In this project we evaluate the application of the case management and treatment delivery practices developed under the HOPE probation strategy to pretrial individuals who are conditionally released from jail subject to criminal justice supervision.  In the jurisdiction we study (Honolulu, Hawaii), defendants on supervised release are typically monitored by pretrial officers located at the county jail.  The revocation of supervised release occurs once a defendant has failed to comply several times with a set of pre-specified conditions, including but not necessarily limited to refraining from drug use and additional criminal activity, maintaining contact with the assigned pretrial officers, and making all scheduled court dates.  The intervention we evaluate applies random drug testing in conjunction with swift, certain, consistent, and proportionate sanctions to pretrial misconduct.  That is to say, misconduct is met with quickly administered arrest and re-incarceration, yet subsequent jail spells are proportionate to the seriousness of the violation.  The intervention also includes drug treatment interventions for those who repeatedly fail drug tests (or who request treatment services) and direct interaction following each violation with the presiding judge of a court devoted to HOPE probation as well as HOPE pretrial defendants. 

Between September 2014 and August 2016, felony defendants who failed to make bail and who were granted supervised release were randomly assigned to either status-quo pretrial services or to the HOPE pretrial treatment group.  We use administrative data on drug tests, revocations, supervised release case dispositions, and criminal history records to assess whether applying HOPE to individuals on pretrial supervised release impacts various measures of pretrial misconduct, criminal case disposition, and post-disposition arrests.  Our findings are the following:

(1) HOPE treatment group members experience more pretrial supervised release revocations most of which are better characterized as modifications but fewer permanent revocations ending the supervised release term relative to control group members. 

(2) Treatment under HOPE pretrial reduced the proportion of drug tests resulting in failure.  The drug test failure rate for treatment group members was roughly 21 to 30 percent lower than the comparable failure rate observed for the control group with the difference statistically significant.

(3) HOPE treatment did not impact total jail days served between the supervised release date and the disposition date for the criminal case.  However, treatment group members serve jail days earlier in their supervised release term while control group members serve more jail days later.

(4) Average total pretrial arrests occurring after supervised release does not differ significantly between the treatment and control group.  However, treatment group members are significantly and substantially less likely to be arrested with a new criminal charge.

(5) Treatment group members are less likely to be convicted and less likely to be convicted for a felony.

(6) We do not find statistically significant effects of treatment on post-disposition arrest outcomes.

This paper shows that greater global spatial correlation of productivities can increase crosscountry welfare dispersion by increasing the correlation between a country’s productivity and its gains from trade. We causally validate this general-equilibrium prediction using a global climatic phenomenon as a natural experiment. We find that gains from trade in cereals over the last halfcentury were larger for more productive countries and smaller for less productive countries when cereal productivity was more spatially correlated. Incorporating this general-equilibrium effect into a projection of climate-change impacts raises projected international inequality, with higher welfare losses across most of Africa.

Intergenerational income transmission varies across commuting zones (CZs). I investigate whether children’s educational outcomes help to explain this variation. Differences among CZs in the relationship between parental income and children’s human capital explain only one-ninth of the variation in income transmission. A similar share is explained by differences in the return to human capital. One-third reflects earnings differences not mediated by human capital, and 40% reflects differences in marriage patterns. Intergenerational mobility appears to reflect job networks and the structure of local labor and marriage markets more than it does the education system.