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Incarceration and the Transition to Adulthood

Incarceration and the Transition to Adulthood

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Incarceration and the Transition to Adulthood

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  1. Incarceration and the Transition to Adulthood Gary Sweeten Arizona State University Robert Apel University at Albany June 4, 2007 2007 Crime and Population Dynamics Summer Workshop

  2. After Incarceration • 240,000 youths under age 24 are released from secure adult or juvenile facilities each year • Two-thirds of ex-prisoners are re-arrested in three years • Nearly one quarter are re-incarcerated in three years • Relegation to secondary labor market: lower wages, less wage growth, instability • Less educational attainment • Disruption of marital unions

  3. Research Questions • Does incarceration have a causal effect on crime, employment, education, relationships and fertility? • Do juvenile and adult incarceration have different effects? • How do causal effects develop over time? (decay vs. growth)

  4. Fundamental Problem • The biggest hurdle in estimating a causal effect of incarceration is selection bias • The justice system reserves incarceration for the most serious offenders. • Incarcerees differ significantly from the general population, from self-reported offenders, from arrestees, from convicts, and from probationers.

  5. Selection: Incarcerated sample is more involved in crime

  6. Panel Models • Fixed effects models eliminate selection bias attributable to time-stable unobservables • Identification: within-individual change • Remaining problems: • Bias due to omitted dynamic variables • Bias due to varying effects of time-stable variables • Adolescence is a time of great change. For many outcomes of interest, there is little to no pre-period variation (e.g. marriage, employment, dropout)

  7. Panel Models • In this paper, we employ difference-in-difference fixed effects models to assess the effects of incarceration. • Identification: within-individual change, contrasted between groups • Contrast groups: un-incarcerated, arrested, convicted • Advantage: eliminates bias attributable to time-stable unobservables, and bias due to time-varying unobservables with equivalent effects on the compared groups

  8. Propensity Score Matching • We also employ propensity score matching to assess the effects of incarceration. • Identification: unincarcerated individuals matched to incarcerated based on propensity to be incarcerated • Advantages: highlights common support issue, allows assessment of multiple outcomes over multiple years once balance is demonstrated

  9. Data: Two Samples • National Longitudinal Survey of Youth 1997 • First eight waves, 1997-2004 • 8,984 youths 12-16 years old as of 12/31/1996

  10. Re-alignment of Data • Pre-treatment waves: used for contrast in fixed effects d-in-d models, for propensity score estimation, assessment of balance • Treatment wave, average of up to 3 waves during which individual was 16 or 17 (18 or 19 for older sample) • Post-treatment waves: treatment effect assessed during waves after the age of interest

  11. Key Measures: Treatment and Response Variables Treatment • Self-reported incarceration of any length Response variables (all self-report) • Criminal behavior, illegal earnings, arrest • Formal employment, hours, earnings • High school dropout, GED, grades completed • Marriage, cohabitation, fertility

  12. Random-Effects Models of Pre-Incarceration Differences between Treated and Untreated Individuals, by Age of First Incarceration + p < .10,* p < .05)

  13. Fixed Effects Difference-In-Difference Results, Incarcerated vs. Convicted + p < .10,* p < .05)

  14. Propensity Score Matching • In simple comparisons, less than 40% of 206 background variables were balanced between incarcerated and unincarcerated groups • Type of matching: up to 3 nearest neighbors within .01 on propensity score metric • Using just 32 predictors for juvenile incarceration (58 for adult) 98% of background variables were balanced (91% for adults) • Support: 5 of 116 (4.3%) incarcerated juveniles and 9 of 135 (6.7%) incarcerated adults went unmatched

  15. Propensity Score Matching Estimates + p < .10,* p < .05)

  16. Conclusions • The correlation between incarceration and life transitions is causal for some outcomes, but a selection artifact for others • Crime and arrest: possibly short-term criminogenic causal effect (mixed evidence) • Employment: reduced participation in formal job market, short-term for adult incarceration • But, for those who find employment, there appears to be no effect of incarceration on other features of work • Education: consistent negative effects that grow over time • Family transitions: no evidence of casual effect