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

2512. Multivariate Analysis of ParticipationWe extended the bivariate analysis of factors correlated with beneficiary participation byconsidering how all factors together are related to beneficiaries’ participation decisions. Thismultivariate approach lets us assess how well we can predict participation on the basis ofmeasured characteristics. It also lets us assess the extent to which any specific factor isrelated to participation once we control for the effects of other beneficiary characteristicsthat may be correlated with that factor. For example, the multivariate analysis lets us assesswhether the bivariate finding that concurrent beneficiaries participated at a higher rate thanDI-only or SSI-only beneficiaries is really due to the fact that concurrent beneficiaries tendto be younger than other beneficiaries (younger beneficiaries also participate at higher rates).Overall, we found that each characteristic that has a substantial bivariate relationshipwith the participation rate, as described above, also has a substantial relationship with theparticipation rate after accounting for co-variation with other characteristics. In fact, thebivariate and multivariate relationship between participation and each characteristic is almostthe same for many characteristics. A few exceptions are noteworthy, as discussed below.The characteristics included in this analysis are title, sex, age, attainment of Ticket eligibilityafter the initial selection date, race, ethnicity, education, monthly benefit, months since initialDI or SSI award, language preference, level of allowance, participation in the EPE, Section1619a or Section 1619b during the ticket mail month, primary impairment, state ofresidence, and a series of county characteristics (enumerated later). Details of thespecification appear in Appendix B. Variables were defined as they were in the bivariateanalysis.One important finding from this analysis is that it is very difficult to predict whichbeneficiaries participate from characteristics that are observed in administrative data. Onlyabout one percent of the variation in participation can be accounted for by all of thecharacteristics used in this analysis. 16 Further, even when we use all of the characteristics aspredictors, the highest estimated probability of participation is less than 10 percent, and onlyone percent of beneficiaries has a predicted probability of 4.4 percent or higher. Becausemany beneficiaries do participate, we would have expected that some beneficiaries wouldhave had a high predicted participation probability if our model had been accurate. The lowpredicted probabilities suggest that other unmeasured factors, such as the nature/severity oftheir impairment, social supports, and personal motivation, play an important role inbeneficiaries’ decisions.After other characteristics are controlled for, the relationship between Title andparticipation changes. DI-only and concurrent beneficiaries participate at almost identicalrates, and the participation rate for all DI beneficiaries is 0.2 percentage points higher thanfor SSI-only beneficiaries.16 This statement is based on the value of the adjusted R 2 from the regression of the participation indicatoron all of the characteristics (1.2 percent).II: Beneficiary Participation in Ticket to Work