National Evaluation of the Welfare-to-Work Grants Program: Final Report. Endnotes

09/01/2004

(50) In Milwaukee and Philadelphia, where rates of receipt of assistance from community organizations were especially low during the first year after program entry, WtW enrollees experienced little or no erosion in such support during the second year.

(51) The government assistance programs considered in this study are: TANF, food stamps, SSI or SSDI, Social Security retirement or survivors benefits, unemployment insurance benefits, general relief or general assistance, foster care or adoption assistance, and other assistance (including workers compensation and veterans benefits but not housing or medical assistance). Appendix Exhibit B.11 presents findings on the receipt and amounts of these types of assistance.

(52) The discussion of TANF and food stamp receipt is based on data for early WtW enrollees rather than all enrollees. This is because in 10 of the study sites, a full 8 quarters of post-entry data are available only for early enrollees, whereas only six or fewer quarters of post-entry data are available for all enrollees. Early enrollees are defined as those who entered WtW prior to July 1, 2000. Chicago is the only study site in which there were no early enrollees; consequently, it is the one site for which less than 8 quarters of post-entry administrative data are available. The 4 quarters of post-entry results shown in Exhibit V.3 for Chicago are based on all WtW enrollees. Among all of the study sites, in those quarters for which administrative data are available for all enrollees as well as early enrollees, quarter-specific TANF participation rates are generally quite similar between the two groups, as shown in Appendix Exhibits D.2.a and D.2.b. This is especially true for the latest of those quarters, typically Quarters 4 through 6. Thus, we believe that our decision to focus on results for early enrollees does not distort the conclusions that we draw from these data.

(53) The relative change in the rate of TANF receipt over the two years following WtW program entry is defined as the change in the rate of receipt between Quarter 0 and Quarter 8, divided by the rate of receipt in Quarter 0 and expressed as a percentage. All percentage changes reported in this section have been calculated in this manner.

(54) The results for Chicago are based on the four quarters of post-entry administrative data that were available to this study.

(55) State administrative data for all families receiving TANF in the study sites were not available for Boston and Milwaukee.

(56) From fiscal year 2000 to June 2003, the average monthly number of individuals receiving TANF nationwide fell by 17 percent (Committee on Ways and Means of the U.S. House of Representatives 2004; DHHS 2004) while the number receiving food stamps rose by 27 percent (USDA 2004). We would not expect patterns of receipt by cohorts of individuals or families, such as those who participated in the WtW evaluation, to mirror these caseload trends. However, the caseload trends do provide supportive context for our finding that the receipt of TANF by WtW enrollees fell relative to the receipt of food stamps.

(57) This is consistent with the evaluation teams observation site visits to local TANF offices under this and other studies that many TANF agencies were making efforts to identify individuals on their caseloads who were close to exhausting their TANF five-year limit and might qualify for SSI or SSDI and to help them with their applications.

(58) The measure of income reported here is for the month prior to the month in which the 24-month survey interview was completed. It includes cash income of all types (the enrollees own earnings, earnings of other household members, cash benefits from government programs, and any other cash income), plus food stamps, received by all members of the enrollees household. See Appendix Exhibit B.16 for additional details on the calculation of total household income.

(59) The study sample size in Milwaukee was 276, of whom 195 responded to the 12-month follow-up survey and 190 responded to the 24-month follow-up survey. See Appendix F of this report and Appendix C of Fraker et al. 2004 for additional details on this studys survey data collection.

(60) Loprest (2001) based her analysis on the 1999 wave of the National Survey of Americas Families. To be included in that analysis, families had to have left TANF sometime during the two years prior to the survey interview and to have not been receiving TANF at the time of the interview. Seventy-nine percent of these families included at least one parent who was employed at the time of the interview.

(61) To be consistent with the Census Bureaus methodology for determining poverty status, we excluded food stamps from the previously-described measure of income (see footnote 58) for the purpose of the poverty analysis. For the same reason, we did not factor payroll taxes, income taxes, or the EITC into the poverty analysis.

(62) Elsewhere in this report, employment is defined as working on a job for pay at the time of the survey interview. However, to obtain a consistent reference period for earnings and employment in the analysis of poverty by employment status, employment here is defined as positive enrollee earnings in the month prior to the survey interview (the month for which income data were reported). This definition ensures that there are no employed enrollees without earnings in the analysis of poverty by employment status. If such individuals had been included in the analysis, they would have tended to exaggerate the poverty rate among employed enrollees.

(63) We simulated household poverty rates for employed enrollees under the assumptions of: (1) no income from government programs (including the EITC), (2) the enrollees actual earnings in the month prior to the month of the survey interview, and (3) whatever other income their households actually received in that month. The simulated poverty rates are as follows (in percentages): Baltimore County 51, Boston 60, Chicago 74, Ft. Worth 62, Milwaukee 41, Nashville 74, Philadelphia 81, Phoenix 63, St. Lucie County 62, West Virginia 81, and Yakima 60. We then repeated the simulation, but replaced the enrollees actual earnings with earnings calculated on the basis of the usual weekly hours of work on the principal job held at the time of the survey interview, the hourly wage on that job, and 4.3 weeks of work in the month. Poverty rates under the second simulation are less than or equal to those under the first simulation; typically, they are about 10 percentage points lower: Baltimore County 34, Boston 41, Chicago 66, Ft. Worth 56, Milwaukee 41, Nashville 62, Philadelphia 65, Phoenix 48, St. Lucie County 52, West Virginia 75, and Yakima 51. An important factor contributing to the higher simulated poverty rates based on actual earnings is lack of consistent work by employed WtW enrollees over the month preceding the survey interview. We conducted these simulations using data for enrollees who (1) had positive earnings in the month prior to the survey interview and (2) had positive hours of work and a positive wage rate on the principal job held at the time of the interview.

(64) The value of the index of material distress was computed by adding up the number of an enrollees affirmative responses to 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 of the index of material distress closely resembles that of the index of material hardship 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). For this study, we omitted two of seven specific types of distress, both reflecting failure to see a health care professional when needed. We included these instead in this studys index of health-related distress (Appendix Exhibit B.22).

(66) These three study sites were the only ones in which the incidence of either form of homelessness among WtW enrollees exceeded 10 percent during the second year following program entry (Appendix Exhibit B.18).

(67) As noted in Section C.3 of Chapter IV, coverage by employer-provided health insurance increased among employed enrollees between the end of the first year following program entry and the end of the second year in Chicago, Philadelphia, and Nashville. Rates of TANF receipt, and presumably rates of own Medicaid coverage, fell among all enrollees in these same sites over that period. These two trends had opposing implications for enrollee health insurance coverage. The net effect was a reduction in health insurance coverage among enrollees in Chicago and Philadelphia and essentially no change in coverage among enrollees in Nashville.

 

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