development
Washington University in St. Louis
Increasing Questioning of Income as
Sole Definition of Poverty and Well-Being
Welfare States have used primarily an income definition
of well-being in social policy.
Amartya Sen (1993, 1999) and others are looking toward
a broader definition of capabilities.
Assets can be seen as part of this discussion: one aspect of
of long-term capabilities.
Center for Social Development
Washington University in St. Louis
Can Policy Aim for Asset Accumulation?
In US, over $300 billion annually in tax expenditures
for assets (homes, investments, retirement accounts)
Over 90 percent of this goes to households
with incomes over $50,000 per year
(Sherraden, 1991; Howard, 1997; Seidman, 2001;
Corporation for Enterprise Development, 2004)
Center for Social Development
Washington University in St. Louis
The Poor Do Not Have the Same
Opportunities and Subsidies
for Asset Accumulation
The poor are less likely to own homes, have investments,
or have retirement accounts, where most asset-based
policies are targeted (Haveman and Wolff, 2005).
The poor have little or no tax incentives, or other
incentives, for asset accumulation (Seidman, 2001).
Center for Social Development
Washington University in St. Louis
One Policy Strategy for Asset Building:
Individual Development Accounts (IDAs)
(Sherraden, 1988, 1991)
• Special savings accounts
• Started as early as birth
• Savings are matched for the poor, up to a cap
• Multiple sources of matching deposits
• With financial education
• For homes, education, business capitalization
Center for Social Development
Washington University in St. Louis
IDAs in Demonstration Phase
IDAs proposed as a universal policy (everyone has an account
from birth), with greater subsidies for the poor in the form of
matches for deposits.
But implemented as short-term (3 to 5 year) demonstrations
targeting low-income households, in community-based
projects.
Center for Social Development
Washington University in St. Louis
Research on IDAs:
American Dream Demonstration (ADD)
•
•
•
•
•
•
•
First major demonstration of IDAs
Fourteen IDA programs around the country
ADD from 1997 through 2001, research through 2005
Organized by Corporation for Enterprise Development
Research plan by Center for Social Development
Experiment designed and led by Abt Associates
Funded by twelve foundations (Ford has been the major
supporter, with partnerships from CS Mott, Citigroup,
Fannie Mae, EM Kauffman, MetLife, FB Heron, Levi
Strauss, Rockefeller, and others)
Center for Social Development
Washington University in St. Louis
ADD Research Agenda:
Multiple Methods
Research methods in ADD have been multiple, each making
unique contributions. In this presentation, we look at four
research methods:
•
•
•
•
Account monitoring research
In-depth interviews
Cost assessment
Experiment
Center for Social Development
Washington University in St. Louis
Account Monitoring Research
Data set from MIS IDA, created by CSD for this purpose.
Record of all savings transactions for all participants.
Very accurate data on saving, coming from bank records.
Perhaps the most thorough existing data set on saving in
low-income households.
Analysis using two-step regression. First identifies factors
associated with being a “saver” (net savings of over $100),
then among “savers”, identifies factors associated with average
monthly net deposit (Schreiner & Sherraden, 2007).
Center for Social Development
Washington University in St. Louis
Account Monitoring:
Limitations and Usefulness
All participants in ADD are self-selected and program
selected.
This data set from all 14 ADD sites does not have a
counterfactual, and cannot address impacts.
This data set can address IDA savings patterns and
outcomes, as well as participant and program
characteristics associated with IDA savings, controlling
for many other variables.
Center for Social Development
Washington University in St. Louis
Account Monitoring Research:
Overall Savings Outcomes
(Schreiner & Sherraden, 2007)
Number of IDA participants in ADD = 2,364
Average monthly net deposit (AMND) = $16.60
About half of IDA participants (52%) were “savers”
“Savers” had AMND of $32.44
Match rates varied, with 2:1 most typical
Of every $1.00 that could be matched, $0.42 was saved.
Home purchase is the most popular use of IDAs (with
positive impact in experimental conditions).
Center for Social Development
Washington University in St. Louis
Uses of IDA Savings in ADD:
Matched Withdrawals
Of matched withdrawals taken by the end of ADD:
26% for microenterprise
22% for home repair
21% for home purchase
21% for post-secondary education
7% for retirement
2% for job training
Home purchase and repair continue to be popular (48%).
When offered (to 35% of participants) retirement saving
is also a popular option.
Center for Social Development
Washington University in St. Louis
Account Monitoring Research:
Individual Variables
Controlling for many other factors, income (both recurrent
and intermittent) is weakly associated with savings outcomes.
The poorest ADD participants saved a higher proportion of their
income in IDAs
Employment and welfare receipt (past or current) was not
associated with saving outcomes in IDAs.
These results suggest that something other than the observed
individual characteristics may be leading to savings outcomes
in IDAs.
Center for Social Development
Washington University in St. Louis
Account Monitoring Research:
Program Variables
We look briefly at:
Match rate
Match cap
Direct deposit
Financial education
Center for Social Development
Washington University in St. Louis
Match Rate
Matching seems to attract and hold participants in IDAs.
Controlling for many participant and program variables,
higher match rates are associated with the probability of being
a “saver”.
But among “savers”, higher match rates are associated with
lower AMND. It could be that a higher match substitutes for
an individual’s own saving to reach a saving goal.
Center for Social Development
Washington University in St. Louis
Match “Cap”
Controlling for many other factors, the amount that can
be matched (“match cap”) is strongly associated with net
monthly savings.
Each additional dollar of match cap is related to an
additional $0.57 in net monthly savings (a large effect).
Participants appear to turn the match cap into a savings
target.
Center for Social Development
Washington University in St. Louis
Automatic Deposit
Controlling for many other factors, automatic monthly
deposit is associated with participants being “savers”
But among “savers”, direct deposit has no statistical
relationship with AMND. This may be due to saving
being on “autopilot” with direct deposit.
Center for Social Development
Washington University in St. Louis
Financial Education
Among “savers” the first 10 hours of financial education is
positively associated with AMND, with no relationship after
10 hours. This is important, because financial education is
quite expensive to deliver, and perhaps the full benefit is in
the first 10 hours.
Each of the first 10 hours is associated with an increase of
$1.16 in AMND. Therefore 10 hours is associated with an
increase of $11.60 per month or $139 per year, which would
be $418 if matched 2:1, and $1,670 over four years.
Center for Social Development
Washington University in St. Louis
Summary Observations from
Account Monitoring Research
Overall, it may be that program characteristics are
as or more important than individual characteristics in
explaining savings outcomes in IDAs.
Regarding program characteristics, more than incentives
(in the form of matches) are related to savings outcomes.
The positive effect of incentives may be in attracting
and keeping people saving in the program, and not in saving
amount by those who participate (see also Engen, Gale, &
Scholz, 1996).
Center for Social Development
Washington University in St. Louis
Beyond Program Characteristics:
Institutional Constructs that May Affect
Saving and Asset Accumulation
•
•
•
•
•
•
•
•
Access (eligible, available, default enrollment)
Information (financial education, feedback)
Incentives (match rates, other inducements)
Facilitation (direct deposit, personal assistance)
Expectations (match cap, saving targets)
Restrictions (pre-commitment, restricted uses)
Security (money safe, dependable access)
Simplicity (simple products, limited choices)
Center for Social Development
Washington University in St. Louis
Toward Policy:
An Inclusive Savings Plan
Policy implications are for a saving plan with desirable
institutional features, similar to a 401(k) Plan, Federal Thrift
Savings Plan, or 529 College Savings Plan.
Desirable features might include: automatic enrollment, low
initial deposits, simple investment options, low annual fees,
financial education, matched savings for the poor, and target
savings amounts (Clancy et al., 2003, 2004, 2005).
As particular application, “Save More Tomorrow” illustrates
potential of a plan structure (Thaler & Benartzi, 2003).
Center for Social Development
Washington University in St. Louis
Insights from In-depth Interviews
(Margaret Sherraden et al., 2005; Margaret
Sherraden & Mcbride, forthcoming)
Subsample of ADD experiment, 60 IDAs and 30 controls
One key finding: IDA funds are not perfectly fungible.
Participants have mental understanding of short-term and
long-term accounts and value this distinction, e.g., glad that
IDA savings are “out of reach”.
Another key finding: IDA participants understand the matchcap as a target saving amount. The institutional construct
of “expectations” emerged from in-depth interviews.
Center for Social Development
Washington University in St. Louis
IDAs and Future Orientation
IDA participants say they can “see more clearly”
and better “visualize a future” than before IDAs.
IDA program is said to “create goals and purpose.”
IDA program is said to provide “way to reach goals.”
With these changes in outlook and capability, IDA
participants say they are “more able to save”, “look
forward to saving”, and “plan to save for the future”.
These findings from in-depth interviews may support
a cognitive approach to understanding the influence
of institutions on savings outcomes.
Center for Social Development
Washington University in St. Louis
How Much Do IDAs Cost?
(Schreiner 2002, 2006)
Thorough cost assessments published by CSD. Has caused
our policy colleagues some challenges, but necessary.
Program costs for administration (not counting matching funds)
are about $61 per month.
In part, high costs are due to demonstration (e.g., start-up
inefficiency, communications, policy involvement), but IDAs
are unlikely in this community-based model to get much below
$30 per month.
Compare to 401(k) administration of about $10 per month, and
intensive family intervention that may reach $400 per month.
Center for Social Development
Washington University in St. Louis
Demonstration Model:
Cost Is a Barrier to Scale
We do not yet know if IDAs are cost beneficial. ADD Wave 4
will include a cost-benefit analysis. All things considered, it
seems unlikely that monetizable benefits in ADD will exceed
costs.
Even if the cost-benefit outcome is positive (possible), high
administrative costs will be a barrier to large-scale policy
expansion.
The most scalable form of IDAs or other progressive savings
will be a large, centralized, efficient plan structure (discussed
above).
Center for Social Development
Washington University in St. Louis
The ADD Experiment:
What Are the Measured Impacts?
(Mills et al., 2004, 2006, forthcoming)
Experiment in Tulsa, OK, with 1103 participants randomly
assigned to treatment and control groups, three waves, 1998
to 2002.
ADD implemented by CFED, IDA program run by CAPTC,
with Abt Associates leading the experiment. CSD provided
Coordination. Abt was funded directly and did not report to
CSD. CSD asked to step back so that Abt can report the basic
experimental results, which we have been glad to do.
Key financial impacts are reviewed in this paper.
Center for Social Development
Washington University in St. Louis
Impact on Homeownership
Mills et al. (2004):
For treatment group, + 6.2 percentage points
Mills et al. (2006):
For black renters, +10% percentage points
Mills et al. (forthcoming):
For renters, +7 to 11% percentage points
Center for Social Development
Washington University in St. Louis
Interpreting Home Ownership Impact
It seems likely that research results in home ownership,
which is dichotomous, may have less measurement error than
financial variables, as these stable results may indicate.
A 6 to 11% positive impact in home ownership is large, and
could be a very positive outcome in ADD, especially if more
African Americans have become homeowners.
But perhaps IDAs only rushed people into homeownership who
would have done so otherwise. Or perhaps IDAs encouraged
home ownership among people who cannot sustain it over the
long term. All of this remains to be seen.
Center for Social Development
Washington University in St. Louis
Impact on Net Worth
Mills et al. (2004):
+$29 (NS)
Mills et al. (2006):
+$2,118 (NS)
Mills et al. (forthcoming):
+$1,339 (NS)
Center for Social Development
Washington University in St. Louis
Interpreting Net Worth Impact
The most apparent explanation is that there is no increase in net
worth due to IDAs during this period.
It could be that closing costs are not yet recovered in home equity
growth. In other words, home ownership may take longer to
show up as a change in net worth (Mills et al., all three versions).
It could be that extreme values in ADD data, leading to large
standard errors, make it impossible to identify a modest
underlying impact on net worth if it existed. One analysis by
Abt, addressing extreme values by trimming 3% of net worth
values and setting out-of-range controls to the mean, finds a
positive impact on net worth ($5,390, p<.01).
Center for Social Development
Washington University in St. Louis
Interpreting New Worth Impact (cont.)
Overall, Bill Gale’s assessment is that it is not possible to say
with this data set whether net worth increased on not due to
large variance in changes in net worth and relatively small
sample size (Mills et al., forthcoming).
The analysis by Abt cited above may suggest that variance is a
greater challenge than sample size, including variance in both
net worth and controls.
CSD will offer additional analyses that attempt to deal with
extreme values and possible measurement error (APPAM
in November). Regardless of these findings, we agree that
conclusions on net worth may be unwarranted at this time.
Center for Social Development
Washington University in St. Louis
Selected Impacts:
Other Assets & Liabilities
Mills et al. (2004), for all IDA group:
Real assets +$6,310 (p<.10) (+ p<.05 for black and 36+)
Total assets +$4,186 (NS) (+ p<.10 for black and 36+)
Total liabilities +4,157 (NS) (+p<.10 for black and 36+)
Mills et al. (2006):
For all IDA group, +computer purchase (p<.05)
For black renters, +$4,073 home equity (p<.05)
For black renters, -$1,348 financial assets (p<.10)
For black renters, -business ownership (p<.10)
For white renters, +$1,747 business equity (p<.05)
Mills et al. (forthcoming):
For all IDA group, financial assets -$1,925 (p<.05)
Center for Social Development
Washington University in St. Louis
Interpreting Asset & Liability Impacts
Overall, some indication that both assets and financial liabilities
increased.
It could be that increased asset ownership, even if offset by
liabilities, represents a positive (or negative) impact.
Having greater assets and greater liabilities could represent a
higher level of economic functioning with greater well being, as
may occur in owning a home with mortgage debt.
Or conversely, taking on greater liabilities to purchase assets
could lead to debt problems that limit future well being.
Center for Social Development
Washington University in St. Louis
Next Step: ADD Experiment, Wave 4
As indicated above, many questions remain unanswered. In
key respects, the time period for 3 waves of ADD was short,
and a follow-up Wave 4 may be informative.
ADD Experiment Wave 4 is now in planning and should be in
the field in 2008. Supported by the MacArthur and F.B. Heron
Foundations (so far).
The research team is led by University of North Carolina,
with Brookings Institution and CSD as partners, and survey
data collection by RTI International.
Center for Social Development
Washington University in St. Louis
Influence of IDA Research in US
IDAs included as a state option in 1996 “welfare reform” Act
(Boshara, 2003)
Federal Assets for Independence Act in 1998, first public
IDA demonstration (Boshara, 2003).
Over 40 US states now have some type of IDA policy
(Edwards & Mason, 2003; Warren & Edwards, 2005)
United Way of American in 2007 announced a $1.5 billion
Financial Stability Partnership focused on increasing income,
savings, IDAs, and protecting assets.
Center for Social Development
Washington University in St. Louis
Influence of ADD Research
Internationally
Saving Gateway and Child Trust Fund in the United
Kingdom (Kelly and Lissauer, 2000; Blair, 2001; Sherraden,
2002, H.M. Treasury, 2003; Paxton, 2003; Kempson et al.,
2003, 2006)
Family Development Accounts by Taipei City (Cheng, 2003)
IDAs and “Learn$ave” demonstration in Canada (Kingwell
et al., 2003)
Matched saving in Australia (ANZ Bank), Uganda (CSD’s
AssetsAfrica initiative), Colombia and Peru (International
Fund for Agricultural Development), Hungary (OSI).
Center for Social Development
Washington University in St. Louis
Example: Matched Savings with
HIV/AIDS Orphans in Uganda
(Ssewamala and Curley, 2005)
High risk population, including likely HIV infection later
Aiming for US$600 for secondary schooling
Savings of $200 matched with $400
Pilot successful
Now larger project with NIH funding:
• One of few NIH grants outside of US
• One of first NIH grants to test economic intervention on health
outcomes (preventing HIV infection as children grow older)
So far, evidence of positive impact (vs. comparison group) on HIV
prevention attitudes and educational planning (Ssewamala et al.,
2007).
Center for Social Development
Washington University in St. Louis
Children’s Development Accounts:
Potential in the United States
Average children’s allowance in Western Europe is 1.8% of
GDP. US has no children’s allowance and under-invests in
children. Even 0.1% of US GDP would be enough for a $2,500
start in life account for every newborn (Curley & Sherraden,
2000).
Many proposals now in the US Congress for CDAs (New
America Foundation, 2004, 2006).
Recently Sen. Clinton proposed an account for every US
Newborn, with initial $5,000 deposit.
Center for Social Development
Washington University in St. Louis
Next Step: Testing CDAs in the US:
The SEED Demonstration
Twelve SEED demonstration sites around the country, multiple
research methods.
Partners are CFED, New America Foundation, University of
Kansas, Research Triangle Institute, Aspen Institute, and CSD.
Research funding for SEED from Ford, CS Mott, MetLife,
Lumina, and Smith Richardson (pending) foundations.
CSD is organizing an experiment (random assignment at birth)
in one state (Oklahoma), using the 529 College Savings Plan:
1,490 participants and 1,490 controls, $1,000 deposits at birth
and matching savings, seven-year project to 2014.
Center for Social Development
Washington University in St. Louis
Last Comment: Payoffs of
Demonstration Research
Field demonstrations over an extended period can be
challenging to implement and carry out. They depend on
cooperation among many different partners. But payoffs of
demonstration research include:
•
•
•
•
•
Provides opportunity to test and improve an innovation
Builds practitioner and field capacity
Creates examples that can influence policy
Yields research that can inform knowledge and policy
Trains new scholars for future research and analysis
Center for Social Development
Washington University in St. Louis
References
Beverly, S.G., & Sherraden, M. (1999). Institutional determinants of saving:
Implications for low-income households and public policy, Journal of Socioeconomics 28, 457-473.
Blair, T. (2001). Savings and assets for all, speech. London: 10 Downing Street,
April 26.
Boshara, R. (2003). Federal policy and asset building. Social Development Issues
25(1&2), 130-141.
Bynner, J.B., & Paxton, W. (2001). The asset effect. London: Institute for Public
Policy Research.
Caner, A., & Wolff, E.N. (2004). Asset poverty in the United States. Levy Economics
Institute, Bard College.
Cheng, Li-Chen (2003). Developing Family Development Accounts in Taipei:
Policy innovation from income to assets. Social Development Issues 25(1/2),
106-117.
Clancy, M., Cramer, R., & Parrish, L. (2005). Section 529 savings plans,
access to post-secondary education, and universal asset building.
Washington: New American Foundation.
Center for Social Development
Washington University in St. Louis
References (cont.)
Clancy, M, Orszag, P., & Sherraden, M. (2004). College savings plans: A
platform for inclusive savings policy? St. Louis: Center for Social
Development, Washington University.
Clancy, M., & Sherraden, M. (2003). The potential for inclusion in 529
savings plans: Report of a survey of states. St. Louis: Center for Social
Development, Washington University in St. Louis.
Corporation for Enterprise Development (2004). Hidden in plain site: A look at
the $335 billion federal asset-building budget. Washington: Corporation for
Enterprise Development.
Curley, J., & Sherraden, M. (2000). Policy lessons from children’s allowances
for children’s savings accounts, Child Welfare, 79(6), 661-687.
Edwards, K., & Mason, L.M. (2003). State policy trends for Individual
Development Accounts in the United States, Social Development Issues 25
(1&2), 118-129.
Engen, E.M, Gale, W., & Scholz, J. (1996). The illusory effects of savings
incentives on saving, Journal of Economic Perspectives 10(4), 113-138.
Center for Social Development
Washington University in St. Louis
References (cont.)
Goldberg, F. (2005). The universal piggy bank: Designing and
implementing a system of savings accounts for children. In M. Sherraden,
ed., Inclusion in the American dream: Assets, poverty, and public policy.
New York: Oxford University Press.
H.M. Treasury (2003). Details of the Child Trust Fund. London: H.M.
Treasury.
Haveman, R., & Wolff, E.M. (2005). Who are the asset poor? Levels, trends,
and composition, 1983-1998. In M. Sherraden, ed., Inclusion in the American
dream: Assets, poverty, and public policy. New York: Oxford University Press.
Howard, C. (1997). The hidden welfare state: Tax expenditures and social policy in
the United States. Princeton: Princeton University Press
Kempson, E., McKay, S., & Collard, S. (2003). Evaluation of the CFIL and
Saving Gateway pilot projects. Bristol, United Kingdom: University of
Bristol.
Center for Social Development
Washington University in St. Louis
References (cont.)
Kempson E, Atkinson A, Collard S (2006). Saving for children: A
baseline survey at the inception of the Child Trust Fund, HM Revenue &
Customs Research Report 18. Personal Finance Research Centre, University
of Bristol.
Kingwell, P., Dowie, M., Holler, B., & Jimenez, L. (2004). Helping people help
themselves: An early look at Learn$ave. Ottawa, Canada: Social Research
and Demonstration Corporation.
Kelly, G., & Lissauer (2000). Ownership for all. London: Institute for Public
Policy Research.
Kochhar, R. (2004). The wealth of Hispanic households. Washington: Pew
Hispanic Center.
Lindsey, D. (1994). The welfare of children. New York: Oxford University
Press.
Loke, V., & Sherraden, M. (2006) Building assets from birth: Comparison of
policies and proposals on Children’s Savings Accounts, working paper. St.
Louis: Center for Social Development.
Center for Social Development
Washington University in St. Louis
References (cont.)
Midgley, J. (1999). Growth, redistribution, and welfare: Toward social
investment, Social Service Review 77(1), 3-21.
Mills, G., Patterson, R., Orr, L., & Demarco, D. (2004). Evaluation of the
American Dream Demonstration, final report. Cambridge, MA: Abt
Associates.
Mills, G., Gale, W.G., Patterson, R., & Apostolov, E. (2006). What do
individual development accounts do? Evidence from a controlled experiment,
working paper. Washington: Brookings Institution.
Mills, G., Gale, W.G., Patterson, R., Englehardt, G.V., Eriksen, M.D., &
Apostolov, E. (forthcoming). Effects of Individual Development Accounts
on asset purchases and saving behavior: Evidence from a controlled
experiment.
Mishel, L., Berstein, J., Allegretto, S. (2007). The state of working America.
Washington: Economic Policy Institute.
Center for Social Development
Washington University in St. Louis
References (cont.)
New America Foundation (2004). ASPIRE Act summary. Washington: New America
Foundation.
New America Foundation (2006). Savings accounts for kids: Current federal
proposals. Washington: New America Foundation.
Nissan, D., & LeGrand, J. (2000). A capital idea: Start-up grants for young
people, policy report no. 49. London: Fabian Society.
Oliver, M., & Shapiro, T. (2006). Black wealth/white wealth, second edition. New York:
Routledge.
Paxton, W., ed. (2003). Equal shares? Building a progressive and coherent
asset-based welfare policy. London: Institute for Public Policy Research.
Russell, R., & Fredline, L. (2004). Evaluation of the Saver Plus pilot project.
Australia: RMIT University.
Schreiner, M. (2006). Program costs for Individual Development Accounts:
Final figures from CAPTC in Tulsa, Savings and Development 30(3), 247274.
Center for Social Development
Washington University in St. Louis
References (cont.)
Schreiner, M., & Sherraden, M. (2007). Can the poor save? Savings and asset
building in Individual Development Accounts. New Brunswick, NJ:
Transaction.
Seidman, L. (2001). Assets and the tax code. In T. Shapiro & E.N. Wolff, eds.,
Assets for the poor: Benefits and mechanisms of spreading asset ownership,
324-356. New York: Russell Sage Foundation.
Sen, A. (1993). Capability and well-being. In M. Nussbaum & A. Sen, eds., The quality
of life, 30-53. Oxford: Clarendon Press.
Sen, A. (1999). Development as freedom. New York: Knopf.
Shapiro, T. (2004). The hidden costs of being African-American. New York: Oxford
University Press.
Sherraden, M.S., & McBride, A.M. (forthcoming). Particicipant views of IDAs
(working title). Ann Arbor: University of Michigan Press.
Sherraden, M.S., McBride, A.M, Hanson, S., & Johnson, L. (2005). The
meaning of saving in low-income households, Journal of Income
Distribution 13(3-4).
Sherraden, M. (1988). Rethinking social welfare: Toward assets. Social Policy
18(3), 37-43.
Center for Social Development
Washington University in St. Louis
References (cont.)
Sherraden, M. (1991). Assets and the poor. Armonk, NY: ME Sharpe.
Sherraden, M. (2002). Opportunity and assets: The role of the Child Trust
Fund, seminar organized by Prime Minister Tony Blair, 10 Downing, and
dinner speech with Chancellor of the Exchequer Gordon Brown, 11
Downing, London, September 19.
Sherraden, M., & Barr, M.S. (2005). Institutions and inclusion in saving
policy, in N. Retsinas & Eric Belsky, eds., Building assets, building credit:
Creating wealth in low-income communities. Washington: Brookings
Institution.
Sherraden, M., Schreiner, M., & Beverly, S. (2003). Income, institutions, and
saving performance in Individual Development Accounts, Economic
Development Quarterly 17(1), 95-112.
Sswamala, F., Alicea, S, Bannon, W.M, & Ismayilova, L. (2007). A novel
economi intervention to reduce HIV risks among school-going AIDS orphans
in rural Uganda, Journal of Adolescent Health.
Center for Social Development
Washington University in St. Louis
References (cont.)
Ssewamala, F.S., & Curley, J. (2005). Improving life chances of orphan
children in Uganda: Testing an asset-based development strategy, working
paper 05-01. St. Louis: Center for Social Development.
Thaler, R., & Benzartzi, S. (2004). Save More Tomorrow: Using behavioral
economics to increase employee saving, Journal of Political Economy 112,
S164-S187.
Warren, N., & Edwards, K. (2005). Status of State Supported IDA Programs
in 2005, working paper 05-03. St. Louis, Center for Social Development.
Williams Shanks, T.R. (2007). The impacts of household wealth on child
development, Journal of Poverty 11(2), 93-116.
Wolff, E.N. (2004). Changes in household wealth in the 1980s and 1990s in
the United States, working paper no. 407. Levy Economics Institute, Bard
College.
Zhan, M., & Sherraden, M. (2003). Assets, expectations, and children’s
educational achievement in single-parent households, Social Service Review
77(2), 191-211.
Center for Social Development
Washington University in St. Louis