Evaluation of the Ticket to Work Program, Implementation ...

As mentioned, the bivariate analysis indicates that beneficiaries who received theirbenefit allowance in the six months before March 2004 are less likely than others toparticipate, and that participation rates vary little with duration of time on the rolls for thosewho received their allowance earlier. In the multivariate analysis, we experimented with asimple model that had only one category for those on the rolls for 24 months or more andaccounted for a possible interaction between those on the rolls for less than 24 months andthose enrolled in DI. The purpose of the experiment was to capture the possibility thatsome DI-only beneficiaries might refrain from participating in TTW until they were entitledto Medicare (that is, until they had completed the two-year waiting period). Using themodel, we found that those on the rolls for 7 to 23 months as of March 2004 participated ata rate that was only slightly higher than the rate for those who received their award at anypoint up through six months. We also found that DI-only beneficiaries were just slightly lesslikely than SSI beneficiaries to participate. We plan to examine this issue further in thefuture with more detailed statistical models.We also included a variety of county characteristics 17 in the multivariate analysis toexamine whether these characteristics are predictive of participation after controlling forbeneficiary characteristics and state of residence (see Appendix B). The results indicate that,most county characteristics individually have very little predictive power after individualcharacteristics are controlled for. We also found that the results are difficult to interpretbecause of correlations between the numerous county characteristics. In the future, we willdevelop models in which county variables are treated in a way that makes the results easier tointerpret. 1827C. PREDICTORS OF PROVIDER AND PAYMENT TYPEFor our earlier report, we found that provider and payment type for in-use Tickets varywith age. We continue to find, in both Phase 1 and 2 states, that older beneficiaries are morelikely than younger beneficiaries to assign their Tickets to ENs and to use one of the newpayment systems. For example, in March 2004, 13.0 percent of Phase 1 beneficiaries age 60to 64 with in-use Tickets had assigned their Tickets to ENs, 21.0 percent of which wereassigned under one of the new payment systems; the corresponding percentages for those 18to 24 years old were 3.4 and 7.9 percent, respectively.17 The variables are: population density, population loss between 1990 and 2000, percent AfricanAmerican, percent non-white, percent Hispanic, percent of populations living in households with incomebelow the poverty line, percent of employment in manufacturing, the unemployment rate, another lowemployment index, an urban/rural index, the percentage of workers using public transit, a housing stress index,and a low education index.18 There are several possible reasons for the low predictive power of individual county characteristics.One is that they are highly correlated with individual characteristics already captured by other variables—especially the state indicators, as well as race, education, and possibly others. Another is that they are highlycorrelated with each other across counties, making it difficult to separate the predictive power of any one fromthe others. Agodini et al. (2002) found similar results in an evaluation of the State Partnership Initiative. Wewill explore these explanations further in future analyses.II: Beneficiary Participation in Ticket to Work