Studies conducted on the characteristics and circumstances of sanctioned families presented relatively consistent findings (see Table 7). These studies found that sanctioned recipients are more likely than non-sanctioned recipients to have personal characteristics, human capital deficits, transportation barriers or personal and family challenges that make them harder to employ. They are more likely to return to TANF and less likely to be employed. These families are also more likely to experience various hardships and, on average, have lower household income. While these findings are generally consistent, the measures used are not, making it impossible to compare the magnitude of the differences across studies. The area in which these findings are most incomplete is in the presence of personal and family challenges such as substance abuse, mental health and domestic violence. Few studies captured this information; those that did didn't always reach the same conclusions. The information on the greater presence of material hardships is also difficult to interpret because it may be unrelated to the imposition of the sanction (i.e., sanctioned families may have experienced greater hardships prior to the sanction).
Few data necessary to examine families' characteristics and circumstances are readily available from routine administrative data files. Thus, to obtain more detailed information, survey data are needed. Surveying a cohort of recipients at multiple times would provide the most comprehensive information. Attaching a longitudinal survey component to the multi-state study recommended earlier would enable a simultaneous analysis of the characteristics and circumstances of sanctioned and non-sanctioned recipients, and of incidence and duration. Key topics to include in the survey would be the presence of various barriers to employment and the experience of material hardship. Standardized measures would make it possible to compare these results with those of other studies examining the TANF population as a whole. One possible way to better examine whether sanctioned families are more likely than non-sanctioned families to experience hardships would be to examine the frequency of these hardships using a multivariate analysis that controls for individual differences. This would address, at least partially, the issue that sanctioned and non-sanctioned families may be different even before the sanction is imposed.
In the absence of a new multi-site study, cross-state analysis of the recent ASPE-funded state surveys of current TANF recipients could substantially increase our understanding of the employment barriers among sanctioned and non-sanctioned families, and whether there are similar patterns observed across states. Six states fielded the same survey (with a few state-specific questions added), producing comparable data on barriers to employment among states that use a variety of sanction policies. The states are linking administrative data with survey responses, making it possible to identify families who were sanctioned at the time the survey sample was selected. With additional administrative data, it would be possible to identify families sanctioned prior to or after the selection month. For example, if you followed these families for a year or two after the time they were selected into the sample you could track them over time using administrative data to see who gets sanctioned.
|Study||More likely to be Hard-to-Employ||More likely to return to TANF||Less likely to be employed||Have less household income||More likely to experience material hardships|
|*Born et al. (1999)||x||x||x||x||n/a|
|Cherlin et al. (2001)||x||n/a||n/a||x||x|
|*Edelhoch et al. (2000)||x||n/a||x||x||x|
|Fein and Lee (1999)||x||x||x||x||n/a|
|Kalil et al. (2002)||x||n/a||n/a||n/a||x|
|*Mancuso and Linder (2001)||x||n/a||n/a||x||N/a|
|*Westra and Routely (2000)||x||x||x||x||x|
|* Indicates studies that compare sanctioned welfare recipients to other welfare leavers.
n/a - Variables not included in the analysis.
Then, you could use the combined administrative and survey data to conduct a detailed analysis of who is at risk of a sanction. One possible limitation is that the survey samples were selected from the entire TANF caseload, and may not yield sufficient cases for analysis of sanctioned and non-sanctioned cases. The capture of sufficient cases depends on several factors, including the size of the original survey sample, the state sanction policy, the rate at which sanctions are imposed and the length of follow-up to identify cases that are eventually sanctioned.
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