Journal of Policy Analysis and Management最新文献

Involvement with the juvenile justice system carries immense consequences both to detained youth and to society more broadly. Extant research on the “school-to-prison pipeline” has often focused on school disciplinary practices such as suspension with less attention on understanding the impact of school referrals to the juvenile justice system on students. Using novel administrative data from North Carolina, we link 3 years of individual educational and disciplinary infraction records to juvenile justice system records to identify the effect of juvenile justice referrals for school-based offenses on academic and behavioral outcomes. We find that, even for the same offense type and circumstance, relative to students only punished internally in the school, students referred to juvenile justice experience lower academic achievement and increased absenteeism, and are more likely to be involved in future disciplinary infractions and juvenile system contact. We show that these juvenile referrals are not inevitable and instead reflect a series of discretionary choices made by school administrators and law enforcement. Moreover, we find that female students, Black students, and economically disadvantaged students are more likely to receive referrals even for the same offense type and circumstances.

We use a baby formula “food scare” in Israel in 2003 as a plausible natural experiment to study the causal relationship between breastfeeding and mothers’ return to work after childbirth. Analysis of administrative data covering the universe of births in the country shows that first-time mothers who gave birth shortly after the scare delayed their return to work. Their average months worked in the first 6 months after childbirth fell by about 11% relative to their counterparts in the previous year. Data from a major medical equipment lender in Israel indicates an increased likelihood of borrowing milk pumps, suggesting that the delay in returning to work was driven by an increase in breastfeeding. The results indicate that despite developments in technology and policy changes in recent decades, mothers still trade off work for the breastfeeding of their children.

Differential coverage across demographic groups in a census or survey can reduce the accuracy and representativeness of the resulting statistics. Researchers traditionally have used community-level measures to study response behavior and coverage, which can obscure patterns for small population groups. We illustrate this using household-level citizenship and immigration status. We construct household-level characteristics using administrative records for each address in a randomized control trial (RCT) survey that measured the effects of including a citizenship question on a decennial census questionnaire. Our results show that the self-response rate to the questionnaire without the citizenship question ranges from 70.4% in households with only U.S.-born non-Hispanic Whites to 27.5% in those with at least one likely undocumented person (a 42.9 percentage point gap). Including the citizenship question widens the gap by a statistically significant 2.4 percentage points. Compared to households with all U.S.-born non-Hispanic Whites, the household roster omission rate in households with at least one likely undocumented member is 6.0 times higher without the citizenship question and 10.4 times higher with the question. These patterns help explain why administrative record-based population data include more non-citizens than survey-based official statistics.

A commonly expressed concern about distributional weighting in benefit-cost analysis is that the informational burden is too high and the practical challenges insurmountable. In this paper, we address this concern by conducting distributional weighting on a number of real-world examples, covering a range of different types of policy impacts. We uncover and explore a number of methodological issues that arise in the process of distributional weighting and provide a simplified set of steps that we believe can be implemented by practitioners with a wide range of expertise. We conduct sensitivity analysis and Monte Carlo simulation to test the robustness of our estimates of weighted net benefits to the various assumptions we make, and find that, in general, distributional weighting is no more vulnerable to modeling assumptions and parameter selection than unweighted benefit-cost analysis itself. We conclude that the concern about the practicability of distributional weighting is, at least in a range of important cases, unfounded.

We study how civilian complaint investigators affect officer behavior in Chicago. We exploit quasi-random assignment of complaints to supervising investigators and use variation in whether supervisors tend to acquire sworn affidavits that substantiate the complaints. When the assigned investigator opens more investigations through obtaining affidavits, accused officers accumulate fewer complaints in the first three months of the investigation. We find that, prior to a scandal, assignment to high-investigation supervisors causes officers to make more arrests. However, this reverses after the scandal. Our findings suggest that police watchdogs can improve officer behavior in ordinary oversight environments but may backfire in heightened oversight environments.

In this essay, I seek to reconcile critical and econometric approaches to diagnosing the causes of deep racial inequalities in child welfare system outcomes. Using a series of causal diagrams and critical engagement with the counterfactual causal model, I suggest policy analysts embrace a theoretical framework for quantitative inference that recognizes the complex ways that racism impacts families, places, and policy systems. Common approaches that partition inequalities into risk and bias components normatively imply that some inequalities are legitimate and some illegitimate. As we push toward foundational reform in how policy systems work with children and families, we must embrace analytic approaches that 1) map more convincingly onto real-world processes and 2) take questions of equity and harm as central ethical concerns.