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Potential Assistance for Disadvantaged Workers: Employment Social Enterprises

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By integrating a business mission into a transitional jobs program, employment social enterprises (ESEs) provide temporary work and a supported work environment to reduce the barriers facing disadvantaged workers while generating revenue to cover production costs. This study uses surveys of workers in and financial statements from seven ESEs to provide information for three sets of complementary analyses: a pre-post analysis examines changes in employment between the time a person starts ESE work and about one year later; a case study uses propensity score methods to compare changes in employment between ESE workers and similar people who did not work in an enterprise; and a cost-benefit analysis estimates the potential value of ESE jobs. Results suggest that individuals have close to 21% gain in employment one year after starting ESE work; taxpayers gain at least $0.42 for every dollar spent on an ESE job; the return to society of developing an ESE is at least 34%; and the social returns to converting a profit-driven business into an ESE exceed 100%. Although the study cannot control for many of the factors that would allow estimation of causal impacts, it provides some of the first preliminary evidence of the value of the ESEs’ public-private approach to increase workforce skills and employment and stabilize lives of individuals with employment barriers.

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  1. The number of issues varied by enterprises, but such comparisons should be interpreted cautiously, because they reflect only the number of separate issues people reported and not their complexity or severity.

  2. The CBA used point estimates for benefits from the six organizations with financial data. Because the seventh organization did not have financial data, the 8% of ESE participants from that organization were excluded from analysis. This exclusion does not influence the conclusions of either the pre-post analysis or the CBA.

  3. We corrected for nonresponse in the pre-post and case study analysis by weighting all data. These nonresponse weights helped mitigate the small differences (5 percentage points or fewer) that occurred between respondents and nonrespondents (Rotz et al. 2015). Response rates varied somewhat by participant characteristics but did not significantly differ by treatment status for the case study, conditional on background factors. For example, respondents in the pre-post analysis were more likely than nonrespondents to (1) have worked in the month or year before social enterprise employment, (2) have education beyond high school, (3) be female, and (4) to need more support to succeed in the labor market, as deemed by program staff. Respondents in the case study enterprise or case study comparison group were less likely than nonrespondents therein to (1) have recently used temporary housing and (2) have been arrested. Differences by gender and education are consistent with typical patterns of survey response (Groves 1992). Differences in employment, temporary housing, and arrest records suggest that less stable participants were less likely to respond to our survey, either because they were more difficult to locate or because they were less likely to agree to participate in the survey once our study team located them.


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This research is derived from earlier work with our valued colleague Adam Dunn. We also thank Melissa Dugger and her team for heroic surveying efforts; Anne Gordon, Josh Haimson, Debbie Reed, and David Neumark for comments and feedback on earlier work; Kathryn Gonzales for outstanding technical and research assistance; and Christina Garcia and Tracy Lam-Hine for providing the cost data. This paper is based on work supported by the Corporation for National and Community Service under Social Innovation Fund Grant No. 10SIHCA001. Opinions or points of view expressed are those of the authors and do not necessarily reflect the official position of, or a position that is endorsed by, the Corporation or the Social Innovation Fund program.

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Correspondence to Nan L. Maxwell.

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Both authors work for Mathematica Policy Research, which received funding to conduct the evaluation from which data used in this study were derived.

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Maxwell, N.L., Rotz, D. Potential Assistance for Disadvantaged Workers: Employment Social Enterprises. J Labor Res 38, 145–168 (2017).

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