Will the real nonparticipants please stand up?

1. Will the real nonparticipants please stand up? Exploring selection bias and treatment contamination in employment programs

2. agenda • Reentry context in New York State • Knowledge base: work, finances, and crime • Aims and research questions • Research findings • Practice and research implications • Ongoing and future research

3. “…reducing the madness OF AN INCARCERATION SOCIETY…”* • 25% decline in NY prison population • Declining crime rates in NYC • Rockefeller drug laws reform • Cuomo: reduce fiscal burden on the state • 11 recent, 4 planned prison closings • Reinvest in preventive and rehabilitative services *Cuomo, 2014

4. Prison reduction strategies • Council on Community Re-Entry and Reintegration • State council to help nonviolent offenders • $5 million proposed FY14 investment in programs: • Workforce Investment Board: Oneida County • TASC Case management and reentry services • Strategies include job training and supported work

5. Jobs program logic model • Services • Life skills • Transitional jobs • Job coaching • Job development • Supportive services • Increased • Employment • Income • Soft skills • Work readiness • Stability • Increased • Employment • Job retention • Reduced recidivism • Reduced recidivism Adapted from Redcross et al. (2012)

6. Weak evaluation support • Programs do not appear to improve work outcomes or reduce crime • Experimental studies: Most jobs programs show modest or null effects • Positive effects observed among: • Older former prisoners • High-risk prisoners

7. labor force participation • Before prison • Rising unemployment • High levels of work instability • High job turnover • After release • Initial boost in formal employment • Rates decline to pre-prison levels within three years

8. Labor force nonparticipation • Low opportunity cost to crime • Limited job options available • Limited formal work experience • Weak labor market skills • High opportunity cost to formal employment • Low hourly wage, reduced leisure time • Garnished wages (e.g., child support, legal debts) • Risk detection at workplace

9. Research questions, Part 1 • Do respondents exhibit distinct arrest trajectories before entering prison? • Do participants differ from nonparticipants along prior arrest trajectories? • Do employment programs improve men’s post-release employment and recidivism outcomes?

10. Research questions, Part 2 • Is labor force non-participation associated with increased recidivism risk? • Is labor force participation associated with higher quality employment? • What factors break the association between employment and reduced offending?

11. Research aims • Examine whether evaluation findings reflect • Men’s selection into employment services • Contamination from participation in similar programs • Examine whether effects persist after controlling for • Prior criminal record • Work experience • Participation in programs that offer overlapping content

12. Serious and violent offender reentry initiative (SVORI) • Target Population: • Adult male prisoners under 35 years old • Convicted of violent or serious drug offenses • States designed services to fit local context • Intent-to-treat design • Propensity score weights: SVORI service receipt

13. data sources FBI National Crime Information Center • Lifetime adult arrest records • Spanning state lines and agency reporting systems SVORI Evaluation baseline interviews • Conducted in prisons during month before release • Demographics, background, criminal history, prison experiences, physical/mental health

14. Descriptive statistics (N = 1,575)

15. Trajectory model Predictor variables, final model: • Age at each arrest: Linear and squared terms • Indicator of arrests during 10 years before SVORI term • State indicator for prison site • Age at release from prison • Lifetime adult arrest record: Natural log transformation Outcome variable: • Predicted probability of group membership

16. Pre-svori arrest trajectories High (38.9%) Probability of arrest each year Middle (45.1%) Low (16.0%) Age at arrest

17. Criminal history: Trajectory groups

18. Demographics: trajectory groups

19. Group characteristics • High-level group • Young, African American high school dropouts • High-rate property and drug offenders • Low-level group • Older, White or Hispanic, high school graduates • Low-rate violent offenders • Mid-level group • Similar demographic profile to low-level group

20. Participation: trajectory groups

21. Propensity score matching Multilevel logistic regression model • Stata xtmelogit • SVORI treatment condition, Prison site (state) • Individual-level characteristics Matching techniques • Stata psmatch2 • Radius matching with caliper (.2 SD/ln odds) • Common support condition, ties permitted

22. Criminal history: participation

23. Demographics: trajectory groups

24. Prison site: participation

25. Lingering differences • Participants • Younger mean age of first arrest • Younger mean age at release • Longer mean SVORI prison term • Nonparticipants • Higher mean arrest total • Higher mean prison terms • More likely to have high school diploma

26. Duration model measures Duration models • Indicators of three employment services • Indicator of multiple service receipt • Demographic characteristics • Indicator for work before prison • Criminal history

27. Hazard ratios: Time to first arrest

28. Duration model findings • Shorter time to first rearrest • Participation in multiple employment programs • African Americans (ref. White) • Property offender • Parole violator • Longer time to first rearrest • Older age at release from prison • GED or trade certification

29. Strengths and limitations • Trajectory model • Varying length of criminal records • Unobserved heterogeneity • Propensity score model • Lingering observed heterogeneity • Unobserved heterogeneity • Limited common overlap • Duration model • Variation in quality and quantity of services received • Official data: timing and observation

30. Part 2: Job quality model • norawikoff.wordpress.com

31. Implications: research • Direction of the work-crime relationship • Factors that contribute to labor force exit • Low wages, debts, garnishments, financial strain • Factors that increase labor force attachment

32. Implications: practice • Program design • Offer intensive programs to a select few • Use desistance “signals” to identify participants • Program evaluation • Model the selection process (not cream-skimming) • Service delivery • Address financial challenges

33. Other research • SEED for Oklahoma Kids (SEED OK) • Test of universal Child Development Accounts • Experimental study design • Better Futures Enterprises (Twin Cities, MN) • Social enterprise providing subsidized housing and supported employment to homeless men • Pay-for-success agreements with nonprofits and governmental agencies

34. future research: Pathways to Desistance • Life events and transitions during early adulthood • Model employment and offending trajectories • Examine effect of interventions and programs • 7-year follow-up period (84% retention) • Multiple data sources: self-report, official, and collateral reporters

35. Acknowledgements This research is supported by a research grant from the National Institute of Justice: NIJ Graduate Research Fellowship • Grant Award #: 2013-IJ-CX-0042 • Project Period: 11/1/13 – 7/31/14

36. Contact information Nora Wikoff Brown School of Social Work Washington University in St. Louis nwikoff@go.wustl.edu [c] 314-703-8731 norawikoff.wordpress.com