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

Introduction

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.
Homeownership

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)
N=83

Figure 1.
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.
Education

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.
Microenterprise

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)
N=38

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.

Recommendations

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).

Limitations

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.

Acknowledgement

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

References

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