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强度变化的重复处理下的工具变量回归AI 解读

Instrumental variable models with repeated endogenous treatments are popular in empirical research using pooled cross-sectional or short panel datasets. This paper proposes a novel semi-parametric approach that explicitly considers 1) path dependency in the contemporaneous treatment effect and 2) a direct carryover effect from past treatments. We demonstrate that when either of these new features is present, the standard two-stage least squares estimator is generally…

存在第一阶段异质性的工具变量估计AI 解读

We propose a simple data-driven procedure that exploits heterogeneity in the first-stage correlation between an instrument and an endogenous variable to improve the asymptotic mean squared error (MSE) of instrumental variable estimators. We show that the resulting gains in asymptotic MSE can be quite large in settings where there is substantial heterogeneity in the first-stage parameters. We also show that a naive procedure used in some applied work, which consists of…

处理效应异质性下的动态断点回归AI 解读

Regression discontinuity is a popular tool for analyzing economic policies or treatment interventions. This research extends the classic static RD model to a dynamic framework, where observations are eligible for repeated RD events and, therefore, treatments. Such dynamics often complicate the identification and estimation of long‐term average treatment effects. Empirical papers with such designs have so far ignored the dynamics or adopted restrictive identifying…

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…

断点回归设计中的处理效应异质性检验AI 解读

Treatment effect heterogeneity is frequently studied in regression discontinuity (RD) applications. This paper proposes, under the RD setup, formal tests for treatment effect heterogeneity among individuals with different observed pre-treatment characteristics. The proposed tests study whether a policy treatment (1) is beneficial for at least some subpopulations defined by pre-treatment covariate values, (2) has any impact on at least some subpopulations, and (3) has a…

分布偏效应的估计与推断：理论及应用AI 解读

This article considers nonparametric and semiparametric estimation and inference of the effects of a covariate, either discrete or continuous, on the conditional distribution of a response outcome. It also proposes various uniform tests following estimation. This type of analysis is useful in situations where the econometrician or policy-maker is interested in knowing the effect of a variable or policy on the whole distribution of the response outcome conditional on…

Economists are often interested in identifying effective policies or treatments together with subpopulations of individuals who respond positively (or with a sign that is expected) to these treatment interventions. In this paper, we propose an optimal false discovery rate controlling method that is especially useful for such one‐sided testing problems. The proposed procedure is optimal in the sense of minimizing the false non‐discovery rate while controlling the false…

两样本工具变量回归中的弱工具稳健推断AI 解读

Summary Instrumental variable (IV) methods for regression are well established. More recently, methods have been developed for statistical inference when the instruments are weakly correlated with the endogenous regressor, so that estimators are biased and no longer asymptotically normally distributed. This paper extends such inference to the case where two separate samples are used to implement instrumental variables estimation. We also relax the restrictive assumptions of…

This paper proposes consistent testing methods for examining the effect of a policy treatment on the whole distribution of a response outcome within the setting of a regression discontinuity design. These methods are particularly useful when a policy is expected to produce treatment effects that are heterogeneous along some unobserved characteristics. The test statistics are Kolmogorov-Smirnov-type and are asymptotically distribution free when the data are i.i.d. The…

具有斜率异质性的删失面板数据模型估计AI 解读

SUMMARY This paper considers estimation of censored panel‐data models with individual‐specific slope heterogeneity. The slope heterogeneity may be random (random slopes model) or related to covariates (correlated random slopes model). Maximum likelihood and censored least‐absolute deviations estimators are proposed for both models. The estimators are simple to implement and, in the case of maximum likelihood, lead to straightforward estimation of partial effects. The…