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Abstract We study the health impacts of job loss and unemployment insurance (UI) among Brazilian workers, using unique administrative data linking employment, hospitalizations, health insurance, and mortality records over 17 years. Leveraging mass layoffs for identification, we find that job loss raises hospitalization (+33%) and mortality (+23%) risks for men, with no significant effects for women. Impacts are pervasive across age, income, and education levels, with…

断点回归设计中的灵活协变量调整AI 解读

Empirical regression discontinuity (RD) studies often include covariates in their specifications to increase the precision of their estimates. In this paper, we propose a novel class of estimators that use such covariate information more efficiently than existing methods and can accommodate many covariates. Our estimators are simple to implement and involve running a standard RD analysis after subtracting a function of the covariates from the original outcome variable. We…

回归不连续效应及其外部有效性的联合推断AI 解读

ABSTRACT The external validity of regression discontinuity designs is crucial for informing policy but is rarely examined in applied work. To advance empirical practice, we propose a joint inference procedure for the treatment effect and its local external validity, captured by the treatment effect derivative (TED), within a robust bias correction framework. We further introduce a locally linear treatment effects assumption, which extends the scope of the TED and enables…

We study the impact of financial aid on upward mobility. We estimate the causal impacts of a Colombian policy targeting high-achieving, low-socioeconomic-status students on later-life educational and labor market outcomes. Using regression discontinuity design, difference-in-differences, and population-wide administrative microdata, we find that the policy boosted attendance and completion at high-value-added colleges, particularly in STEM fields. Improved college quality…

This study investigates how financial literacy shapes the propensity of individuals to commit financial crime. Using state-level administrative data on criminal charges linked to comprehensive public records , we exploit a policy-based discontinuity in grade level assignment based on individual birth dates that exogenously requires certain high school cohorts to attend a financial literacy course. Our estimates suggest that exposure to the course reduces the propensity to…

Abstract This paper asks whether increasing public school funding can be an effective long-run crime-prevention strategy in the United States. Specifically, we examine the effect of increases in funding early in children’s lives on the likelihood that they are arrested as adults. We exploit quasi-experimental variation in public school funding, leveraging two natural experiments in Michigan and a novel administrative data set linking the universe of Michigan public school…

Abstract We examine firm responses to state hiring and investment subsidies. We leverage institutional features of the California Competes Tax Credit (CCTC), a large-scale business incentive program that incorporates best practices from prior job creation policies. The CCTC award selection procedure combines formula-based and discretionary components. Leveraging applicant score eligibility cutoffs in a regression discontinuity design and taking advantage of rich longitudinal…

Abstract We quantify micro and macro effects of changes in the potential benefit duration (PBD) in unemployment insurance. In Poland, the PBD is 12 months for the newly unemployed if the previous year’s county unemployment rate is more than 150% of the national average, and 6 months otherwise. We exploit this cut-off using regression discontinuity estimates on registry data containing the universe of unemployed from 2005 to 2019. For those whose PBD is directly affected by…

内生性下的极端分位数处理效应AI 解读

We introduce a novel method for estimating and conducting inference about extreme quantile treatment effects (QTEs) in the presence of endogeneity. Our approach is applicable to a broad range of empirical research designs, including instrumental variables design and regression discontinuity design, among others. By leveraging regular variation and subsampling, the method ensures good performance even in extreme tails, where data may be sparse. Simulation studies confirm the…

Abstract This paper examines how politically connected firms shape housing supply in U.S. cities. Using new data on campaign donations to U.S. mayors and a regression discontinuity design, I present three findings. First, developers connected to the mayor sell more new housing units. Second, more sales of new housing by connected developers coincide with higher local housing supply: cities where mayors received more developer donations issue nearly 70 percent more permits…

学校选择中的非参数处理效应识别AI 解读

This paper studies nonparametric identification and estimation of causal effects in centralized school assignment. In many centralized assignment algorithms, students face both lottery-driven variation and regression discontinuity- (RD) driven variation. We characterize the full set of identified atomic treatment effects (aTEs), defined as the conditional average treatment effect between a pair of schools given student characteristics. Atomic treatment effects are the…

可能包含大量协变量的断点回归设计AI 解读

This article examines high-dimensional covariates in regression discontinuity design (RDD) analysis. We introduce estimation and inference methods for the RDD models that incorporate covariate selection while maintaining stability across various numbers of covariates. The proposed methods combine a localization approach using kernel weights with $\ell _{1}$ -penalization to handle high-dimensional covariates. We provide both theoretical and numerical evidence demonstrating…

Abstract We estimate impacts of male job loss, female job loss, and male unemployment benefits on domestic violence (DV) in Brazil. We merge individual-level employment and welfare registers with different measures of DV: judicial cases brought to criminal courts, the use of public shelters by victims, and mandatory DV notifications by health providers. Leveraging mass layoffs for identification, we first show that both male and female job loss, independently, lead to large,…

Abstract Using administrative data and a regression discontinuity design, we study the labor market effects of a government-sponsored award given to top-performing students on Colombia’s national college exit exam. The award signals field-specific skills, leading recipients to earn seven to ten percent more than comparable peers without the signal. The benefits are concentrated among graduates from lowerreputation institutions, who enter the market with weaker signals and…

Abstract In most national elections, voters face a key choice between continuity and change. Electoral turnovers occur when the incumbent candidate or party fails to win reelection. To understand how turnovers affect national outcomes, we study all presidential and parliamentary elections held globally between 1946 and 2018. We document the prevalence of turnovers over time and estimate their effects on economic performance, human development, and the quality of democracy.…

回归不连续设计的统一诊断检验AI 解读

Diagnostic tests for regression discontinuity design face a size-control problem. We document a massive over-rejection of the diagnostic restriction among empirical studies in the top five economics journals. At least one diagnostic test was rejected for 19 out of 59 studies, whereas less than 5% of the collected 787 tests rejected the null hypotheses. In other words, one-third of the studies rejected at least one of their diagnostic tests, whereas their underlying…

多维断点回归设计的操纵检验AI 解读

ABSTRACT The causal inference model for the regression discontinuity design (RDD) relies on assumptions that imply the continuity of the density of the assignment (running) variable. The test for this implication is commonly referred to as the manipulation test and is regularly reported in applied research to strengthen the design's validity. The multidimensional RDD (MRDD) extends the RDD to contexts where treatment assignment depends on several running variables. This…

断点回归设计中由噪声诱导的随机化AI 解读

Summary Regression discontinuity designs assess causal effects in settings where treatment is determined by whether an observed running variable crosses a prespecified threshold. Here, we propose a new approach to identification, estimation and inference in regression discontinuity designs that uses knowledge about exogenous noise (e.g., measurement error) in the running variable. In our strategy, we weight treated and control units to balance a latent variable, of which the…

含协变量的秩相似分位数断点回归：识别与推断AI 解读

This study investigates the identification and inference of quantile treatment effects (QTEs) in a fuzzy regression discontinuity (RD) design under rank similarity . Unlike Frandsen et al. (2012, Journal of Econometrics 168, 382–395), who focus on QTEs only for the compliant subpopulation, our approach can identify QTEs and average treatment effect for the whole population at the threshold. We derived a new set of moment restrictions for the RD model by imposing a local rank…

Abstract The economic and social integration of refugees is a key policy concern and the situation of refugee women is particularly challenging, as many never enter the labor force. We study a reform of the Swedish integration program designed to tackle this issue by increasing women's participation in and access to active labor market programs. Using administrative data and a regression discontinuity design, we show that the reform resulted in lasting improvements in…

帮派、劳动流动与发展AI 解读

We study how criminal organizations affect economic development. We exploit a natural experiment in El Salvador, where these criminal organizations emerged due to an exogenous shift in American immigration policy that led to the deportation of gang leaders from the United States to El Salvador. Using a spatial regression discontinuity design that focuses on the gang‐created system of borders, we find that individuals in gang‐controlled neighborhoods have less material…

让补贴发挥作用：规则与自由裁量AI 解读

We estimate the employment effects of a large program of public investment subsidies to private firms that ranked applicants on a score reflecting both objective rules and local politicians' discretion. Leveraging the rationing of funds as an ideal Regression Discontinuity Design, we characterize the heterogeneity of treatment effects and cost‐per‐new‐job across inframarginal firms and estimate the cost‐effectiveness of subsidies under factual and counterfactual allocations.…

Abstract We leverage the discontinuity in the assignment mechanism of the Small and Medium Enterprise Instrument—the first European research and development (R&D) subsidy targeting small firms—to provide the broadest quasi-experimental evidence on R&D grants over both geographical and sectoral scopes. Grants trigger sizable impacts on a wide range of firm-level outcomes. Heterogeneous effects are consistent with grants reducing financial frictions. This reduction is due to…

The editors1 of The Econometrics Journal decided to award the 2023 Denis Sargan Econometrics Prize to Alexander Kreiss (Leizpig University) for his article “Inference in regression discontinuity designs with high-dimensional covariates” with Christoph Rothe in the May 2023 issue of The Econometrics Journal.2 The regression-discontinuity approach can be used to learn about the causal effects of a binary treatment (e.g. enrolment in an educational program) that is fully…