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The effects of welfare-to-work programs on child well-being are addressed in two chapters in this report. This chapter captures the breadth of the effects of seven welfare-to-work programs on the well-being of children of all respondents in the Five-Year Client Survey. Program effects are evaluated for children in four age groups, — from toddlers to adolescents at the time of study entry, — and on outcomes in two domains of child development — academic functioning and health and safety — as well as on and on selected other selected outcomes. Chapter 12 analyzes, in greater depth, effects on child well-being at the five- year follow-up for a subset of "focal" children, aged 3 to 5 at random assignment, in six welfare-to-work programs in Atlanta, Grand Rapids, and Riverside. (1) Details about the samples examined in these two chapters and how they are derived from the full impact sample in this report are shown in Figure 11.1.
Figure 11.1
Samples and Subsamples Used In Chapter 11 and 12
As discussed in Chapter 1, a central goal of the federal JOBS program, under the 1988 Family Support Act (FSA), was to move single mothers from public assistance to paid employment. This goal was largely implemented by imposing strict participation and work requirements. For 20 years prior to 1988, women receiving welfare who had children under age 6 generally were not subject to these mandates. With the passage of the FSA, women with children as young as age 3 (or as young as age 1, at state option) were newly designated as mandatory participants. Thus, in the early 1990s there was much interest in how welfare-to-work programs might affect children, especially very young children. that differed from the past, particularly for mothers who had children aged less than 6. The well-being of children remained of central concern and produced considerable debate at the passage of this legislation as well as the more recent 1996 welfare reform law (Personal Responsibility and Work Opportunity Reconciliation Act, or PRWORA) that similarly imposed requirements to move welfare recipients into employment and imposed participation mandates on women with children as young as age 1 (or younger, at state option). A two-year follow-up evaluation of the effects of the NEWWS programs on child well-being, which outcomes that included a special study of preschool-age children, was one of the first to inform this debate. The analysis in these two chapters represents the first evaluations of long-term effects of mandatory welfare-to-work programs on the well-being of children.
Earlier chapters in this report primarily focused on the effects of welfare-to-work programs on the outcomes targeted by these programs, such as education, employment, and welfare receipt. As these chapters revealed, during the five-year follow-up period the NEWWS programs, regardless of whether they were program was employment- or education-focused, generally increased participation in employment-related activities, employment and earnings and reduced public assistance payments. for all respondents in the study. The consistency of these findings across programs and sites is not surprising given the stated goals of the programs. Appendix I, summarizes these effects for the Five-Year Client Survey sample and shows that, with some exceptions for the Riverside LFA and HCD programs, and, most important, the Portland program, the pattern of impacts for the respondents in the Five-Year Client Survey sample were quite similar to the impacts for the full impact sample are presented and discussed in Chapters 4-6.
Unlike early childhood intervention programs, the NEWWS programs were not structured to directly affect the well-being of children. It is still possible, however, that welfare-to-work programs could produced either favorable or unfavorable effects on child outcomes. Current theories hypothesize that, by affecting the behavior of mothers' programs could also indirectly affect children's well-being through, for example, changes in mothers' psychological well-being or parenting skills or styles, in child care, and/or in family life and material resources. Some of these changes may bode well for certain child outcomes but prove problematic for others, and thus the effects of a given type of welfare-to-work program on child outcomes may not be uniformly favorable or unfavorable across developmental domains.(2) Also, it is possible that program impacts on child outcomes may vary, depending on whether the effects are enduring, the extent of the exposure to the program, or on the combined effects of all program impacts.
The ways that welfare programs might affect child well-being can be depicted in a simple conceptual framework.(3) A program's features, such as its message, sanctioning rates, and monitoring, can affect the targeted or direct outcomes of the program, such as employment, public assistance receipt, income, and education, and nontargeted outcomes, such as child care and parenting behavior, and ultimately leading to effects on child outcomes. Prior research, though largely based on nonexperimental studies, provides a basis for predicting and understanding how effects on key outcomes such as education, employment, earnings, and income may affect children. For example, mothers' increased educational attainment and employment (depending on the extent and quality of the job), and/or family income may prove beneficial to children in low-income families.(4) Mothers' psychological well-being and parenting — shown to be related to children's developmental outcomes in the nonexperimental literature(5) — may also be affected by these programs, though the extent and direction of likely change may vary.(6) Child care is another way in which mothers' employment may affect children. Unstable or low-quality child care may produce detrimental effects on children's development.(7)
This chapter reviews general hypotheses and impact findings on child outcomes, organized by child age. It discusses whether or not mothers with children in various age groups may have behaved and responded differently to these welfare-to-work programs.(8), (9) Also, welfare-to-work programs might have affected children differently at different points in their development. For example, toddlers may be the most vulnerable to possible negative effects of mothers' employment, particularly if they are placed in poor-quality child care. Adolescents, in contrast, may have the most to gain if they are placed in enriching after-school programs. Older children may be left unsupervised or may take on more responsibilities at home as mothers join the workforce, which could lead to unfavorable effects on their development, particularly their social behavior. In reviewing the discussion of impacts throughout this chapter, it is important to remember that, as discussed in Chapter 1, some control group members in Atlanta and Grand Rapids became eligible for program services after the third year of the follow-up period. However, it appears that program impacts on earnings and welfare receipt were only slightly affected by the end of the control group embargo in these sites. The chapter then ends with a discussion, again by child age, of what may have led to that program effects on children.
Table 11.1 summarizes the impacts on the limited set of outcomes examined in this chapter, by child age.
| Academic Functioning | Health and Safety | Other | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Repeated a Grade | Suspended or Expelled | Attended a Special Class for a Condition | Dropped Out of School | Had a Condition That Required Frequent Medical Attention | Required Emergency Room Visit | Had a Condition That Impeded on Mother's Ability to Go to Work or School | Did Not Live With Mother Because She Could Not Care for Child | Had a Baby as a Teen | |
Toddlers |
|||||||||
| Grand Rapids LFA | F | - | F | - | |||||
| Grand Rapids HCD | F | - | - | ||||||
| Portland | - | - | |||||||
Preschool-age children |
|||||||||
| Atlanta LFA | - | U | U | - | |||||
| Atlanta HCD | - | U | - | ||||||
| Grand Rapids LFA | - | - | |||||||
| Grand Rapids HCD | U | - | - | ||||||
| Riverside LFA | F | - | f | F | S | - | |||
| In needa | F | - | F | - | |||||
| Riverside HCD | - | - | |||||||
| Portland | - | - | |||||||
Young school-age children |
|||||||||
| Atlanta LFA | - | ||||||||
| Atlanta HCD | - | ||||||||
| Grand Rapids LFA | u | U | - | ||||||
| Grand Rapids HCD | F | F | - | ||||||
| Riverside LFA | F | S | - | ||||||
| In needa | u | F | S | - | |||||
| Riverside HCD | F | F | S | - | |||||
| Portland | - | ||||||||
Adolescents |
|||||||||
| Atlanta LFA | F | f | |||||||
Atlanta HCD |
|||||||||
| Grand Rapids LFA | U | u | u | ||||||
| Grand Rapids HCD | U | u | |||||||
| Riverside LFA | U | u | F | S | |||||
| In needa | u | U | F | s | U | ||||
| Riverside HCD | U | U | U | U | u | ||||
| Portland | |||||||||
| NOTES: "F" indicates a statistically significant
favorable impact. "U" indicates a statistically significant unfavorable impact.
"f" indicates a favorable impact above the cutoff for statistical significance
but part of the overall pattern. "u" indicates an unfavorable impact above
the cutoff for statistical significance but part of the overall pattern.
"S" indicates a statistically significant impact that could not be categorized
as favorable or unfavorable. "s" indicates an impact above the cutoff for
statistical significance but part of the overall pattern. See
Chapter 2 for the definition of a pattern. "-"
indicates that a measure was not appropriate for a particular child age group.
Blank spaces indicate that there were no impacts. a Sample members lacked a high school diploma or basic skills at random assignment. |
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The measures of child well-being analyzed in this section were constructed from mothers' responses to the Five-Year Client Survey. Respondents were asked about their children's academic functioning, health and safety, and other outcomes. (See Table 11.1.) Respondents answered for their own children — whether biological children, legally adopted children, or stepchildren. Although they were asked about all children regardless of age, this analysis is limited to children who were aged 18 or under at random assignment. This section provides a discussion about the construction of these measures. (Details about these measures can also be found in Appendix J.)
Respondents were asked a variety of questions about their children, concerning events or situations since a focal date. For most respondents the focal date was the date of the two-year interview. For those who did not answer the two-year survey, the focal date was the date of random assignment. Thus, for most respondents, child outcomes are measured for years 3 to 5 of follow-up (that is, since the two-year interview point). Some outcomes, such as dropping out of school, were not restricted to the period of time since the focal date. Instead these outcomes were measured "ever" in a child's life.
The first group of measures captures children's academic functioning including whether or not they had been suspended or expelled from school, repeated a grade, dropped out of school, or attended a special class or special school for a physical, emotional, or mental condition.
The second group of measures captures children's health and safety, including whether they had a physical, emotional, or mental condition that required frequent medical attention, frequent use of medication, or the use of any special equipment; whether they ever had a physical, emotional, or mental condition that demanded a lot of attention and made it difficult for the respondent to attend work or school; and whether they had an accident, injury, or poisoning that required a visit to a hospital emergency room or clinic. This last outcome is only a rough proxy for child safety. On the one hand, it may measure neglect if children are experiencing more accidents or injuries as mothers increase their work effort and children are left unsupervised, with abusive partners or other adults, or, possibly, placed in unsafe child care arrangements. On the other hand, this outcome may simply reflect a mother's ability to purchase medical care. Emergency room use may be used as a replacement for visits to a doctor or a clinic.
The final group of measures concerns living arrangements (whether a child did not live with their mother because she could not care for them) and teenage parents (whether a child gave birth as a teenager). In this analysis children were considered to have been teenage parents if they had a child at age 18 or under during the five-year follow-up period. Whether children did not live with their mother because she could not care for them may have numerous interpretations: It may capture the consequence or result of a government intervention in the family, for example, being forced to place children in foster care. However, it is also possible that a mother voluntarily elected to place her children in another living arrangement, which may provide a better environment. This outcome may be also interpreted more generally as a measure of household composition or living arrangements rather than a direct measure of child well-being.
Outcomes in this chapter are presented for any child in the family and for each child in the family. Measures presented for any child indicate the percentage of families in which at least one child experienced a certain outcome (for example, "any child ever repeated a grade" indicates that at least one child in the family repeated a grade) and provide a general snapshot of child outcomes at the family level. These measures are similar to those analyzed at the two-year follow-up point. Measures presented for each child in the family indicate the percentage of children who have experienced a certain outcome. Thus, unlike most of the information collected in the survey, these outcomes are specific to a child within a family. Each child in a family who was 18 or under at random assignment is represented in the impact analysis.(11) The 5,342 families in this analysis had a total of 13,726 children.
Four age groups of children are examined:
The ages of respondent's children varied across sites. As discussed in Chapter 1, mothers with children aged 3 or over were required to participate in most sites. However, in Grand Rapids and Portland, the participation mandate was extended to single mothers with a child as young as age 1. Although this analysis treats children mutually exclusively, the mothers of these children within and across each age group are not mutually exclusive: 41.5 percent of respondents have more than one child within one age group and 49.6 percent have at least one child in more than one age group. The sample size for each of these age categories and the general structure of how the samples were derived for these two chapters are presented in Figure 11.1.
Although the outcomes covered in this chapter provide important information about child well-being, they have some limitations. First, all of them are based on mothers' reports, which may differ from teachers' or children's reports or from direct assessments of the children.(13) Second, the outcomes provide only a snapshot of particular domains of children's development. For example, children's problem behavior (such as their expressions of anxiety, depression, or aggression) and positive behavior (such as their interaction with peers and others) are not captured, and it may be that the NEWWS programs are most likely to affect these behaviors. Measures collected in the Child Outcomes Study described in Chapter 12 address these limitations.
Third, similar measures were collected and constructed for each child regardless of age, yet these measures have different implications by child age. For example, partly because of age requirements for employment, an adolescent who repeats a grade may be much more likely to drop out of school and possibly enter the labor force than a younger school-age child who repeats a grade. Dropping out of school is highly correlated with future labor force participation.(14) In addition, control group levels on these outcomes might differ by age group: Control group levels of suspension or expulsion are naturally higher for adolescents than for early school-age children, making it harder for programs to produce any statistically significant changes.
To provide some basis for evaluating the magnitude of impacts, Tables 11.2-11.6 and Tables 12.1-12.5 report effect sizes in the last column. The accompanying text box describes effect sizes in more detail.
Effect Sizes and the Magnitude of Effects on Child Outcomes Evaluating the effects of welfare-to-work programs on child outcomes also requires an assessment of whether the effects are big or small. An impact may be statistically significant, but is it large enough to be deemed important? Evaluating the size of an impact on various measures of adult economic outcomes is relatively straightforward. For example, most can assess whether or not an impact of $200 is a big or small effect on an individual's annual income. It is much more challenging to evaluate whether or not a 10 point change in a scale measuring a child's behavioral problems or a 5 percent change in a scale measuring school progress is big or small. One method of assessing impact size is to standardize it. To do this, impact estimates can be converted into effect sizes. Effect sizes are computed by dividing the impact (the difference in outcomes between the program group and the control group) by the standard deviation of the outcome for the control group. The value of the effect size provides a standardized measure of the program impact that can be used to compare program impacts on outcomes with very different scales. Effect sizes generally range from 0 to 1; a larger absolute value indicates a larger impact on an outcome and a smaller absolute value indicates a smaller impact. Effect sizes rather than percentage changes are reported in the last column of Tables 11.2-11.6 and Tables 12.1-12.5. How large are these effects? Generally effect sizes of 0.1, 0.3, and 0.5 are considered small, medium and large, respectively.a However, these benchmarks are based on nonexperimental studies that cover a broad range of topics. One method is to compare effect sizes on adult economic outcomes and effects sizes on child outcomes. Most welfare and employment programs generate effect sizes of about 0.2 to 0.3 on outcomes such as employment and earnings, and effect sizes on child outcomes are generally half this size. Another method is to compare these effect sizes with effects produced from child-focused interventions such as the Perry Preschool Program and the Abecedarian Project. These child-focused interventions produced effects that generally ranged from 0.2 to 1.0. Finally, it is important to consider that even small effects may have a large impact on the future well-being of a child. Longitudinal studies of children have found that achievement and behavior problems can have important implications for children's well-being as adults.b For example, achievement and problem behavior in early childhood are related to adolescent achievement and behavior. Small effects (for example, 0.1-0.2) may continue to have implications for children over their lives.
a Cohen, 1988; Lipsey, 1990. |
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Table 11.2 shows impacts on child outcomes for any child in a survey respondent's family. As mentioned above, these analyses are similar to those conducted at the two-year follow-up point. Although some measures are directly comparable with the two-year measures, such as grade repetition and suspensions or expulsions, the estimates are shown for the five-year survey sample only (rather than for the sample that had information collected at both the two-year and five-year points).
Site and Program |
Sample Size | Program Group (%) | Control Group (%) | Difference (Impact) | Effect Size |
|---|---|---|---|---|---|
| Any child ever repeated a grade | |||||
| Atlanta Labor Force Attachment | 1,048 | 21.3 | 25.6 | -4.3* | -0.10 |
| Atlanta Human Capital Development | 1,125 | 20.8 | 25.6 | -4.8* | -0.11 |
| Grand Rapids Labor Force Attachment | 1,077 | 20.8 | 16.9 | 3.9 | 0.10 |
| Grand Rapids Human Capital Development | 1,085 | 21.9 | 16.9 | 5.0** | 0.13 |
| Riverside Labor Force Attachment | 1,196 | 11.9 | 11.6 | 0.3 | 0.01 |
| Lacked high school diploma or basic skills | 644 | 11.4 | 12.6 | -1.2 | -0.03 |
| Riverside Human Capital Development | 767 | 14.9 | 12.6 | 2.2 | 0.06 |
| Portland | 493 | 12.1 | 8.2 | 3.9 | 0.14 |
| Any child suspended or expelled | |||||
| Atlanta Labor Force Attachment | 1,049 | 28.6 | 31.9 | -3.3 | -0.07 |
| Atlanta Human Capital Development | 1,125 | 32.4 | 31.9 | 0.5 | 0.01 |
| Grand Rapids Labor Force Attachment | 1,072 | 24.8 | 26.5 | -1.7 | -0.04 |
| Grand Rapids Human Capital Development | 1,081 | 22.0 | 26.5 | -4.4* | -0.10 |
| Riverside Labor Force Attachment | 1,190 | 21.4 | 24.1 | -2.7 | -0.06 |
| Lacked high school diploma or basic skills | 639 | 18.5 | 25.0 | -6.5** | -0.15 |
| Riverside Human Capital Development | 760 | 22.7 | 25.0 | -2.3 | -0.05 |
| Portland | 490 | 29.4 | 29.7 | -0.3 | -0.01 |
| Any child ever dropped out of schoola | |||||
| Atlanta Labor Force Attachment | 1,049 | 17.3 | 18.4 | -1.1 | -0.03 |
| Atlanta Human Capital Development | 1,126 | 19.6 | 18.4 | 1.3 | 0.03 |
| Grand Rapids Labor Force Attachment | 1,077 | 19.3 | 17.8 | 1.5 | 0.04 |
| Grand Rapids Human Capital Development | 1,088 | 18.6 | 17.8 | 0.8 | 0.02 |
| Riverside Labor Force Attachment | 1,198 | 15.5 | 13.7 | 1.8 | 0.05 |
| Lacked high school diploma or basic skills | 643 | 16.3 | 14.2 | 2.2 | 0.06 |
| Riverside Human Capital Development | 768 | 17.9 | 14.2 | 3.8 | 0.11 |
| Portland | 495 | 21.8 | 20.1 | 1.6 | 0.04 |
| Any child attended a special class for a physical, emotional, or mental conditionb | |||||
| Atlanta Labor Force Attachment | 1,050 | 12.6 | 12.0 | 0.6 | 0.02 |
| Atlanta Human Capital Development | 1,128 | 10.5 | 12.0 | -1.5 | -0.05 |
| Grand Rapids Labor Force Attachment | 1,077 | 28.9 | 28.3 | 0.6 | 0.01 |
| Grand Rapids Human Capital Development | 1,084 | 28.5 | 28.3 | 0.2 | 0.00 |
| Riverside Labor Force Attachment | 1,197 | 20.1 | 18.0 | 2.1 | 0.06 |
| Lacked high school diploma or basic skills | 643 | 20.9 | 18.8 | 2.1 | 0.05 |
| Riverside Human Capital Development | 768 | 20.3 | 18.8 | 1.4 | 0.04 |
| Portland | 494 | 29.2 | 24.8 | 4.4 | 0.10 |
| Any child had a physical, emotional, or mental condition that impeded on mother's ability to go to work or schoolb | |||||
| Atlanta Labor Force Attachment | 1,048 | 6.9 | 5.8 | 1.1 | 0.05 |
| Atlanta Human Capital Development | 1,128 | 6.9 | 5.8 | 1.1 | 0.05 |
| Grand Rapids Labor Force Attachment | 1,080 | 13.0 | 14.7 | -1.6 | -0.05 |
| Grand Rapids Human Capital Development | 1,091 | 10.4 | 14.7 | -4.3** | -0.12 |
| Riverside Labor Force Attachment | 1,200 | 10.0 | 12.1 | -2.1 | -0.06 |
| Lacked high school diploma or basic skills | 645 | 7.7 | 9.9 | -2.2 | -0.07 |
| Riverside Human Capital Development | 768 | 13.9 | 9.9 | 4.0* | 0.13 |
| Portland | 493 | 20.6 | 19.0 | 1.6 | 0.04 |
| Any child had a physical, emotional, or mental condition that required frequent medical attentionb | |||||
| Atlanta Labor Force Attachment | 1,049 | 11.7 | 10.6 | 1.1 | 0.04 |
| Atlanta Human Capital Development | 1,127 | 8.9 | 10.6 | -1.7 | -0.06 |
| Grand Rapids Labor Force Attachment | 1,077 | 20.3 | 19.2 | 1.1 | 0.03 |
| Grand Rapids Human Capital Development | 1,085 | 15.5 | 19.2 | -3.7 | -0.10 |
| Riverside Labor Force Attachment | 1,198 | 13.0 | 16.2 | -3.2 | -0.09 |
| Lacked high school diploma or basic skills | 645 | 11.5 | 13.6 | -2.1 | -0.06 |
| Riverside Human Capital Development | 769 | 13.5 | 13.6 | -0.1 | -0.00 |
| Portland | 494 | 23.3 | 20.5 | 2.8 | 0.07 |
| Any child ever had accident, injury, or poisoning that required an emergency room visit | |||||
| Atlanta Labor Force Attachment | 1,042 | 22.4 | 25.4 | -3.1 | -0.07 |
| Atlanta Human Capital Development | 1,118 | 21.4 | 25.4 | -4.0 | -0.09 |
| Grand Rapids Labor Force Attachment | 1,071 | 35.7 | 36.9 | -1.2 | -0.02 |
| Grand Rapids Human Capital Development | 1,085 | 31.5 | 36.9 | -5.4* | -0.11 |
| Riverside Labor Force Attachment | 1,186 | 38.1 | 39.5 | -1.3 | -0.03 |
| Lacked high school diploma or basic skills | 639 | 34.0 | 37.2 | -3.2 | -0.07 |
| Riverside Human Capital Development | 763 | 35.9 | 37.2 | -1.3 | -0.03 |
| Portland | 490 | 42.1 | 41.6 | 0.5 | 0.01 |
| Any child did not live with mother because she could not care for child | |||||
| Atlanta Labor Force Attachment | 1,051 | 4.3 | 5.2 | -1.0 | -0.04 |
| Atlanta Human Capital Development | 1,129 | 4.0 | 5.2 | -1.3 | -0.06 |
| Grand Rapids Labor Force Attachment | 1,082 | 7.3 | 7.2 | 0.1 | 0.01 |
| Grand Rapids Human Capital Development | 1,094 | 7.7 | 7.2 | 0.5 | 0.02 |
| Riverside Labor Force Attachment | 1,203 | 10.9 | 8.6 | 2.3 | 0.08 |
| Lacked high school diploma or basic skills | 647 | 10.3 | 7.0 | 3.3 | 0.12 |
| Riverside Human Capital Development | 770 | 9.0 | 7.0 | 2.0 | 0.07 |
| Portland | 495 | 11.6 | 12.5 | -1.0 | -0.03 |
| Any child ever had a baby as a teenc | |||||
| Atlanta Labor Force Attachment | 1,047 | 14.8 | 19.3 | -4.5** | -0.12 |
| Atlanta Human Capital Development | 1,126 | 18.2 | 19.3 | -1.1 | -0.03 |
| Grand Rapids Labor Force Attachment | 1,081 | 12.5 | 15.1 | -2.6 | -0.07 |
| Grand Rapids Human Capital Development | 1,091 | 15.0 | 15.1 | -0.1 | -0.00 |
| Riverside Labor Force Attachment | 1,199 | 12.0 | 10.0 | 2.0 | 0.07 |
| Lacked high school diploma or basic skills | 645 | 15.5 | 10.6 | 4.9** | 0.16 |
| Riverside Human Capital Development | 768 | 13.3 | 10.6 | 2.7 | 0.09 |
| Portland | 495 | 9.6 | 13.6 | -4.1 | -0.12 |
| SOURCE: MDRC calculations from the Five-Year
Client Survey. NOTES: See Appendix A.2. Owing to missing values, sample sizes may vary. a Measures whether the child dropped out of school at any point during the child's lifetime. b Refers to conditions that were current at the time the survey was administered. c Measures whether the child had a baby while a teenager at any point during the five-year follow-up period. |
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Although there was no consistent pattern of effects on outcomes for any child in a family, there were more effects than would be expected by chance. Notably, of the effects that occurred, most were produced by the Grand Rapids HCD program. The effects, however, were both favorable and unfavorable within outcome or domain (across program approaches or site). For example, the Atlanta HCD program decreased the proportion of families who had a child retained in grade by approximately 5 percentage points, whereas the Grand Rapids HCD program increased it by 5 percentage points. The Grand Rapids HCD program also decreased the proportion of families with a child who had a physical, emotional, or mental condition that demanded a lot of attention, and the Riverside HCD program increased it. These noted effects also show that effects varied by program approach and site (across outcomes or domains). The conclusion drawn here about the effects of welfare-to-work programs on these outcomes measured for any child in the family are similar to the conclusion drawn at the two-year follow-up point.
As previously discussed, while evaluating effects on any child in a family may be useful in capturing a general snapshot, there are reasons to suspect that this kind of analysis may not be revealing clear patterns of effects on each child. The next sections review impacts presented in Tables 11.3-11.6 and show that some of the impacts that occurred for the analysis of any child in the family (such as effects in Atlanta on grade repetition) also generally occurred, though not always statistically significant, across children in many age groups. As would be expected, other effects, such as on teen childbearing, were concentrated among adolescents.
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Impacts for survey sample respondents with toddlers (present in Grand Rapids and Portland samples only) are similar to impacts found for the client survey sample. Thus, mothers of these toddlers experienced some increased employment and losses in income from welfare and earnings. Research finds some evidence that mothers' employment during the first few years of life may be particularly detrimental to children's development.(15) The Canadian Self-Sufficiency Project, however, provides some evidence, based on limited outcomes, that welfare and employment programs that increase employment and income do not cause harm to infants and toddlers. Less is known about the sole effect of decreased income.(16)
Table 11.3 shows outcomes and impacts for children who were toddlers at study entry in the Grand Rapids and Portland sites. (These children were roughly 1st and 2nd graders at the time of the five-year follow-up.) Approximately 10 percent of these children in the Grand Rapids control group and 4 percent in the Portland control group repeated a grade during the last three years of follow-up. This range is comparable to national figures, which show that 7 percent of all 2nd graders and 10 percent of 2nd graders below poverty were retained in kindergarten or 1st grade in 1996.(17) Incidences of suspensions and expulsions among this age group — approximately 6 percent — seem quite high and, given that many of these children were aged 3 to 5 three years prior to the five year follow-up, may reflect suspensions or expulsions from child care arrangements rather than school. Possibly more alarming for this age group is that approximately 5 to 6 percent of these children in the control group did not live with their mother at some point during the follow-up period because she could not care for them.
Site and Program |
Sample Size | Program Group (%) | Control Group (%) | Difference (Impact) | Effect Size |
|---|---|---|---|---|---|
Ever repeated a grade |
|||||
| Grand Rapids Labor Force Attachment | 361 | 8.7 | 10.4 | -1.6 | -0.05 |
| Grand Rapids Human Capital Development | 381 | 8.2 | 10.4 | -2.1 | -0.07 |
| Portland | 217 | 6.2 | 3.6 | 2.6 | 0.19 |
Ever suspended or expelled |
|||||
| Grand Rapids Labor Force Attachment | 360 | 0.0 | 6.2 | -6.4*** | -0.27 |
| Grand Rapids Human Capital Development | 380 | 1.6 | 6.2 | -4.6** | -0.19 |
| Portland | 217 | 6.6 | 6.0 | 0.6 | 0.03 |
Attended a special class for physical, emotional, or mental conditiona |
|||||
| Grand Rapids Labor Force Attachment | 358 | 11.5 | 15.2 | -3.7 | -0.10 |
| Grand Rapids Human Capital Development | 379 | 14.7 | 15.2 | -0.5 | -0.01 |
| Portland | 215 | 20.0 | 17.2 | 2.8 | 0.08 |
Had a physical, emotional, or mental condition that impeded on mother's ability to go to work or schoola |
|||||
| Grand Rapids Labor Force Attachment | 364 | 6.3 | 7.6 | -1.3 | -0.05 |
| Grand Rapids Human Capital Development | 385 | 4.8 | 7.6 | -2.8 | -0.10 |
| Portland | 218 | 13.2 | 12.9 | 0.2 | 0.01 |
Had a physical, emotional, or mental condition that required frequent medical attentiona |
|||||
| Grand Rapids Labor Force Attachment | 363 | 7.3 | 14.1 | -6.8** | -0.20 |
| Grand Rapids Human Capital Development | 385 | 10.3 | 14.1 | -3.9 | -0.12 |
| Portland | 218 | 14.4 | 11.7 | 2.7 | 0.09 |
Ever had accident, injury, or poisoning that required an emergency room visit |
|||||
| Grand Rapids Labor Force Attachment | 358 | 23.0 | 24.3 | -1.3 | -0.03 |
| Grand Rapids Human Capital Development | 380 | 19.4 | 24.3 | -4.9 | -0.11 |
| Portland | 216 | 20.3 | 27.0 | -6.8 | -0.15 |
Did not live with mother because she could not care for child |
|||||
| Grand Rapids Labor Force Attachment | 364 | 6.2 | 4.6 | 1.6 | 0.07 |
| Grand Rapids Human Capital Development | 386 | 5.0 | 4.6 | 0.4 | 0.02 |
| Portland | 218 | 8.4 | 6.0 | 2.4 | 0.10 |
| SOURCE: MDRC calculations from the Five-Year
Client Survey. NOTES: See Appendix A.2. Standard errors have been adjusted to account for the presence of multiple siblings within a family. Owing to missing values, sample sizes may vary. a Refers to conditions that were current at the time the survey was administered. |
|||||
In general, few program effects were found for this age group. Given that the mothers of these toddlers generally experienced increased employment, it is noteworthy that more unfavorable effects were not found. Some of the unfavorable effects of employment on children may be influenced by the type and hours of employment, whether or not a mother wants to be employed, and the quality of child care. In fact, both Grand Rapids programs produced a consistent (though not always statistically significant) pattern of favorable effects for six of the seven outcome measures examined. The LFA and HCD program effects on suspensions and expulsions and the LFA effect on a condition requiring frequent medical attention were statistically significant and of a modest-to-large size relative to effects on child outcomes observed in comparable experimental studies.(18)
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With a few exceptions, impacts on economic outcomes for survey sample respondents with preschool-age children are similar in Atlanta, Grand Rapids, and Portland to impacts noted for the client survey sample.(19) However, in Riverside impacts are larger and more pronounced for survey sample respondents with preschool-age children than for the client survey sample. In particular, the Riverside LFA employment impacts for each of the five years of follow-up and cumulative earnings impacts for survey sample respondents with preschool-age children are nearly one-third to twice as big as impacts for the client survey sample.(20) The effects of mothers' employment for this age group may be either favorable (for example, through role modeling) or unfavorable. Although most of the children in this age group are likely to be in school for a large portion of the day, they still require supervision during off-school hours, and, thus, the effects of mothers' employment may also depend on the quality of child care or out-of-school arrangements. Recent evidence suggests that programs that increased employment and increased income have positive benefits for young school-age children, particularly in their cognitive development.(21) Research on the effects of poverty also finds that the negative effects of poverty are particularly pronounced for this age group of children.(22)
Outcomes and impacts for children of preschool-age at study entry (young school-age at the time of the five-year follow-up) are shown in Table 11.4. The table shows that 7 to 12 percent of children in the control group repeated a grade and 5 to 15 percent were ever suspended or expelled during the last three years of the follow-up period. The youngest of these children were likely in 2nd grade. For the oldest of these children, national figures for a roughly comparable age group show that 3.3 percent of 4th to 8th graders were retained in grade in 1995.(23) Roughly 5 to 7 percent of these children did not live with their mother because she could not care for them.
Site and Program |
Sample Size | Program Group (%) | Control Group (%) | Difference (Impact) | Effect Size |
|---|---|---|---|---|---|
Ever repeated a grade |
|||||
| Atlanta Labor Force Attachment | 766 | 11.9 | 11.9 | -0.0 | -0.00 |
| Atlanta Human Capital Development | 876 | 10.2 | 11.9 | -1.7 | -0.05 |
| Grand Rapids Labor Force Attachment | 562 | 13.5 | 10.4 | 3.1 | 0.10 |
| Grand Rapids Human Capital Development | 534 | 15.7 | 10.4 | 5.2* | 0.17 |
| Riverside Labor Force Attachment | 829 | 4.4 | 9.7 | -5.2*** | -0.18 |
| Lacked high school diploma or basic skills | 501 | 4.5 | 11.4 | -6.9*** | -0.22 |
| Riverside Human Capital Development | 648 | 8.9 | 11.4 | -2.5 | -0.08 |
| Portland | 262 | 6.4 | 7.1 | -0.7 | -0.03 |
Ever suspended or expelled |
|||||
| Atlanta Labor Force Attachment | 766 | 8.8 | 8.7 | 0.2 | 0.01 |
| Atlanta Human Capital Development | 876 | 8.8 | 8.7 | 0.1 | 0.00 |
| Grand Rapids Labor Force Attachment | 561 | 6.6 | 8.2 | -1.6 | -0.06 |
| Grand Rapids Human Capital Development | 532 | 7.6 | 8.2 | -0.6 | -0.02 |
| Riverside Labor Force Attachment | 820 | 4.3 | 6.2 | -1.9 | -0.08 |
| Lacked high school diploma or basic skills | 496 | 4.0 | 4.7 | -0.8 | -0.04 |
| Riverside Human Capital Development | 640 | 5.5 | 4.7 | 0.8 | 0.04 |
| Portland | 257 | 9.4 | 14.8 | -5.4 | -0.16 |
Attended a special class for physical, emotional, or mental conditiona |
|||||
| Atlanta Labor Force Attachment | 766 | 8.2 | 7.2 | 1.0 | 0.04 |
| Atlanta Human Capital Development | 876 | 6.1 | 7.2 | -1.2 | -0.04 |
| Grand Rapids Labor Force Attachment | 559 | 21.7 | 18.9 | 2.8 | 0.07 |
| Grand Rapids Human Capital Development | 529 | 22.6 | 18.9 | 3.7 | 0.09 |
| Riverside Labor Force Attachment | 828 | 14.5 | 13.7 | 0.9 | 0.03 |
| Lacked high school diploma or basic skills | 498 | 17.2 | 15.6 | 1.6 | 0.04 |
| Riverside Human Capital Development | 646 | 13.0 | 15.6 | -2.7 | -0.07 |
| Portland | 259 | 19.5 | 18.8 | 0.7 | 0.02 |
Had a physical, emotional, or mental condition that impeded on mother's ability to go to work or schoola |
|||||
| Atlanta Labor Force Attachment | 767 | 5.3 | 1.8 | 3.5*** | 0.26 |
| Atlanta Human Capital Development | 877 | 3.2 | 1.8 | 1.3 | 0.10 |
| Grand Rapids Labor Force Attachment | 564 | 7.1 | 6.7 | 0.3 | 0.01 |
| Grand Rapids Human Capital Development | 536 | 6.8 | 6.7 | 0.1 | 0.00 |
| Riverside Labor Force Attachment | 832 | 4.9 | 8.5 | -3.6** | -0.13 |
| Lacked high school diploma or basic skills | 501 | 3.4 | 7.0 | -3.6* | -0.14 |
| Riverside Human Capital Development | 648 | 7.3 | 7.0 | 0.3 | 0.01 |
| Portland | 262 | 13.8 | 16.2 | -2.4 | -0.06 |
Had a physical, emotional, or mental condition that required frequent medical attentiona |
|||||
| Atlanta Labor Force Attachment | 767 | 7.1 | 3.4 | 3.7** | 0.20 |
| Atlanta Human Capital Development | 877 | 6.8 | 3.4 | 3.4** | 0.18 |
| Grand Rapids Labor Force Attachment | 563 | 13.9 | 11.2 | 2.7 | 0.08 |
| Grand Rapids Human Capital Development | 536 | 13.2 | 11.2 | 2.0 | 0.06 |
| Riverside Labor Force Attachment | 832 | 6.9 | 9.9 | -3.0 | -0.10 |
| Lacked high school diploma or basic skills | 501 | 6.9 | 8.7 | -1.8 | -0.06 |
| Riverside Human Capital Development | 648 | 7.2 | 8.7 | -1.5 | -0.05 |
| Portland | 260 | 16.0 | 11.0 | 5.0 | 0.16 |
Ever had accident, injury, or poisoning that required an emergency room visit |
|||||
| Atlanta Labor Force Attachment | 766 | 15.1 | 16.0 | -0.9 | -0.02 |
| Atlanta Human Capital Development | 876 | 14.2 | 16.0 | -1.9 | -0.05 |
| Grand Rapids Labor Force Attachment | 561 | 22.7 | 22.0 | 0.7 | 0.02 |
| Grand Rapids Human Capital Development | 531 | 18.7 | 22.0 | -3.3 | -0.08 |
| Riverside Labor Force Attachment | 819 | 25.0 | 24.5 | 0.6 | 0.01 |
| Lacked high school diploma or basic skills | 498 | 22.9 | 19.3 | 3.6 | 0.09 |
| Riverside Human Capital Development | 640 | 20.2 | 19.3 | 0.9 | 0.02 |
| Portland | 258 | 33.3 | 24.7 | 8.6 | 0.20 |
Did not live with mother because she could not care for child |
|||||
| Atlanta Labor Force Attachment | 767 | 3.4 | 4.8 | -1.4 | -0.07 |
| Atlanta Human Capital Development | 877 | 3.0 | 4.8 | -1.8 | -0.09 |
| Grand Rapids Labor Force Attachment | 564 | 6.9 | 4.8 | 2.2 | 0.10 |
| Grand Rapids Human Capital Development | 538 | 5.1 | 4.8 | 0.3 | 0.01 |
| Riverside Labor Force Attachment | 831 | 9.9 | 6.6 | 3.3* | 0.13 |
| Lacked high school diploma or basic skills | 500 | 6.8 | 6.6 | 0.2 | 0.01 |
| Riverside Human Capital Development | 647 | 5.2 | 6.6 | -1.5 | -0.06 |
| Portland | 262 | 9.8 | 7.3 | 2.5 | 0.09 |
| SOURCE: MDRC calculations from the Five-Year
Client Survey. NOTES: See Appendix A.2. Standard errors have been adjusted to account for the presence of multiple siblings within a family. Owing to missing values, sample sizes may vary. a Refers to conditions that were current at the time the survey was administered. |
|||||
Again, few effects were found for this age group. The effects that were found were concentrated in Atlanta and Riverside, were all unfavorable in Atlanta, and, with one exception, favorable in Riverside. For example, both Atlanta programs increased the likelihood that a child had a condition requiring medical attention and Atlanta LFA increased the likelihood that a child had a condition that demanded a lot of attention. The Riverside LFA program decreased grade repetition by 5.2 percentage points. Attention should be drawn to the fact that the Riverside LFA program increased the likelihood that preschool-age children did not live with their mother because she could not care for them. It is interesting that the Riverside LFA program decreased grade repetition and, at the same time, increased the likelihood of not living with a parent.
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Impacts for survey sample respondents with young school-age children are similar to impacts noted for the client survey sample. As mentioned above for preschool-age children, young school-age children may also benefit from or be harmed by mothers' employment. Because most of the children in this age group are likely to be in school for a large portion of the day, the effects of mothers' employment depend on the quality of child care or other arrangements for supervision during off-school hours
Table 11.5 shows outcomes and impacts for children of young school-age at study entry (aged 11 to 14 at the five-year follow-up). Approximately 4 to 13 percent of children in the control group repeated a grade during the last three years of follow-up and 17 to 25 percent were ever suspended or expelled. Dropout rates were negligible (at about 1 percent). National figures show that 3.3 percent of 4th to 8th graders (as mentioned) and 2.4 percent of 9th to 12th graders were retained in grade in 1995.(24) Even though the age groups are not directly comparable it suggests that NEWWS sample rates of grade retention for this age group are higher than national rates. Rates of suspensions or expulsions, on the other hand, seem comparable to state figures. According to 1999 data from the National Survey of America's Families, 24.5 percent of children aged 12 to17 in families below 200 percent of poverty in California and 23.2 percent in Michigan were suspended or expelled.
Site and Program |
Sample Size | Program Group (%) | Control Group (%) | Difference (Impact) | Effect Size |
|---|---|---|---|---|---|
Ever repeated a grade |
|||||
| Atlanta Labor Force Attachment | 652 | 11.3 | 13.3 | -2.0 | -0.06 |
| Atlanta Human Capital Development | 697 | 9.7 | 13.3 | -3.6 | -0.10 |
| Grand Rapids Labor Force Attachment | 524 | 14.4 | 9.9 | 4.4 | 0.14 |
| Grand Rapids Human Capital Development | 513 | 12.6 | 9.9 | 2.7 | 0.09 |
| Riverside Labor Force Attachment | 758 | 7.6 | 6.0 | 1.5 | 0.06 |
| Lacked high school diploma or basic skills | 427 | 8.3 | 5.0 | 3.3 | 0.16 |
| Riverside Human Capital Development | 490 | 7.2 | 5.0 | 2.3 | 0.11 |
| Portland | 265 | 4.9 | 4.4 | 0.5 | 0.03 |
Ever suspended or expelled |
|||||
| Atlanta Labor Force Attachment | 653 | 25.0 | 25.0 | 0.1 | 0.00 |
| Atlanta Human Capital Development | 694 | 26.0 | 25.0 | 1.1 | 0.02 |
| Grand Rapids Labor Force Attachment | 517 | 25.7 | 18.7 | 7.0* | 0.18 |
| Grand Rapids Human Capital Development | 503 | 16.7 | 18.7 | -1.9 | -0.05 |
| Riverside Labor Force Attachment | 753 | 13.9 | 19.5 | -5.6** | -0.14 |
| Lacked high school diploma or basic skills | 422 | 11.7 | 19.6 | -7.9** | -0.19 |
| Riverside Human Capital Development | 484 | 11.2 | 19.6 | -8.4*** | -0.21 |
| Portland | 262 | 24.6 | 17.1 | 7.5 | 0.20 |
Ever dropped out of schoola |
|||||
| Atlanta Labor Force Attachment | 0 | 0.0 | 0.0 | 0.0 | 0.00 |
| Atlanta Human Capital Development | 0 | 0.0 | 0.0 | 0.0 | 0.00 |
| Grand Rapids Labor Force Attachment | 525 | 0.4 | 1.1 | -0.7 | -0.08 |
| Grand Rapids Human Capital Development | 512 | 0.0 | 1.1 | -1.2 | -0.14 |
| Riverside Labor Force Attachment | 760 | 0.7 | 1.5 | -0.8 | -0.06 |
| Lacked high school diploma or basic skills | 427 | 1.3 | 1.1 | 0.2 | 0.02 |
| Riverside Human Capital Development | 490 | 0.6 | 1.1 | -0.5 | -0.05 |
| Portland | 267 | 0.8 | 0.0 | 0.9 | 0.00 |
Attended a special class for physical, emotional, or mental conditionb |
|||||
| Atlanta Labor Force Attachment | 654 | 7.9 | 9.1 | -1.2 | -0.04 |
| Atlanta Human Capital Development | 699 | 6.4 | 9.1 | -2.6 | -0.09 |
| Grand Rapids Labor Force Attachment | 522 | 23.1 | 25.8 | -2.7 | -0.06 |
| Grand Rapids Human Capital Development | 507 | 19.6 | 25.8 | -6.2 | -0.14 |
| Riverside Labor Force Attachment | 755 | 13.2 | 13.5 | -0.3 | -0.01 |
| Lacked high school diploma or basic skills | 423 | 12.6 | 14.3 | -1.8 | -0.05 |
| Riverside Human Capital Development | 486 | 14.2 | 14.3 | -0.2 | -0.01 |
| Portland | 264 | 24.1 | 14.4 | 9.7 | 0.27 |
Had a physical, emotional, or mental condition that impeded on mother's ability to go to work or schoolb |
|||||
| Atlanta Labor Force Attachment | 655 | 4.4 | 3.3 | 1.0 | 0.06 |
| Atlanta Human Capital Development | 700 | 4.4 | 3.3 | 1.1 | 0.06 |
| Grand Rapids Labor Force Attachment | 529 | 10.9 | 12.7 | -1.9 | -0.06 |
| Grand Rapids Human Capital Development | 518 | 6.3 | 12.7 | -6.4** | -0.19 |
| Riverside Labor Force Attachment | 761 | 7.5 | 7.7 | -0.3 | -0.01 |
| Lacked high school diploma or basic skills | 428 | 5.4 | 7.1 | -1.8 | -0.07 |
| Riverside Human Capital Development | 490 | 6.4 | 7.1 | -0.7 | -0.03 |
| Portland | 267 | 14.0 | 12.9 | 1.1 | 0.03 |
Had a physical, emotional, or mental condition that required frequent medical attentionb |
|||||
| Atlanta Labor Force Attachment | 654 | 6.9 | 6.6 | 0.4 | 0.02 |
| Atlanta Human Capital Development | 700 | 4.4 | 6.6 | -2.2 | -0.09 |
| Grand Rapids Labor Force Attachment | 529 | 13.7 | 15.1 | -1.4 | -0.04 |
| Grand Rapids Human Capital Development | 518 | 9.7 | 15.1 | -5.4* | -0.16 |
| Riverside Labor Force Attachment | 761 | 8.9 | 8.0 | 0.9 | 0.03 |
| Lacked high school diploma or basic skills | 428 | 6.0 | 5.7 | 0.3 | 0.01 |
| Riverside Human Capital Development | 490 | 7.2 | 5.7 | 1.5 | 0.06 |
| Portland | 267 | 16.3 | 14.8 | 1.5 | 0.04 |
Ever had accident, injury, or poisoning that required an emergency room visit |
|||||
| Atlanta Labor Force Attachment | 652 | 14.2 | 14.2 | 0.0 | 0.00 |
| Atlanta Human Capital Development | 696 | 11.4 | 14.2 | -2.9 | -0.08 |
| Grand Rapids Labor Force Attachment | 524 | 18.4 | 22.4 | -3.9 | -0.09 |
| Grand Rapids Human Capital Development | 514 | 18.2 | 22.4 | -4.2 | -0.10 |
| Riverside Labor Force Attachment | 754 | 22.9 | 21.8 | 1.1 | 0.03 |
| Lacked high school diploma or basic skills | 426 | 23.0 | 18.8 | 4.2 | 0.11 |
| Riverside Human Capital Development | 486 | 12.8 | 18.8 | -6.0* | -0.15 |
| Portland | 262 | 24.3 | 24.1 | 0.2 | 0.00 |
Did not live with mother because she could not care for child |
|||||
| Atlanta Labor Force Attachment | 655 | 4.6 | 3.9 | 0.7 | 0.04 |
| Atlanta Human Capital Development | 699 | 3.6 | 3.9 | -0.3 | -0.02 |
| Grand Rapids Labor Force Attachment | 529 | 6.3 | 6.9 | -0.6 | -0.03 |
| Grand Rapids Human Capital Development | 518 | 6.5 | 6.9 | -0.4 | -0.02 |
| Riverside Labor Force Attachment | 759 | 10.8 | 6.8 | 4.0* | 0.15 |
| Lacked high school diploma or basic skills | 428 | 9.5 | 4.2 | 5.3** | 0.25 |
| Riverside Human Capital Development | 490 | 9.4 | 4.2 | 5.2** | 0.24 |
| Portland | 267 | 10.7 | 11.9 | -1.2 | -0.04 |
| SOURCE: MDRC calculations from the Five-Year
Client Survey. NOTES: See Appendix A.2. Standard errors have been adjusted to account for the presence of multiple siblings within a family. Owing to missing values, sample sizes may vary. a Measures whether the child dropped out of school at any point during the child's lifetime. b Refers to conditions that were current at the time the survey was administered. |
|||||
There are generally more effects than would be expected by chance for outcomes of young school-age children. Although effects are not consistent within domain, program approach, or site, two interesting general patterns emerge.
First, both Riverside programs increased the likelihood that young school-age children did not live with their mother because she could not care for them. The magnitude of this effect is also relatively large — almost doubling the likelihood (and effect sizes of 0.15 to 0.25). Both Riverside programs decreased suspensions and expulsions for young school-age children (though these effects are not supported by other measures that might be expected to be affected by a suspension or expulsion such as grade repetition or dropping out of school). It appears that the Riverside programs are producing favorable effects on one measure of academic functioning and, at the same time, increasing the likelihood of not living with a parent. One hypothesis is that a mother may have decided voluntarily to place her children in an alternative, perhaps temporary, living arrangement and this arrangement may have long-term benefits for the child's development. Or, alternatively, these effects may be capturing two different groups of children: those who experienced a decrease in grade repetition and those who were more likely to not live with their mother because she could not care for them.
Second, a pattern of favorable effects occurred for young school-age children in the Grand Rapids HCD program for seven of the eight outcome measures examined. These children were less likely to be suspended or expelled, less likely to drop out of school (approached statistical significance at p = .14), less likely to have attended a special class (approached statistical significance at p = .14), less likely to have had a condition that demands a lot of attention, and less likely to have had a condition that demands frequent medical attention.(25)
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Impacts are smaller and more negative in Atlanta and Grand Rapids, similar in Riverside, and more positive in Portland for survey sample respondents of adolescents (aged 10 or over at time of study entry), than for the client survey sample.(26) The effect of mothers' employment may be particularly pronounced for adolescents by, for example, providing a positive role model and encouraging adolescents to prepare for the labor force as young adults. In addition, adolescents in low-income families may take on additional responsibilities at home, such as chores, or may engage in their own employment to help support their family. These activities could have either positive or negative consequences for adolescent outcomes. Finally, adolescents might be harmed by mothers' increased employment because it may translate to lack of supervision during a time when many may initiate risk-taking behaviors. On the other hand, supervised and high-quality out-of-school programs may have particularly beneficial effects for adolescents.(27)
Outcomes and impacts for children who were adolescents at study entry (aged 15 to 23 at the five-year follow-up), are shown in Table 11.6. Rates of grade retention during the last three years of follow-up varied considerably across sites among adolescents in the control group, from 4 percent in Portland and Riverside to 17 percent in Atlanta. Dropout rates also varied considerably, from 17 percent in Riverside to 31 percent in Portland. These dropout rates are higher than the dropout rates of 10th to 12th graders for a national sample of 15-to -24-year olds in families at the bottom 20 percent of income levels.(28) Approximately 15 to 23 percent of adolescents in the control group were ever suspended or expelled during the last three years of follow-up. Unsurprisingly, these rates of grade retention, suspensions and expulsions, and dropping out are considerably higher for adolescents than for younger children.
Site and Program |
Sample Size | Program Group (%) | Control Group (%) | Difference (Impact) | Effect Size |
|---|---|---|---|---|---|
Ever repeated a grade |
|||||
| Atlanta Labor Force Attachment | 834 | 15.2 | 17.2 | -1.9 | -0.05 |
| Atlanta Human Capital Development | 938 | 15.5 | 17.2 | -1.6 | -0.04 |
| Grand Rapids Labor Force Attachment | 890 | 11.7 | 7.5 | 4.2** | 0.16 |
| Grand Rapids Human Capital Development | 919 | 11.8 | 7.5 | 4.3** | 0.16 |
| Riverside Labor Force Attachment | 1126 | 7.1 | 4.2 | 2.9** | 0.14 |
| Lacked high school diploma or basic skills | 638 | 7.0 | 4.3 | 2.8 | 0.13 |
| Riverside Human Capital Development | 657 | 8.2 | 4.3 | 3.9** | 0.18 |
| Portland | 406 | 5.6 | 4.4 | 1.2 | 0.06 |
Ever suspended or expelled |
|||||
| Atlanta Labor Force Attachment | 836 | 16.3 | 23.2 | -6.8** | -0.16 |
| Atlanta Human Capital Development | 938 | 21.3 | 23.2 | -1.9 | -0.05 |
| Grand Rapids Labor Force Attachment | 891 | 21.3 | 20.0 | 1.3 | 0.03 |
| Grand Rapids Human Capital Development | 924 | 18.2 | 20.0 | -1.8 | -0.05 |
| Riverside Labor Force Attachment | 1120 | 15.4 | 15.0 | 0.3 | 0.01 |
| Lacked high school diploma or basic skills | 634 | 13.3 | 16.6 | -3.3 | -0.09 |
| Riverside Human Capital Development | 652 | 17.5 | 16.6 | 0.9 | 0.02 |
| Portland | 395 | 16.9 | 18.6 | -1.7 | -0.04 |
Ever dropped out of schoola |
|||||
| Atlanta Labor Force Attachment | 836 | 22.8 | 24.1 | -1.3 | -0.03 |
| Atlanta Human Capital Development | 937 | 26.1 | 24.1 | 2.0 | 0.05 |
| Grand Rapids Labor Force Attachment | 899 | 29.5 | 26.0 | 3.5 | 0.08 |
| Grand Rapids Human Capital Development | 934 | 29.1 | 26.0 | 3.1 | 0.07 |
| Riverside Labor Force Attachment | 1122 | 18.5 | 17.9 | 0.6 | 0.01 |
| Lacked high school diploma or basic skills | 635 | 18.2 | 17.3 | 0.9 | 0.02 |
| Riverside Human Capital Development | 657 | 22.8 | 17.3 | 5.4* | 0.14 |
| Portland | 409 | 36.4 | 31.2 | 5.2 | 0.11 |
Attended a special class for physical, emotional, or mental conditionb |
|||||
| Atlanta Labor Force Attachment | 835 | 5.0 | 4.4 | 0.6 | 0.04 |
| Atlanta Human Capital Development | 939 | 3.9 | 4.4 | -0.4 | -0.02 |
| Grand Rapids Labor Force Attachment | 894 | 11.5 | 8.5 | 3.0 | 0.10 |
| Grand Rapids Human Capital Development | 928 | 11.0 | 8.5 | 2.5 | 0.09 |
| Riverside Labor Force Attachment | 1128 | 7.3 | 5.0 | 2.2 | 0.10 |
| Lacked high school diploma or basic skills | 640 | 7.5 | 3.9 | 3.6* | 0.18 |
| Riverside Human Capital Development | 660 | 6.9 | 3.9 | 3.0* | 0.15 |
| Portland | 407 | 8.0 | 6.4 | 1.6 | 0.06 |
Had a physical, emotional, or mental condition that impeded on mother's ability to go to work or schoolb |
|||||
| Atlanta Labor Force Attachment | 836 | 2.3 | 3.0 | -0.7 | -0.04 |
| Atlanta Human Capital Development | 939 | 2.9 | 3.0 | -0.1 | -0.00 |
| Grand Rapids Labor Force Attachment | 900 | 5.7 | 3.9 | 1.8 | 0.09 |
| Grand Rapids Human Capital Development | 943 | 4.3 | 3.9 | 0.4 | 0.02 |
| Riverside Labor Force Attachment | 1133 | 3.4 | 3.2 | 0.2 | 0.01 |
| Lacked high school diploma or basic skills | 644 | 2.8 | 3.1 | -0.2 | -0.01 |
| Riverside Human Capital Development | 663 | 6.2 | 3.1 | 3.1* | 0.17 |
| Portland | 409 | 4.5 | 2.6 | 1.8 | 0.10 |
Had a physical, emotional, or mental condition that required frequent medical attentionb |
|||||
| Atlanta Labor Force Attachment | 835 | 5.3 | 4.6 | 0.6 | 0.03 |
| Atlanta Human Capital Development | 939 | 3.8 | 4.6 | -0.8 | -0.04 |
| Grand Rapids Labor Force Attachment | 899 | 6.6 | 4.3 | 2.3 | 0.11 |
| Grand Rapids Human Capital Development | 941 | 4.7 | 4.3 | 0.4 | 0.02 |
| Riverside Labor Force Attachment | 1134 | 3.4 | 6.3 | -2.8** | -0.12 |
| Lacked high school diploma or basic skills | 644 | 2.8 | 5.4 | -2.6* | -0.11 |
| Riverside Human Capital Development | 664 | 3.8 | 5.4 | -1.6 | -0.07 |
| Portland | 409 | 4.5 | 4.9 | -0.4 | -0.02 |
Ever had accident, injury, or poisoning that required an emergency room visit |
|||||
| Atlanta Labor Force Attachment | 822 | 10.8 | 12.0 | -1.2 | -0.04 |
| Atlanta Human Capital Development | 921 | 11.8 | 12.0 | -0.2 | -0.01 |
| Grand Rapids Labor Force Attachment | 873 | 14.1 | 17.4 | -3.2 | -0.09 |
| Grand Rapids Human Capital Development | 910 | 17.3 | 17.4 | -0.1 | -0.00 |
| Riverside Labor Force Attachment | 1104 | 15.1 | 16.9 | -1.8 | -0.05 |
| Lacked high school diploma or basic skills | 628 | 10.8 | 13.3 | -2.5 | -0.07 |
| Riverside Human Capital Development | 648 | 15.9 | 13.3 | 2.6 | 0.08 |
| Portland | 397 | 23.5 | 20.1 | 3.4 | 0.09 |
Did not live with mother because she could not care for child |
|||||
| Atlanta Labor Force Attachment | 836 | 4.3 | 3.9 | 0.4 | 0.02 |
| Atlanta Human Capital Development | 937 | 4.1 | 3.9 | 0.2 | 0.01 |
| Grand Rapids Labor Force Attachment | 900 | 3.8 | 4.6 | -0.9 | -0.04 |
| Grand Rapids Human Capital Development | 943 | 6.4 | 4.6 | 1.7 | 0.08 |
| Riverside Labor Force Attachment | 1134 | 8.1 | 5.4 | 2.7* | 0.12 |
| Lacked high school diploma or basic skills | 644 | 7.7 | 4.8 | 2.9 | 0.13 |
| Riverside Human Capital Development | 664 | 3.3 | 4.8 | -1.5 | -0.07 |
| Portland | 409 | 7.9 | 10.1 | -2.2 | -0.08 |
Ever had a baby as a teenc |
|||||
| Atlanta Labor Force Attachment | 829 | 16.9 | 21.3 | -4.5 | -0.11 |
| Atlanta Human Capital Development | 936 | 22.3 | 21.3 | 0.9 | 0.02 |
| Grand Rapids Labor Force Attachment | 893 | 19.6 | 19.7 | -0.2 | -0.00 |
| Grand Rapids Human Capital Development | 923 | 20.6 | 19.7 | 0.8 | 0.02 |
| Riverside Labor Force Attachment | 1123 | 15.4 | 13.0 | 2.4 | 0.07 |
| Lacked high school diploma or basic skills | 637 | 19.4 | 13.2 | 6.2** | 0.18 |
| Riverside Human Capital Development | 658 | 16.9 | 13.2 | 3.7 | 0.11 |
| Portland | 399 | 13.8 | 17.2 | -3.4 | -0.10 |
| SOURCE: MDRC calculations from the Five-Year
Client Survey. NOTES: See Appendix A.2. Standard errors have been adjusted to account for the presence of multiple siblings within a family. Owing to missing values, sample sizes may vary. a Measures whether the child dropped out of school at any point during the child's lifetime. b Refers to conditions that were current at the time the survey was administered. c Measures whether the child had a baby while a teenager at any point during the five-year follow-up period. |
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One important outcome for adolescents, especially for female adolescents, is teen childbearing, which is correlated with a decreased likelihood of completing schooling and of succeeding in the labor market and an increased likelihood of receiving public assistance. Furthermore, being raised by a teen mother may have negative consequences on children's development.(29) Approximately 13 to 21 percent of adolescents in the NEWWS sample ever had a baby as a teen.(30) These rates are slightly lower when the sample of adolescents is restricted to those aged 10 or over at random assignment but under age 19 at the five-year follow-up (7 to 15 percent; not shown). These are double the national rates, though much of the difference is likely due to the fact that the national figures are not restricted to a low-income or welfare sample.(31) The national birth rate in 1998 for teens aged 15 to 19 was 5 percent.(32) In 1997, teen birth rates for females aged 15 to 19 were 5.7 percent in California, 6.7 percent in Georgia, 4.4 percent in Michigan, and 4.7 percent in Oregon.(33)
The welfare-to-work programs examined in this chapter produced the most effects on outcomes for adolescents. The effects were generally unfavorable in the Grand Rapids and Riverside programs, especially the Riverside HCD program. Both programs in Grand Rapids and both programs in Riverside increased grade repetition by 3 percentage points (Riverside LFA) to 4 percentage points (Grand Rapids HCD). These unfavorable impacts are of concern because children who repeat a grade in high school may be more likely to drop out of school and, as previously noted, completed education is highly correlated with future labor force participation.
In addition to increasing grade repetition, the Riverside HCD program increased the likelihood that an adolescent would drop out of school, increased the percentage of adolescents who attended a special class because of a physical, emotional, or mental condition, and increased the percentage who had a physical, emotional, or mental condition that demanded a lot of the respondents' time. It also increased the percentage of adolescents who were teen parents, an effect that approached statistical significance (p = .18).
Similar unfavorable effects were not found in Atlanta or in Portland. In fact, the Atlanta LFA program decreased suspensions or expulsions by almost 7 percentage points and decreased teenage childbearing by nearly 5 percentage points (with the latter effect approaching statistical significance at p = .11).
Comparisons of NEWWS effects with effects found in other recent studies are discussed in the accompanying text box.
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The earlier sections began with hypotheses about how targeted outcomes of welfare-to-work programs, such as income and employment, may affect child well-being, and then discussed impacts on child outcomes. This section expands this discussion and hypothesizes ways in which actual program practices or program effects may have led to effects on child outcomes. A complete analysis of all the ways that a program may have affected or generated changes in child outcomes is beyond the scope of this chapter. However, comparing or "lining up" impacts on outcomes presented and discussed in earlier chapters with impacts on child outcomes can reveal potential effects on children. With this in mind, this section additionally discusses impacts on several other outcomes, including characteristics of employment, household composition, and home ownership for mothers of these children (not shown).
Comparing NEWWS Adolescent Findings With Those of Other Recent Studies Recently released studies have documented some unfavorable effects of welfare and employment policy on the outcomes for adolescents. It was found that the Canadian Self-Sufficiency Project (SSP), a program that increased full-time employment and income, had no effect on major delinquency or academic functioning outcomes but did increase minor delinquency and tobacco, alcohol, and drug use among adolescents.a Florida's Family Transition Program (FTP), one of the first that evaluated the effects of a time limit, also found some scattered evidence that adolescents in the program group fared more poorly on a couple of schooling outcomes than adolescents in the control group.b Furthermore, additional analyses of data from New Hope, a program in Milwaukee that offered an earnings supplement and more generous child care and health care benefits for full-time low-income workers, found that New Hope had unfavorable effects on some measures of academic functioning.c The Minnesota Family Investment Program also produced negative effects on academic functioning outcomes of children aged 10 or over at study entry of recent applicants, although this pattern was generally not found for adolescents of long-term welfare recipients.d Three of these studies (FTP, New Hope, and SSP) examined adolescents who were approximately aged 9 to 15 at the time of study entry, and under age 19 at the time of interview. To draw a more precise comparison of the effects of the welfare-to-work programs examined in this report with these former studies, impacts on adolescents were rerun for a similar age cohort. In general, the unfavorable effects found for the full adolescent sample in Grand Rapids and Riverside were also found for the restricted sample of adolescents. However, notably, as was the case for the full sample, no effects were found on these outcomes for the adolescent samples in Atlanta and Portland. Although confidence in these emerging findings could be bolstered by better and broader measures of adolescent development and larger samples, they do provide some consistent evidence that welfare and employment programs may negatively affect some adolescent children. Why these unfavorable effects are occurring in some sites and programs but not in others, in some domains of development but not in others, and whether or not the observed unfavorable effects will result in long-term difficulties as adolescents move into adulthood are especially important issues for further research.
a Morris and Michalopoulos, 2000. |
Fewer differences than would be expected by chance were found in the effects on child outcomes of the LFA program approach compared with the HCD program approach for each of the child age groups.(34) This suggests that children, ranging in age from toddlers to adolescents, were not affected differently by education-focused programs than by employment-focused programs for the outcomes examined in this chapter.
Both Grand Rapids programs increased mothers' employment but decreased average income from earnings and welfare benefits for mothers of toddlers at study entry. The general pattern of impacts on toddlers suggests that the children in these families were faring as well as, if not doing better than, their control group counterparts. A review of impacts on characteristics of employment, income, and child care assistance suggests some ways in which toddlers may have been affected. This review suggests that the reduced hours of work and, possibly, the use of higher-quality child care, and not decreased income, among program group members compared with control group members in Grand Rapids may have contributed to the pattern of effects on outcomes for toddlers.
A closer look at the impacts on hours of employment for these mothers shows that the Grand Rapid's programs increased part-time employment (and decreased full-time employment) during the most recent or current job. In fact, fewer hours worked may be what contributed to lower income for these mothers. They were also significantly more likely to be in jobs with rotating hours and to use child care after leaving welfare because of earnings. In contrast, the Portland program increased both full-time and part-time employment and similar effects on child care use were not found. Field notes also suggest that caseworkers in Grand Rapids had more leeway in administering reimbursement of child care costs (that is, payments were allocated in advance or retroactively), and one adult education center that operated the program's job clubs as well as providing some educational activities used by NEWWS sample members provided on-site child care. These differences may have influenced the quality of care used (for example, if on-site child care was of higher quality). Neither of these circumstances existed in Portland. Finally, there was a general pattern of decreased income in both Grand Rapids programs and the Portland program, suggesting that decreased income, on its own, is not a likely way in which toddlers were affected.
Both programs in Riverside produced larger employment effects for mothers of adolescents than programs in the other sites. As mentioned above, the Riverside programs also produced unfavorable effects on the academic outcomes of adolescents. One possible explanation is that as mothers' employment increased, especially full-time employment, adolescents were less likely to be supervised, giving them more freedom to engage in risk-taking behaviors. Closer inspection of the employment impacts shows that the Grand Rapids and Riverside programs similarly had larger employment effects during the first year of the follow-up than the Atlanta and Portland programs. Unfortunately, actual measures of supervision were not collected in the survey. Nonetheless, unfavorable academic outcomes during the last few years of the follow-up period may be associated with the extent of mothers' employment early in the follow-up period.
A review of effects on other important family outcomes such as income and family structure suggests that there are other possible reasons why adolescents fared poorly on academic outcomes because of these welfare-to-work programs, especially since nearly all of the programs increased employment but did not produce similarly unfavorable effects on adolescent outcomes. Mothers in the Grand Rapids and Riverside programs also experienced decreased income from earnings and welfare benefits during the last three years of the follow-up period. Adolescents may have taken on more responsibility contributing to household resources, increasing their own employment in response to having less income in the household. Employment during adolescence, particularly if it is more than 20 hours per week, is associated with difficulty in school.(35) In addition, and interestingly, the two programs that produced the most unfavorable effects on adolescents — the Grand Rapids LFA program and the Riverside HCD program — also increased the likelihood that these adolescents' mothers were married and living with a spouse at the five-year follow-up point (not shown). Adolescent children are especially vulnerable to family changes, such as separation, divorce, and marriage.(36)
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This chapter examined the effects of these welfare-to-work programs on child outcomes. In general few, if any, effects were found. Most program effects did not vary by program approach. Employment-focused programs and education-focused programs generally generated similar effects. Program effects generally were not concentrated by site, even with the caveat that differences between program and control groups were not as distinct by the final year of follow-up in Atlanta and Grand Rapids. Portland, in particular, produced few effects, though this was not completely surprising since impacts on employment and other economic outcomes were less positive for the client survey sample than for the full impact sample. Atlanta appeared to produce fewer unfavorable effects than the other sites, especially Grand Rapids and Riverside.
The effects found were primarily clustered by age. First, with data on few outcomes in two sites, these welfare-to-work programs produced no unfavorable effects on the outcomes of children who were toddlers at study entry (aged 6 and 7 at the five-year follow-up). The lack of more unfavorable effects for toddlers is somewhat contrary to what has been found in nonexperimental research that suggests mothers' employment during the first few years of a child's life produces unfavorable results. Fewer hours of employment, part-time work versus full-time work, or the quality of child care arrangements may partially explain why. Second, as has been found in the effects of other experimental welfare and employment policies, these welfare-to-work programs produced unfavorable effects on the outcomes of children who were adolescents at study entry (aged 15 to 23 at the five-year follow-up), especially on academic functioning. The unfavorable effects found for adolescents may be associated with lack of supervision, decreased income in the household, or changes in family composition. In any case, it is the well-being of these children that perhaps should be more closely monitored when mothers are required to participate in welfare-to-work programs.
1. This chapter presents program impacts on selected outcomes for all client survey respondents' children aged 3 to 5. See Chapter 12 for more detail about how the Child Outcomes Study (COS) sample differs from this sample.
2. For example, while research generally shows better cognitive and behavioral outcomes for children in formal child care settings (NICHD Early Child Care Research Network, 2000; Zaslow et al., 1998), studies have also linked attendance in larger child care settings with greater ear infections, with detrimental effects on hearing loss and language development more likely to occur in low-quality settings (Vernon-Feagans, Emanuel, and Blood, 1997). Thus, mothers' involvement in welfare-to-work programs that leads to increased use of large, formal settings for their young children may benefit their cognitive and behavioral development but adversely affect their health. In addition, any one program may have different effects on child outcomes, and these effects may reinforce or cancel each other out. For example, any beneficial effect of mothers' increased employment may be attenuated by any declines in income.
3. See McGroder et al., 2000; Hamilton et al., 2000; Zaslow et al., 1998, 1995.
4.For various reviews about the effects of income on children's outcomes see Duncan and Brooks-Gunn, 1997; Harvey, 1999; Hoffman and Youngblade, 1999; Mayer, 1997; Moore and Driscoll, 1997; Vandell and Ramanan, 1992; and Zaslow et al., 1999a. Some argue that Tthe effects of family income may also depend on the source of income, though many studies find no relation between welfare receipt and children's development controlling for demographic and family characteristics (for example, Haveman and Wolfe, 1995; Levine and Zimmerman, 2000; Yoshikawa, 1999). [Is this really true? I thought that this notion had lost a lot of currency lately, i.e., that welfare dollars were not worth as much as other dollars..
5. McGroder, 2000.
6. See, for example, the "stress hypothesis" proposed by Brooks-Gunn and Berlin, 1993. See also Zaslow et al., 1995.
7. Lamb, 1998; Phillips et al., 1994; Zaslow, 1991.
8. Survey respondents may have children who fall into one or more age groups; for example, a respondent may have a preschool-age child and a young school-age child at study entry. For this reason, survey impacts on economic outcomes for the mothers of children in various age groups do not necessarily reflect effects on mutually exclusive groups.
9. Families with children in different age groups may also differ in other ways. For example, respondents with adolescent children are more likely to be older, more likely to have been ever married, less likely to have a high school diploma or a GED, and more likely to be a longer-term recipient of welfare than respondents with younger children. Program impacts may instead reflect other characteristics of these respondents. Conditional subgroup impact analysis, which would test whether or not age of children or other characteristics explain program impacts, is beyond the scope of work for this chapter.
10.In general, there were a greater number of statistically significant findings than expected by chance alone overall and by each of the child age groups. See Chapter 2 for a more detailed description of the standard used to determine the likelihood of chance findings.
11.All standard errors in the impact analysis were adjusted so that the impact estimates account for the presence of two or more children or siblings within a family.
12.Mothers with children under age 3, or as young as age 1 in some sites, were exempt from participation in mandatory services. These mothers were also excluded from being part of NEWWS. However, because the child age groups were created based on information gathered at the five-year survey point, it is possible that some survey respondents provided information about infants (for example, an infant could have joined the household after random assignment through marriage or foster care). Consequently, though the majority of the toddlers group is composed of children aged 1 and 2 at the time of random assignment, 4.7 percent of these children were under age 1.
13.Detailed information about a subset of children aged 3 to 5 in the Child Outcomes Study includes child outcomes as evaluated by the mother, a teacher, and the child. See the discussion in Chapter 12 about ways in which mothers' and children's reports may differ. The New Chance and New Hope evaluations also found that mothers' reports of children's behavior and academic performance differed from teachers' reports of these outcomes (Quint, Bos, and Polit, 1997; Bos et al., 1999).
14.Freeman and Blanchflower, 1999.
15.Baydar and Brooks-Gunn, 1991.
16.Morris and Michalopoulos, 2000.
17.U.S. Department of Education, 2001.
18.Some examples include MFIP (Gennetian and Miller, 2000), SSP (Morris and Michalopoulos, 2000), and FTP (Bloom et al., 2000a).
19.Compared with the client survey sample, the Grand Rapids LFA program decreased earnings (though not significant) in year 5 and the Grand Rapids HCD program had no employment effect during the first year of follow-up.
20.Some, though not all, of this difference is due to lower control group levels in the sample of respondents with a preschool-age child at study entry.
21.Morris et al., 2001.
22.Duncan and Brooks-Gunn, 1997.
23.U.S. Department of Education, 2001.
24.U.S. Department of Education, 2001.
25.A third interesting pattern emerged in Portland. Portland increased suspensions and expulsions and ever attending a special class among young school-age children (though not statistically significant at conventional levels). These differences are of a similar magnitude, small to medium, as has been found in comparable experimental studies (0.2 to 0.3 effect size). The sample size of young school-age children in Portland was relatively small.
26.Compared with the client survey sample, survey sample members with adolescents had a negative pattern of employment effects, small to no significant earnings gains and a negative though not significant effect on cumulative combined income in the Atlanta LFA program; smaller and no significant effect on cumulative earnings in the Atlanta HCD program; smaller cumulated earnings effects and larger decreased cumulative combined income in the Grand Rapids LFA program; significant decreased cumulative combined income in the Grand Rapids HCD program; and slightly larger and more positive employment effects in Portland.
27.Petit et al., 1999; Posner and Vandell, 1994.
28.U.S. Department of Education, 2001.
29.Moore et al., 1993.
30.This measure includes both males and females.
31.Some of the discrepancy could also be due to the inclusion of teen births to males and females in the NEWWS sample.
32.Brown et al., 1999.
33.Child Trends, December 2000.
34.Although the number of significant differences between HCD and LFA outcome levels did not exceed chance for each of the child age groups, two interesting patterns did emerge for young school-age children and adolescents. For young school-age children, the Grand Rapids HCD outcome levels were lower than LFA outcome levels for suspensions and the likelihood of having a physical, emotional, or mental condition that demanded a lot of mothers' time; and the Riverside HCD outcome levels were lower than LFA outcome levels for emergency room visits. For adolescents, the Atlanta LFA outcome levels were lower than HCD outcome levels for suspensions and the likelihood of having a baby while a teen; and the Riverside LFA outcome levels were lower than HCD outcome levels for emergency room visits and the likelihood of having a physical, emotional, or mental condition that demanded a lot of mothers' time. These patterns are interesting in that they suggest that the type of activity that a mother is first required to participate in may have influences on child outcomes that vary by age of the child. For example, an education-focused programs may give mothers more flexibility to better manage their time between participation requirements and their children's need for supervision than an employment-focused program. In contrast, adolescents may benefit more from having a mother engaged in an employment-focused program than an education-focused program because of the role modeling that mothers in full-time employment provide.
35.Mortimer et al., 1996, and Steinberg and Dornbusch, 1991.
36.McLanahan, 1997.
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