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Qt3sd0f741.Pdf UC Berkeley UC Berkeley Electronic Theses and Dissertations Title Essays in Labor Economics and the Criminal Justice System Permalink https://escholarship.org/uc/item/3sd0f741 Author Shem-Tov, Yotam Publication Date 2019 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California Essays in Labor Economics and the Criminal Justice System by Yotam Shem-Tov A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Economics in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Patrick Kline, Chair Professor David Card Professor Steven Raphael Professor Christopher Walters Spring 2019 Essays in Labor Economics and the Criminal Justice System Copyright 2019 by Yotam Shem-Tov 1 Abstract Essays in Labor Economics and the Criminal Justice System by Yotam Shem-Tov Doctor of Philosophy in Economics University of California, Berkeley Professor Patrick Kline, Chair This dissertation investigates key aspects of the U.S. criminal justice system. The first chapter studies different methods of providing a legal counsel to low-income criminal defendants. Most criminal defendants in the U.S. cannot afford to hire an attorney. To provide constitutionally mandated legal services, states commonly use either private court-appointed attorneys or a public defender organization. This paper investigates the relative efficacy of these two modes of indigent defense by comparing outcomes of co- defendants assigned to different types of attorneys within the same case. Using data from San Francisco, I show that in multiple defendant cases public defender assignment is plausibly as good as random. I find that defendants who have been assigned a public defenders obtain more favorable sentencing outcomes. The second chapter investigate the causal effect of incarceration on reoffending using discontinuities in state sentencing guidelines and two decades of administrative records from North Carolina. A regression discontinuity analysis shows that one year of incarceration reduces the likelihood of committing new assault, property, and drug offenses within three years of conviction by 38%, 24%, and 20%, respectively. Incarceration sentences temporarily incapacitate offenders by removing them from society but can also influence post-release criminal behavior. The third chapter parses the non-linear and heterogeneous effects of incarceration on post-release criminal behavior, I develop an econometric model of sentencing length and recidivism. This model model allows for Roy-style selection into sentencing on the basis of latent criminality. I propose a two-step control function estimator of the model parameters and show that our estimates accurately reproduce the reduced form effects of the sentencing discontinuities that I study. The parameter estimates indicate that incarceration has modest crime-reducing behavioral effects that are diminishing in incarceration length. A cost-benefit analysis suggests, however, that the benefit of reducing crime by lengthening sentences (through both incapacitation and behavioral channels) is outweighed by the large fiscal costs of incarceration. i To my mother. ii Contents Contents ii List of Figures iv List of Tables vi List of Tables viii 1 Make-or-Buy? The Provision of Indigent Defense Services in the U.S.1 I Introduction.................................... 1 II Data........................................ 5 III Identification strategy: Conflict-of-interest considerations in cases of multiple defendants..................................... 6 IV The attorney type effect on case outcomes................... 9 V Attorney characteristics ............................. 12 VI The importance of the attorney type in federal courts............. 13 VII Discussion..................................... 18 2 Does Incarceration Increase Crime? 30 I Introduction.................................... 30 II Conceptual framework .............................. 35 III Setting and data ................................. 40 IV Empirical strategy ................................ 43 V Causal effects of incarceration.......................... 46 VI Threats to identification ............................. 51 3 A Model of the Behavioral Effects of Incarceration 62 I A complete model of incarceration effects.................... 62 II Policy reforms................................... 69 III Concluding remarks................................ 71 Bibliography 80 iii A Chapter 1 appendices 91 I Failure Functions and IV Estimators ...................... 113 II IV using reoffending from at-risk and time-varying controls . 114 III Independent competing risks........................... 116 IV Heterogeneity by discontinuity.......................... 120 iv List of Figures 1.1 San Francisco: The distribution of defendants across attorney types and over time, by filing year.................................. 19 1.2 Validating the conflict of interest hypothesis.................... 20 1.3 San Francisco: Differences in observable characteristics between defendants assigned to PD vs. CA (2006 − 2016) ........................ 21 1.4 San Francisco: The effects of the attorney type on the defendant’s case outcomes 22 1.5 San Francisco: Heterogeneity in the effects of the attorney type on the defendant’s case outcomes by criminal history and demographic characteristics . 23 1.6 Federal courts: Differences in observable characteristics between defendants assigned to PD vs. CA (1996 − 2014) ........................ 24 2.1 Sentencing guidelines until 2009 (illustration) ................... 52 2.2 First stage: sentencing outcomes by prior points for offenders convicted of a class F felony offense.................................... 53 2.3 Predicted reoffending score by felony offense severity class and prior points . 54 2.4 Share reincarcerated within three years of conviction (class F felony offenses) . 55 2.5 Dynamic differences in incarceration status at a given month after conviction (class F felony offenses) ............................... 56 2.6 Effects on reoffending at period t from conviction and on any reoffending up to period t from conviction............................... 57 2.7 A comparison of reoffending patterns between non-incarcerated and compliers under the probation (non-incarceration) regime .................. 58 3.1 Heterogeneity and non-linearity in the behavioral effects of incarceration on reoffending in the years after release ........................ 73 3.2 Control function goodness of fit: Replication of reduced form RD estimates of reoffending at various time windows from conviction................ 74 3.3 Decomposition by offense class of reduced form RD estimates into incapacitation and behavioral channels ............................... 75 3.4 Distribution of reoffending probabilities and the share of offenders incarcerated . 76 v A.1 San Francisco: Monte-Carlo permutations of attorney type assignment within a case: F-statistic using Offense codes and controls ................. 92 A.2 San Francisco: The relationship between initial assignment to a PD and involvement in the criminal justice system within a fixed period of time since disposition ...................................... 93 A.3 Federal courts, the distribution of defendants across attorney types and over time, by filing year ..................................... 96 A.4 Distribution of defendants across attorney types, by the num. of defendants in the case ........................................ 97 A.5 federal courts, validating the conflict of interest hypothesis (1970 − 1995) . 102 A.6 Order on the indictment and the probability to be assigned PD among multiple defendant cases.................................... 103 A.7 Order on the indictment and the length of incarceration . 104 A.8 The rejection rate using permutation inference compare to the standard cluster-robust standard errors . 111 A.9 Reduced form estimates of cumulative reoffending up to period t from conviction 112 A.10 Selection into incarceration duration based on gains (reduction in reoffending due to incarceration exposure).............................. 112 A.11 Illustration of IV estimates of incarceration on re-offending within t months from conviction....................................... 114 A.12 The relationship between technical probation revocation prior to a new offense and the predicted likelihood of committing a new offense within three years . 118 A.13 Independent risks: Reduced form estimates of any incarceration at period t and of any reoffending up to period t from conviction . 119 A.14 Share reincarcerated within three years of conviction (offenses from felony classes E,G,H, and I)..................................... 122 A.15 Dynamic differences in incarceration status at a given month after conviction (class E felony offenses) ............................... 123 A.16 Dynamic differences in incarceration status at a given month after conviction (class G felony offenses) ............................... 124 A.17 Dynamic differences in incarceration status at a given month after conviction (class H felony offenses) ............................... 125 A.18 Dynamic differences in incarceration status at a given month after conviction (class I felony offenses)................................ 126 A.19 Reduced form estimates of reoffending at period t from conviction and also estimates of any reoffending up to period t from conviction . 127 A.20 Reduced form estimates of reoffending at period t from conviction and also estimates
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