Almost all children of WtW enrollees were covered by public or private health insurance at the one-year follow-up point, but coverage for the enrollees themselves was markedly spottier. Coverage rates for children were 95 percent or higher in seven of the study sites and were no less than 85 percent in the other four sites (Exhibit V.10).(69) Most of the enrollees in Milwaukee were not receiving TANF and therefore were unlikely to qualify for Medicaid; consequently, only one-third of them were covered by health insurance. In two other sites Baltimore County and Ft. Worth somewhat less than three-fourths of enrollees were covered by health insurance one year after they entered WtW. In contrast, the coverage rate for enrollees exceeded 90 percent in Boston, Nashville, and Philadelphia and was just short of that threshold in Chicago.(70)
Percentage of WtW Enrollees Who Received Assistance from Support Networks During the Year after Program Entry
Percentage of WtW Enrollees Who Were Receiving Assistance
from Government Programs One Year after Program Entry
Percentages of WtW Enrollees Who Were Receiving TANF
at the Time of Program Entry and One Year Later
Employment and Receipt of TANF by WtW Enrollees One Year after Program Entry
Mean Monthly Household Income of WtW Enrollees,
by Source, One Year after Program Entry
Incidence of Household Poverty among WtW Enrollees One Year after Program Entry
Mean Value of Index of Material Distress Experienced by WtW Enrollees
And Their Households During the Year after Program Entry
Incidence of Household Poverty among WtW Enrollees,
by Employment Status, One Year after Program Entry
Percentages of WtW Enrollees Who Experienced Two Forms of Homelessness
During the Year after Program Entry
Percentages of WtW Enrollees and Their Children Who Were Covered by Health Insurance
One Year after Program Entry
56. For example, the JHU sites in Baltimore County and St. Lucie County primarily served persons who were already working at the time of enrollment, whereas the other nine study sites targeted persons who were not working. Based on this difference in targeting strategies alone, we would expect enrollees in the JHU sites to be doing better, on average, than enrollees in the other sites one year after program entry.
57. The evaluation's 12-month follow-up survey gathered information on help received from family and friends in the form of transportation, use of a telephone, a place to stay, groceries or meals, children's things, and money. It also gathered information on help received from the following community organizations: food pantry or soup kitchen, crisis hotline or center, thrift shop, and church. See Appendix Exhibit B.15 for details.
58. The 12-month follow-up survey explicitly inquired about the receipt of income from seven government programs: food stamps, TANF, Supplemental Security Income or Disability Insurance, Social Security retirement or survivors benefits, Unemployment Insurance, General Assistance, and foster care or adoption assistance. Some respondents reported assistance from other government programs and that was also included in this analysis.
59. The analysis of assistance from government programs included programs for which we were able to conveniently measure both the receipt and the dollar value of benefits. Measurement of the value of public housing would have been problematic in the 12-month follow-up survey. Consequently, we did not attempt to gather information on the dollar value of either public housing or Section 8 housing subsidies in the survey. If housing assistance (public housing and Section 8 subsidies) had been included in the analysis of recipiency, it would have been the first or second most common form of government assistance in five sites and the third or fourth most common in six sites. Appendix Exhibit B.18 reports rates of receipt of housing assistance ranging from 5 percent in Milwaukee to 78 percent in Boston.
60. Many of the Milwaukee enrollees were incarcerated at the time of enrollment and consequently prohibited from receiving TANF. During the ensuing year, most left prison or jail and a few joined existing TANF units or formed new units, causing the TANF receipt rate to rise from 1 to 6 percent.
61. Milwaukee where the NOW program had a distinctive focus on ex-offenders/noncustodial parents presents the sharpest deviation from the pattern of greater welfare dependency than self-sufficiency. Also, in West Virginia and Yakima more enrollees were employed and off of TANF than were on TANF and not working.
62. The measure of total income reported here includes the value of food stamp benefits.
63. To be consistent with the standard methodology for determining poverty status, food stamps were excluded from the measure of household income for the poverty analysis.
64. The value of the index of material distress was computed for an enrollee by adding up the number of affirmative responses to the questions regarding the presence of the five types of material distress and dividing by the number of valid responses. If all five types of distress were experienced, the index took on its maximum value of 1; if only one type was experienced, it took on a value of 0.2 (assuming valid responses to all five questions); and if no type of distress was experienced, the index took on its minimum value of 0.
65. The design for the index of material distress closely resembles that for the "index of material hardship," which was used in several random-assignment evaluations of state welfare-reform initiatives in the 1990s (Bloom et al. 2002, Fraker et al. 2002, and Miller et al. 2000). However, two of seven specific types of distress, both reflecting failure to see a health care professional when needed, were omitted from the index in this study. Those two types of distress were instead included in this study's index of health-related distress (Appendix Exhibit B.22).
66. Appendix Exhibit B.23 shows that poverty status differed significantly by employment status, but the mean value of the index of material distress did not in five of the study sites (Ft. Worth, Milwaukee, Nashville, Philadelphia, and Phoenix). Both measures differed significantly by employment status in only four of the sites (Baltimore County, Boston, Chicago, and Yakima).
67. Enrollees who experienced one of the two forms of homelessness often experienced the other form as well. Consequently, in most sites the overall incidence of homelessness was substantially less than the sum of the two rates. The overall rates of homelessness are presented in Appendix Exhibit B.22.
68. Rates of homelessness were not consistently high in sites where rates of participation in government housing programs (receipt of housing subsidies or residence in public housing) were low. Exhibit B.18 shows that, across the 11 study sites, Boston had the highest rate of participation by WtW enrollees in government housing programs, while St. Lucie and West Virginia were among the four sites with the lowest rates of participation in government housing. Yet Exhibit V.9 shows high rates of homelessness in Boston and low rates in St. Lucie County and in West Virginia. On the other hand, enrollees in Milwaukee rarely participated in government housing programs but they had relatively high rates of homelessness.
69. The health insurance coverage rate for children was high over the entire one-year follow-up period, except in three sites 2 in 10 enrollees in Baltimore County and Phoenix and 3 in 10 enrollees in Ft. Worth had at least one child for whom there was a lapse in health insurance coverage sometime during the follow-up period (Appendix Exhibit B.25).
70. Consistent with their generally high levels of health insurance coverage, WtW enrollees and their families did not experience much health-related distress over the evaluation's one-year follow-up period. The mean value of an index summarizing three types of health-related distress ranged from 0.20 to 0.29 in eight of the study sites (Appendix Exhibit B.22). This was indicative of less than one type of distress, on average. The mean value of the index was below 0.20 in Boston, Chicago, and Philadelphia, where health insurance coverage rates were especially high.