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巴西失业与失业保险对犯罪的影响AI 解读

We investigate the impact of job loss on crime and the mitigating role of unemployment benefits, exploiting detailed individual‐level data linking employment careers, criminal records, and welfare registries for the universe of male workers in Brazil. The probability of committing crimes increases on average by 23% for workers displaced by mass layoffs, and by slightly less for their cohabiting sons. Using causal forests, we show that the effect is entirely driven by young…

打破同序：回归不连续设计与市场设计的结合AI 解读

Many schools in large urban districts have more applicants than seats. Centralized school assignment algorithms ration seats at over‐subscribed schools using randomly assigned lottery numbers, non‐lottery tie‐breakers like test scores, or both. The New York City public high school match illustrates the latter, using test scores and other criteria to rank applicants at the city's screened schools, combined with lottery tie‐breaking at the rest. We show how to identify causal…

模糊断点回归识别假设的检验AI 解读

We propose a new specification test for assessing the validity of fuzzy regression discontinuity designs (FRD‐validity). We derive a new set of testable implications, characterized by a set of inequality restrictions on the joint distribution of observed outcomes and treatment status at the cut‐off. We show that this new characterization exploits all of the information in the data that is useful for detecting violations of FRD‐validity. Our approach differs from and…

We study the causal effect of incarceration on reoffending using discontinuities in North Carolina’s sentencing guidelines. A regression discontinuity analysis shows that 1 year of incarceration causes a reduction in the likelihood of being reincarcerated within 3, 5, and 8 years from sentencing by 44%, 29%, and 21%, respectively. To parse the potentially heterogeneous dose response relationship underlying these effects, we develop an econometric model of prison sentences…

多阈值回归不连续设计中的处理效应外推AI 解读

In non-experimental settings, the Regression Discontinuity (RD) design is one of the most credible identification strategies for program evaluation and causal inference. However, RD treatment effect estimands are necessarily local, making statistical methods for the extrapolation of these effects a key area for development. We introduce a new method for extrapolation of RD effects that relies on the presence of multiple cutoffs, and is therefore design-based. Our approach…

Environmental markets are widely prescribed as an alternative to open access regimes for natural resources. We develop a model of dynamic groundwater extraction to demonstrate how a spatial regression discontinuity design that exploits a spatially incomplete market for groundwater rights recovers a lower bound on the market’s net benefit. We apply this estimator to a major aquifer in water-scarce southern California and find that a groundwater market generated substantial…

运行变量存在组别特定测量误差时的断点回归校正AI 解读

When the running variable in a regression discontinuity (RD) design is measured with error, identification of the local average treatment effect of interest will typically fail. While the form of this measurement error varies across applications, in many cases the measurement error structure is heterogeneous across different groups of observations. We develop a novel measurement error correction procedure capable of addressing heterogeneous mismeasurement structures by…

Africa’s demand for urban housing is soaring, even as it faces a proliferation of slums. In this setting, can modest infrastructure investments in greenfield areas where people subsequently build their own houses facilitate long-run neighborhood development? We study Sites and Services projects implemented in seven Tanzanian cities during the 1970s and 1980s, and we use a spatial regression discontinuity design to compare greenfield areas that were treated (de novo) with…

回归不连续设计下条件处理效应的单调性检验AI 解读

Summary Researchers are often interested in the relationship between treatment effects and observed individual heterogeneity. This paper proposes the first nonparametric monotonicity test for conditional treatment effects under the popular regression discontinuity framework. The proposed test examines whether the average treatment effect or the local average treatment effect has a monotonic relationship with some of the observed individual characteristics. We show…

回归不连续设计中基于 g 阶序统计量的密度连续性检验AI 解读

In the regression discontinuity design (RDD), it is common practice to assess the credibility of the design by testing the continuity of the density of the running variable at the cut-off, e.g., McCrary (2008). In this paper we propose an approximate sign test for continuity of a density at a point based on the so-called g-order statistics, and study its properties under two complementary asymptotic frameworks. In the first asymptotic framework, the number q of observations…

回归折点设计中的分位数处理效应AI 解读

The literature on regression kink designs develops identification results for average effects of continuous treatments (Nielsen et al., 2010, American Economic Journal: Economic Policy 2, 185–215; Card et al., 2015, Econometrica 83, 2453–2483), average effects of binary treatments (Dong, 2018, Jump or Kink? Identifying Education Effects by Regression Discontinuity Design without the Discontinuity), and quantile-wise effects of continuous treatments (Chiang and Sasaki, 2019,…

基于最小对比的密度不连续性经验似然推断AI 解读

This article investigates the asymptotic properties of a simple empirical-likelihood-based inference method for discontinuity in density. The parameter of interest is a function of two one-sided limits of the probability density function at (possibly) two cut-off points. Our approach is based on the first-order conditions from a minimum contrast problem. We investigate both first-order and second-order properties of the proposed method. We characterize the leading coverage…

回归不连续设计、白噪声模型与极小极大理论AI 解读

This paper studies an approximation of sharp regression discontinuity (RD) designs with normal homoskedastic errors by ideal Gaussian white noise models with discontinuous drifts. After establishing an asymptotic equivalence of the two models, we first provide a simple derivation of a lower bound on the minimax optimal convergence rate for estimating the discontinuity size in a derivative (of an arbitrary order) of the regression function. We show that the optimal…

存在干扰参数时的局部回归推断AI 解读

We consider inference based on local estimating equations in the presence of nuisance parameters. The framework is useful for a number of applications including those in economic policy evaluation based on discontinuities or kinks and in real-time financial risk management. We focus on the criterion-function-based (in particular, empirical likelihood-based) inference, and establish conditions under which the test statistic has a pivotal asymptotic distribution. In the key…

The likelihood of seasoned equity offerings (SEOs) jumps discontinuously when the stock price equals the most recent equity offer price. Anchoring on the last offer price holds after considering executive turnovers, stock splits, earnings management, or dividend adjustments. Using a fuzzy regression discontinuity design around this cutoff, which exploits local randomness in stock prices, we investigate the consequences of anchoring in SEOs. We find significant increases in…

具有多个阈值的回归不连续设计AI 解读

Numerous empirical studies employ regression discontinuity designs with multiple cutoffs and heterogeneous treatments. A common practice is to normalize all the cutoffs to zero and estimate one effect. This procedure identifies the average treatment effect (ATE) on the observed distribution of individuals local to existing cutoffs. However, researchers often want to make inferences on more meaningful ATEs, computed over general counterfactual distributions of individuals,…

简便的局部多项式密度估计量AI 解读

This paper introduces an intuitive and easy-to-implement nonparametric density estimator based on local polynomial techniques. The estimator is fully boundary adaptive and automatic, but does not require pre-binning or any other transformation of the data. We study the main asymptotic properties of the estimator, and use these results to provide principled estimation, inference, and bandwidth selection methods. As a substantive application of our results, we develop a novel…

模糊回归不连续设计的外部有效性AI 解读

Fuzzy regression discontinuity designs identify the local average treatment effect (LATE) for the subpopulation of compliers, and with forcing variable equal to the threshold. We develop methods that assess the external validity of LATE to other compliance groups at the threshold, and allow for identification away from the threshold. Specifically, we focus on the equality of outcome distributions between treated compliers and always-takers, and between untreated compliers…

This paper examines how housing market distress affects job search. Using data from a leading online job search platform during the Great Recession, we find that job seekers in areas with depressed housing markets apply for fewer jobs that require relocation. With their search constrained geographically, job seekers broaden their search for lower-level positions nearby. These effects are stronger for job seekers with recourse mortgages, which we confirm using a spatial…

Summary This paper develops a novel wild bootstrap procedure to construct robust bias-corrected valid confidence intervals for fuzzy regression discontinuity designs, providing an intuitive complement to existing robust bias-corrected methods. The confidence intervals generated by this procedure are valid under conditions similar to the procedures proposed by Calonico et al. (2014) and related literature. Simulations provide evidence that this new method is at least as…

Summary Modern empirical work in regression discontinuity (RD) designs often employs local polynomial estimation and inference with a mean square error (MSE) optimal bandwidth choice. This bandwidth yields an MSE-optimal RD treatment effect estimator, but is by construction invalid for inference. Robust bias-corrected (RBC) inference methods are valid when using the MSE-optimal bandwidth, but we show that they yield suboptimal confidence intervals in terms of coverage error.…

Conventional wisdom suggests that labor unions raise worker wages, while the newer empirical literature finds only negligible earnings effects. I reconcile this apparent contradiction by arguing that collective bargaining targets fringe benefits. Using U.S. firm-level data from the Bureau of Economic Analysis (BEA) Multinational Enterprise Survey and Compustat, I exploit a regression discontinuity in majority rule union elections to compare changes in employee compensation…

ABSTRACT We study temporary fiscal stimulus designed to support distressed housing markets by inducing demand from buyers in the private market. Using difference‐in‐differences and regression kink research designs, we find that the First‐Time Homebuyer Credit increased home sales by 490,000 (9.8%), median home prices by $2,400 (1.1%) per standard deviation increase in program exposure, and the transition rate into homeownership by 53%. The policy response did not reverse…

Exploiting admission thresholds to the Bologna day care system, we show using a regression discontinuity (RD) design that one additional day care month at age 0–2 reduces intelligence quotient by 0.5% (4.7% of a standard deviation) at age 8–14 in a relatively affluent population. The magnitude of this negative effect increases with family income. Similar negative impacts are found for personality traits. These findings are consistent with the hypothesis from psychology that…