The Journal of Extension -

December 2009 // Volume 47 // Number 6 // Research In Brief // 6RIB3

Survey of Former IDA Program Participants: How Do They Fare?

While a number of studies have examined the savings performance of participants in the Individual Development Account (IDA) program, research about long-term program outcomes is limited. To fill this void, we present findings of a survey of IDA participants' asset holdings after they left the IDA program. Results document that those who successfully complete the IDA program report higher levels of asset ownership after completing the program, compared to those dropping out of the program prematurely. This supports the view that IDA programs affect the dispositions and behaviors necessary to successfully maintain a home, complete post-secondary education, and establish a small business.

Cäzilia Loibl
Assistant Professor

Beth Red Bird
Graduate Student

Department of Consumer Sciences
The Ohio State University
Columbus, Ohio


While a number of studies have examined the savings performance of participants in the Individual Development Account (IDA) program, none of the research has decomposed the long-term outcomes. To fill this void, this article presents findings of a survey of IDA participants' asset situation after they left the IDA program. The research builds upon an expanding body of research that analyzes the effectiveness of the IDA programs (see Schreiner & Sherraden, 2007, for an overview). Key themes in this literature include assessing program structure and related federal regulation (Richards, 2003; Rom, 2005; Sherraden, 2000; Shobe, 2002), analyzing participants' characteristics (Mills, Gale, Patterson, & Apostolov, 2006; Reutebuch, 2001; Rohe, Gorham, & Quercia, 2005), and determining the program impact in various life situations (Grinstein-Weiss, Wagner, & Ssewamala, 2006; Grinstein-Weiss, Zhan, & Sherraden, 2006; Shobe & Boyd, 2003; Shobe & Page-Adams, 2001).

Less effort has been dedicated to understanding the long-term effectiveness of the IDA programs on family wellbeing beyond the time spent in the program. Work by Schreiner and Sherraden (2006) is an exception, though this work uses data on current program participants to estimate their future wellbeing. In fact, none of the aforementioned works deal with the long-term benefits of IDA programs or how programs could be improved to increase financial literacy and family wellbeing using insight from former program participants. Specifically, we aimed to answer three specific questions:

  1. Does IDA program participation help individuals maintain a home, complete post-secondary education, and establish a small business?
  2. What factors cause IDA program dropout?
  3. How do successful program participants differ from those who left the program prior to completion?

To address the research questions, a survey of all former IDA program participants of agencies affiliated with the "Assets Ohio" network of the Ohio Community Development Corporation (CDC) Association was conducted.

  • Eligible respondents were IDA program participants who saved in an Individual Development Account since the program's inception in 1999, including successful graduates and former participants who left the program prematurely.
  • A total of 465 former program participants were contacted by mail and invited to participate in a paper-and-pencil survey.
  • The questionnaire, mailed in April 2007, consisted of 26 questions (19 questions for program dropouts).
  • A total of 164 individuals (or 43% of successful contacts) completed the survey.

Demographic Characteristics

The demographic characteristics for both the full sample and divided by IDA program graduates (77% of respondents) and dropouts (23%) are presented in Table 1. The two groups, graduates and dropouts, differed in some significant areas. Graduates had a higher formal level of education, reported a higher annual post-program household income, and were more often fully employed. IDA graduates had significantly higher post-program financial assets than dropouts.

Table 1.
Demographic Characteristics of Respondents
Measure Range of Scale Graduates Drop-outs Test Statistic
  Mean (SD) Mean (SD)  
Women (enrollment) 1=yes/0=no 84% (36.7%) 84% (37.0%) .000 a), n.s.
White (enrollment) 1=yes/0=no 49% (50.2%) 39% (49.5%) 1.104, n.s.
Education (enrollment) 1=low/10=high 5.29 (1.448) 4.71 (1.228) 9.927, p=.026
Age (enrollment) continuous 3.40 (.922) 3.45 (.978) .061, n.s.
Married (enrollment) 1=yes/0=no 27% (44.0%) 21% (41.3%) .534, n.s.
Children under 18 living in (survey) continuous 1.48 (1.307) 1.63 (1.403) .399, n.s.
Annual household income (survey) 1=low/5=high $20,600 ($7,890) $9,850 ($3,385) 10.964, p=.001
Employment (survey) 1=unable/5=full 4.51 (.874) 4.11 (1.290) 4.882, p=.029
Amount of household financial assets (survey) 1=low/6=high 4.09 (1.846) 2.66 (1.790) 17.745, p=.000
Amount of credit card debt (survey) 1=low/6=high 3.60 (1.948) 3.53 (1.913) 2.867 b), n.s.
N   126 38  
Note: Test Statistic is an ANOVA, Omnibus F Test, except for a) Pearson χ2

Asset Holdings

Below we describe the assets purchases made by program graduates. We also present the most common reasons dropouts reported for leaving the IDA program.

Asset Ownership: Homeownership

A total of 110 survey respondents sought to purchase a home with their savings (67.1%). Of those 110, 83 graduated from the IDA program (75.5%), and 27 dropped out before graduation (24.5%). Of the graduates, all but one respondent still owned the home they purchased with the IDA funds. Table 2 summarizes the findings.

On average, respondents reported experiencing between one and two housing problems included in our list of 12 possible problem areas. As presented in Figure 1, the five most common housing problems were, in order, damp areas, walls, floors, or foundation; heat or cooling system malfunctions; insufficient space; electrical problems; and leaky roofs.

Table 2.
Measure % (N)
Still own the home (mean: .99 (SD: .110); yes=1/ no=0)  
yes 98.8% (82)
no 1.2% (1)
Type of mortgage
Regular fixed-rate mortgage 51.8% (43)
Habitat for Humanity mortgage 16.9% (14)
Government loans 14.5% (12)
Other 16.8% (14)
Monthly payment (.48 (.510); yes=1/no=0)  
None 1.25 (1)
Up to $500 38.6% (32)
$500 to $999 55.4% (46)
$1,000 or more 4.8% (4)
Hard to pay housing expenses in past year: 4.07 (1.068; 1= every month, 5= never)
No housing problems .36 (.483)
Total number of housing problems (continuous) 1.48 (1.572)
Not enough space .19 (.397)
Noise from neighbors or outside .12 (.328)
Too dark/not enough light .06 (.239)
Leaky roof .14 (.354)
Damage to your home's foundation .08 (.280)
Heat or cooling system problems .20 (.406)
Electrical problems .19 (.397)
Cockroach, rat, or other rodent problems .05 (.215)
Damp areas, walls, floors, or foundation .23 (.423)
Rot in window frames or floors .08 (.280)
Pollution, traffic, or industry .01 (.110)
Vandalism or crime in the area .11 (.313)

Figure 1.
Housing Problems
Housing Problems

Asset Ownership: Post-Secondary Education

A total of 24 respondents used their savings to fund higher education expenses (14.6%). Of those 24 respondents, 23 graduated from the IDA program (95.8%), and 1 dropped out before graduation (4.2%). Of the 23 IDA program graduates, 9 have graduated from school, 12 are still enrolled in their programs, and 2 left their educational program without a degree at the time of the survey. The two reasons given were related to the subject matter (poisoning during chemistry home study course) and an inability to combine work, family, and school (Table 3).

Table 3.
Measure % (N)
Still enrolled in the education program (.48 (.511); yes=1/no=0)
yes 47.8% (11)
no 52.2% (12)
Started educational program (1.83 (.778); 1=during program, 5=within 6 months)
During the IDA program 34.8% (8)
1 month after completing the IDA program 52.2% (12)
3 months after completing the IDA program 8.7% (2)
6 months after completing the IDA program 4.3% (1)
Pursuing Bachelors degree (.48 (.510); yes=1/no=0)  
Bachelors' degree 47.8% (11)
Graduate degree 17.4% (4)
Associate degree 10.3% (3)
Other 21.7% (5)
Credit hours have you earned: 29 (26; 1=none, 5=60 plus)  
Plan to graduate (2.74 (1.738); 1=graduated, 6=left program)
Already graduated 39.1% (9)
2007 8.7% (2)
2008 17.4% (4)
2009 17.4% (4)
2010 or later 8.7% (2)
Left program without graduation 8.7% (2)
Hard to pay school expenses in past year (N=17): 3.18 (1.015; 1= every month, 5= never)
Note: N=23

Asset Ownership: Microenterprise

A total of 22 respondents participated in the IDA program to save for a small business venture. Eighteen respondents still owned their small business (78%). Four of the 22 respondents could not sustain their small business (22%), listing personal (husband passed away), customer-related (no or late payments for services), and market-related (bad timing of venture) reasons as the most common causes of business failure. Other reasons were stronger than expected competition, more cash-out flow than in-flow, and higher cost than expected (Table 4).

Table 4.
Measure % (N)
Still own the small business (.78 (.428); yes=1/no=0)  
Yes 77.8% (14)
No 22.2% (4)
Other kind of money invested  
Did not receive any other money 83.3% (15)
Received a loan from a bank or credit union 16.7% (3)
Level of loan payment (N=4; 1.17 (.383), 1=nothing, 5= $8,000 or more)
Nothing 83.3% (15)
Up to $500 16.7% (3)
Hard to pay business expenses in past year (N=12; 4.00 (1.348) 1= every month, 5= never)
every month 5.6% (1)
every other month 5.6% (1)
three or four times 5.6% (1)
once or twice 16.7% (3)
not at all 33.3% (6)
Note: N=18

Asset Ownership: Control Group

The study's control group consisted of the 38 respondents who started an IDA program but left the program before completion. Of those 38 individuals, 25 (66%) have not purchased the asset they were saving for in the IDA program. Of the eight individuals who did purchase the asset, all of them have maintained ownership (Table 5).

As presented in Table 4, the main reasons for leaving the IDA program were unforeseen expenses, unpaid bills, or large upcoming expenses. Other reasons for leaving the IDA program were:

  • Resources-related ("needed a vehicle"; "child support"; "lost my job"; "health problems"; "not enough income to save")
  • Time-related ("could not wait so long")
  • Program-related ("time and location of class"; "program was terminated")
  • Location-related ("moved away")
  • Credit-related ("needed to fix my credit up")
Table 5.
Control Group Characteristics
Measure % (N)
Bought asset since leaving IDA program (.24 (.435); yes=1/no=0)
Yes 21.1% (8)
No 65.8% (25)
Information missing 13.2% (5)
If yes, still owning the asset (N=8; yes=1/no=0)
Yes 100% (8)
Reasons for leaving IDA program (range 1=completely disagree to 5=completely agree)
Costs I did not expect 3.03 (1.678)
Behind with bills 2.74 (1.797)
Large expenses coming up 2.62 (1.724)
No income or was unemployed 2.44 (1.761)
Credit problems that I could not fix 2.09 (1.640)
Forgot to deposit too often 1.94 (1.496)
Program was not what I expected 1.68 (1.249)
Decided not to purchase a home 1.42 (1.062)
Other reason; please specify 4.71 (1.069)

Predicting Financial Wellbeing

The predictors of financial wellbeing were assessed using a set of psychological, financial, and demographic variables (Loibl, Grinstein-Weiss, Zhan, & Red Bird, in press), including self-control (Tangeney, Baumeister, & Boone, 2004), self-efficacy (Pearlin & Schooler, 1978), time preference (Strathman, Gleicher, Boninger, & Edwards, 1994), financial coping (Hilton & Devall, 1997), decision authority (you yourself=1 and you with others or others without you=0), past and future financial situation (3=better, 2=same, 1=worse), and ownership of an investment account (yes=1, no=0). Demographic control variables included those presented in Table 1.

Regression analysis is the perfect tool to combine all these measures into one single analysis. We conducted OLS regression analysis to identify the measures that influence household financial assets (R-Square=0.530, F=5.949, p<0.000). The explanatory variables include the above-mentioned psychological, financial, and demographic measures. Controlling for these variables, the regression results showed that six variables were related to financial wellbeing. Participants with higher household financial assets were more likely successful IDA program graduates (p=0.006), were white (p=0.002), had children under 18 (p=0.082), were employed full-time (p=0.098), owned an investment account (p=0.000), and were more considerate of the future consequences of their actions (p=.006).

Key Findings

The key findings of the survey include the following.

  1. Compared to program dropouts, successful graduates reported in the survey a higher annual household income, more likely being full-time employed, and more likely owning an investment account. Importantly, IDA graduates had significantly higher post-program financial assets than dropouts.
  2. Of the respondents who graduated from the IDA program, all but one still owned the home purchased with the IDA funds.
  3. Of the respondents who saved for higher education, only two left their educational program without a degree.
  4. Three-quarter of respondents who saved to open a small business were able to sustain it.
  5. Program graduates reported only slightly higher tenancies towards the likelihood of future events, ability to control impulsive behavior, and capability to attain goals. They experienced marginally fewer difficulties to cope and less lifestyle deprivation.
  6. The majority of both program graduates and dropouts were the primary financial decision makers for their household.
  7. Inquiring about the past and future financial situation, program dropouts reported a significantly more positive outlook toward their financial future.
  8. Survey participants reporting higher levels of financial wellbeing and were more likely to own an investment account, be white, have graduated from the IDA program, have children under 18 living in their households, be more considerate of the future consequences of their actions, and be employed full-time.


These key findings lead to the following recommendations for program development strategies to further family wellbeing after people leave the IDA program.

  1. Provide extra support to minorities and people with job problems. Our findings show that non-white respondents and those with less than full-time employment are less likely to accumulate a financial cushion after they leave the IDA program.
  2. Teach participants the importance of opening an investment account. Owning an investment account was the most important predictor of post-program financial wellbeing. The IDA program providers may consider providing information about employer-sponsored retirement plans and investment accounts at low-cost investment houses during their financial education and counseling sessions.
  3. Emphasize the importance of future events. Respondents who believed certain economic behaviors are worthwhile because of future benefits, even if immediate outcomes are relatively undesirable or even if there are immediate costs, were able to accumulate higher household financial assets. IDA programs may develop strategies to train participants the skills to forfeit immediate benefits like convenience or pleasure to achieve more desirable future states.
  4. Teach skills that help in coping with situations of limited resources. Among successful program graduates, those who had difficulty coping with limited resources were less successful in accumulating financial assets. IDA programs may offer trainings to participants that develop participants' skills in coping with perceptions of inadequacy with their financial position and with financial concerns and worries.
  5. Encourage formal education. A significant predictor of program graduation was the level of formal education. IDA programs may consider providing information about financial aid and economic access programs to their program participants as a part of their regular financial education and counseling sessions.

Readers interested in an in-depth analysis of IDA program characteristics and their effectiveness for long-term saving may be referred to Loibl, Grinstein-Weiss, Zhan, and Red Bird (in press).


Only 35% of all former IDA program participants in the Ohio CDC Association participated in the survey reported here. Readers should be aware that the findings might not correctly represent the situation of the whole group of former IDA program participants.


The financial support of the Ohio CDC Association and Ohio State University Extension is gratefully acknowledged.


Grinstein-Weiss, M., Wagner, K., & Ssewamala, F. M. (2006). Saving and asset accumulation among low-income families with children in idas. Children and Youth Services Review, 28(2), 193-211.

Grinstein-Weiss, M., Zhan, M., & Sherraden, M. (2006). Saving performance in individual development accounts: Does marital status matter? Journal of Marriage and Family, 68(February), 192-204.

Hilton, J. M., & Devall, E. L. (1997). The family economic strain scale: Development and evaluation of the instrument with single- and two-parent families. Journal of Family and Economic Issues, 18(Fall), 247-271.

Loibl, C., Grinstein-Weiss, M., Zhan, M., & Red Bird, B. (in press). More than a penny saved: Long-term changes in behavior among savings program participants. Journal of Consumer Affairs.

Mills, G., Gale, W. G., Patterson, R., & Apostolov, E. (2006). What do individual development accounts do? Evidence from a controlled experiment. Social Sciences Research Network. Abstract retrieved December 5.2009 from:

Pearlin, L. I., & Schooler, C. (1978). The structure of coping. Journal of Health and Social Behavior, 19(March), 2-21.

Reutebuch, T. G. (2001). An exploration into individual development accounts as an anti-poverty strategy. Journal of Sociology & Social Welfare, 28(3), 95-107.

Richards, R. (2003). Integrity of individual development: Watering down the ida. The Georgetown Journal of Gender and Law, 4, 919-950.

Rohe, W. M., Gorham, L. S., & Quercia, R. G. (2005). Individual development accounts: Participants' characteristics and success. Journal of Urban Affairs, 27(5), 503-520.

Rom, M. C. (2005). Investing in individuals for independence. Review of Policy Research, 22(3), 369-383.

Schreiner, M., Ng, G. T., & Sherraden, M. (2006). Cost-effectiveness in individual development accounts. Research on Social Work Practice, 16(1), 28-37.

Schreiner, M., & Sherraden, M. (2007). Can the poor save? Saving and asset accumulation in individual development accounts. New Brunswick: Transaction.

Sherraden, M. (2000). From research to policy: Lessons from individual development accounts. Journal of Consumer Affairs, 34(Winter), 159-181.

Shobe, M. A. (2002). The future in anti-poverty strategies. Journal of Children and Poverty, 8(1), 35-49.

Shobe, M. A., & Boyd, A. S. (2003). Increasing the economic self-sufficiency of rural families: Individual development accounts. The Social Policy Journal, 2(2/3), 63-87.

Shobe, M. A., & Page-Adams, D. (2001). Assets, future orientation, and well-being: Exploring and extending Sherraden's framework. Journal of Sociology & Social Welfare, 28(3), 109-127.

Strathman, A., Gleicher, F., Boninger, D. S., & Edwards, C. S. (1994). The consideration of future consequences: Weighting immediate and distnt outcomes of behavior. Journal of Personality and Social Psychology, 66(4), 742-752.

Tangeney, J. P., Baumeister, R. F., & Boone, A. L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72(2), 271-324.