Heterogeneous causal effects of neighborhood policing in New York City with staggered adoption of the policy

Communities often self select into implementing a regulatory policy, and adopt the policy at different time points. In New York City, neighborhood policing was adopted at the police precinct level over the years 2015-2018, and it is of interest to both (1) evaluate the impact of the policy, and (2) understand what types of communities are most impacted by the policy, raising questions of heterogeneous treatment effects. We develop novel statistical approaches that are robust to unmeasured confounding bias to study the causal effect of policies implemented at the community level. Using techniques from high-dimensional Bayesian time-series modeling, we estimate treatment effects by predicting counterfactual values of what would have happened in the absence of neighborhood policing. We couple the posterior predictive distribution of the treatment effect with flexible modeling to identify how the impact of the policy varies across time and community characteristics. Using pre-treatment data from New York City, we show our approach produces unbiased estimates of treatment effects with valid measures of uncertainty. Lastly, we find that neighborhood policing decreases discretionary arrests, but has little effect on crime or racial disparities in arrest rates

Uneven Policing: Low-Level Arrests During Gentrification, Fiscal Crisis, and Suburbanization

In this dissertation, I analyze trends in low-level policing between 1990 and 2015. I explore how three contextual changes may have shaped policing during this time: gentrification, fiscal crisis, and the suburbanization of poverty and of people of color. I ask four interrelated research questions: How widely did “broken windows” policing, with its emphasis on misdemeanor arrests, diffuse? Do police make more stops and arrests in neighborhoods undergoing gentrification? Do local governments experiencing revenue shortfalls cut their criminal justice functions to save money, or do they increase them to reassert social order? Did the suburbanization of poverty and of people of color lead police to make more or more racially disproportionate arrests in suburbs? To address these questions, I assemble three novel, longitudinal datasets using publicly available government data. I convey descriptive statistics in graphs, tables, and maps and I construct multivariate regression models to estimate the relationships between policing and place. I build on past theories, especially those exploring the political economy, racial threat, and crime control of policing

Robust inference for geographic regression discontinuity designs: assessing the impact of police precincts

We study variation in policing outcomes attributable to differential policing practices in New York City (NYC) using geographic regression discontinuity designs (GeoRDDs). By focusing on small geographic windows near police precinct boundaries we can estimate local average treatment effects of precincts on arrest rates. The standard GeoRDD relies on continuity assumptions of the potential outcome surface or a local randomization assumption within a window around the boundary. These assumptions, however, can easily be violated in realistic applications. We develop a novel and robust approach to testing whether there are differences in policing outcomes that are caused by differences in police precincts across NYC. In particular, our test is robust to violations of the assumptions traditionally made in GeoRDDs and is valid under much weaker assumptions. We use a unique form of resampling to identify new geographic boundaries that are known to have no treatment effect, which provides a valid estimate of our test statistic's null distribution even under violations of standard assumptions. This procedure gives substantially different results in the analysis of NYC arrest rates than those that rely on standard assumptions, thereby providing more robust tests of the effect of police precincts on arrest rates in NYC

Principal stratification with continuous treatments and continuous post-treatment variables

In causal inference studies, interest often lies in understanding the mechanisms through which a treatment affects an outcome. One approach is principal stratification (PS), which introduces well-defined causal effects in the presence of confounded post-treatment variables, or mediators, and clearly defines the assumptions for identification and estimation of those effects. The goal of this paper is to extend the PS framework to studies with continuous treatments and continuous post-treatment variables, which introduces a number of unique challenges both in terms of defining causal effects and performing inference. This manuscript provides three key methodological contributions: 1) we introduce novel principal estimands for continuous treatments that provide valuable insights into different causal mechanisms, 2) we utilize Bayesian nonparametric approaches to model the joint distribution of the potential mediating variables based on both Gaussian processes and Dirichlet process mixtures to ensure our approach is robust to model misspecification, and 3) we provide theoretical and numerical justification for utilizing a model for the potential outcomes to identify the joint distribution of the potential mediating variables. Lastly, we apply our methodology to a novel study of the relationship between the economy and arrest rates, and how this is potentially mediated by police capacity

Editorial: Nature-based solutions for natural hazards and climate change

No abstract available

Home moves and child wellbeing in the first five years of life in the United States

By the time they are five years old, nearly 70% of children in the United States have moved home, with a substantial minority moving more than once.  These early years are important for children’s later learning and development. Yet, there are a limited number of studies of residential mobility’s impact on young children.  The literature indicates the importance of stressful family events, unstable housing, economic hardship, and neighbourhood conditions for residential mobility and child wellbeing. But research seldom examines the impact of these dimensions simultaneously.  We used data from the first four waves of the Fragile Families and Child Wellbeing Study to analyse precursors of residential mobility and the association of residential mobility with child behavior (N=2,511) and cognitive capabilities (N=2,033) at age five.  Using Generalized Estimating Equations (GEE), we find that the frequency of moving is explained by a range of stressful circumstances, including lack of parental employment, partnership transitions, paternal incarceration, unstable housing tenure, and financial hardship.  These circumstances are associated with increased likelihood of moving home even when other family and neighbourhood conditions are controlled, suggesting that moving is part of a constellation of events and changes experienced by young children.  Using OLS regression models we find that, for young children, the circumstances associated with moving residence appear to be more consequential for child wellbeing than does moving itself, even when children experience multiple moves.

Guidelines for licensing CO2 storage operations around the globe

In January 2008, the European Commission proposed a directive on the geologic storage of CO2 in the EU. Simultaneous to the development of the directive by the EC, the CO2 ReMoVe project, funded by FP6 and industry, wrote a draft contribution to future guidelines for licensing of CO2 storage in saline reservoirs and depleted hydrocarbon reservoirs. This document contains detailed checklists for operators and authorities in each of the stages of a licensing procedure for a CO2 storage operation. The draft guidelines will be updated as results from monitoring ongoing CO2 storage operations become available. They may serve as a contribution to the regulation of CO2 storage anywhere in the world, and may be also be of use in evaluating the EU directive in the futur

Non-enzymatic triggering of the ceramide signalling cascade by solar UVA radiation

Ceramide is a key component of intracellular stress responses. Evidence is provided for a novel mechanism of ceramide formation that mediates solar ultraviolet (UV) A radiation-induced expression of the intercellular adhesion molecule (ICAM)-1. Similarly to UVA radiation, ceramide stimulation of human keratinocytes induced ICAM-1 mRNA expression and activated the ICAM-1 promoter through transcription factor AP-2. Ceramide-activated AP-2 and ceramide-induced ICAM-1 reporter gene activation were abrogated through deletion of the AP-2 binding site. UVA radiation increased the level of ceramide in keratinocytes and inhibition of sphingomyelin synthesis prevented UVA radiation-induced ICAM-1 expression. Hitherto, two pathways have been identified for ceramide accumulation: hydrolysis from sphingomyelin through neutral and acid sphingomyelinases, and de novo synthesis by ceramide synthase. UVA radiation did not activate any of these enzymes. Ceramide generation in UVA-irradiated cells, however, was inhibited by singlet oxygen quenchers and mimicked in unirradiated cells by a singlet oxygen-generating system. In addition, UVA radiation and singlet oxygen both generated ceramide in protein-free, sphingomyelin-containing liposomes. This study indicates that singlet oxygen triggers a third, non-enzymatic mechanism of ceramide formation