Showing papers by "Justine S. Hastings published in 2019"
TL;DR: In this article, the authors investigate the impact of removing children from families investigated for abuse or neglect on the performance of young children before age six and find that removal significantly increases test scores and reduces grade repetition for girls.
Abstract: espanolEste documento analiza como impacta en el desempeno escolar la reubicacion de ninos en servicios de cuidado tutelar, tras investigaciones familiares por maltrato infantil. Para estimar el efecto causal de la reubicacion, se construye una variable instrumental. Dicha variable es la propension a reubicar a otros ninos de cada investigador de servicios de proteccion infantil. La muestra analizada se concentra en los ninos involucrados en investigaciones antes de que cumplan seis anos, y del analisis se desprende que reubicar a las ninas ocasiona un aumento significativo de sus notas escolares y reduce su probabilidad de repetir un grado. Por el contrario, no hay efectos significativos en los ninos. Las diferencias de genero en los resultados no se explican por la heterogeneidad en las caracteristicas de los ninos antes de ser reubicados, el tipo de establecimiento en el que son albergados, o las caracteristicas de sus escuelas. Los resultados respaldan la hipotesis de que las ninas responden de manera mas receptiva a ser reubicadas que los ninos. EnglishThis paper measures impacts of removing children from families investigated for abuse or neglect. We use removal tendencies of child protection investigators as an instrument. We focus on young children investigated before age six and fi nd that removal signifi cantly increases test scores and reduces grade repetition for girls. There are no detectable impacts for boys. This pattern of results does not appear to be driven by heterogeneity in pre-removal characteristics, foster placements, or the type of schools attended after removal. The results are consistent with the hypothesis that development of abused and neglected girls is more responsive to home removal.
51 citations
TL;DR: When properly secured, anonymized, and optimized for research, administrative data can be put to work to help government programs better serve those in need.
Abstract: When properly secured, anonymized, and optimized for research, administrative data can be put to work to help government programs better serve those in need.
17 citations
TL;DR: In this paper, the effect of photo ID laws on voting using a difference-in-differences estimation approach around Rhode Island's implementation of a photo ID law was studied, using anonymized administrative data to measure the law's impact by comparing voting behavior among those with drivers' licenses versus those without.
Abstract: We study the effect of photo ID laws on voting using a difference-in-differences estimation approach around Rhode Island’s implementation of a photo ID law. We employ anonymized administrative data to measure the law’s impact by comparing voting behavior among those with drivers’ licenses versus those without, before versus after the law. Turnout, registration, and voting conditional on registration fell for those without licenses after the law passed. We do not find evidence that people proactively obtained licenses in anticipation of the law, nor do we find that they substituted towards mail ballots which do not require a photo ID.
7 citations
Posted Content•
TL;DR: This work uses new state government administrative data and machine learning methods to examine whether the risk of future opioid dependence, abuse, or poisoning can be predicted in advance of an initial opioid prescription, and accurately predicts these outcomes.
Abstract: Misuse of prescription opioids is a leading cause of premature death in the United States. We use new state government administrative data and machine learning methods to examine whether the risk of future opioid dependence, abuse, or poisoning can be predicted in advance of an initial opioid prescription. Our models accurately predict these outcomes and identify particular prior non-opioid prescriptions, medical history, incarceration, and demographics as strong predictors. Using our model estimates, we simulate a hypothetical policy which restricts new opioid prescriptions to only those with low predicted risk. The policy’s potential benefits likely outweigh costs across demographic subgroups, even for lenient definitions of “high risk.” Our findings suggest new avenues for prevention using state administrative data, which could aid providers in making better, data-informed decisions when weighing the medical benefits of opioid therapy against the risks.
5 citations
Posted Content•
TL;DR: In this article, the authors measure the impacts of removing children from families investigated for abuse or neglect using removal tendencies of child protection investigators as an instrument and find that removal significantly increases test scores and reduces grade repetition for girls.
Abstract: This paper measures impacts of removing children from families investigated for abuse or neglect. We use removal tendencies of child protection investigators as an instrument. We focus on young children investigated before age 6 and find that removal significantly increases test scores and reduces grade repetition for girls. There are no detectable impacts for boys. This pattern of results does not appear to be driven by heterogeneity in pre-removal characteristics, foster placements, or the type of schools attended after removal. The results are consistent with the hypothesis that development of abused and neglected girls is more responsive to home removal.
2 citations
Posted Content•
TL;DR: In this article, the effect of photo ID laws on voting using a difference-in-differences estimation approach around Rhode Island's implementation of a photo ID law was studied, using anonymized administrative data to measure the law's impact by comparing voting behavior among those with drivers' licenses versus those without.
Abstract: We study the effect of photo ID laws on voting using a difference-in-differences estimation approach around Rhode Island’s implementation of a photo ID law. We employ anonymized administrative data to measure the law’s impact by comparing voting behavior among those with drivers’ licenses versus those without, before versus after the law. Turnout, registration, and voting conditional on registration fell for those without licenses after the law passed. We do not find evidence that people proactively obtained licenses in anticipation of the law, nor do we find that they substituted towards mail ballots which do not require a photo ID.
1 citations