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含不可观测个体特定阈值效应的面板阈值回归AI 解读

This paper provides a new approach to estimation and inference in multiple regime panel threshold regression with unobserved individual-specific threshold effects. Such effects are practically relevant and have features that distinguish them from traditional linear panel data models. It is shown that within-regime demeaning in the static model or within-regime first-differencing in the dynamic model both fail to deliver consistent threshold estimators. Instead, correlated…

存在内生性的门槛回归AI 解读

This paper studies estimation in threshold regression with endogeneity in the regressors and thresholding variable. Three key results differ from those in regular models. First, both the threshold point and the threshold effect parameters are shown to be identified without the need for instrumentation. Second, in partially linear threshold models, both parametric and nonparametric components rely on the same data, which prima facie suggests identification failure. But, as…

断点未知的断点回归设计：检验与估计AI 解读

The regression discontinuity design has become a common framework among applied economists for measuring treatment effects. A key restriction of the existing literature is the assumption that the discontinuity point is known, which does not always hold in practice. This paper extends the applicability of the regression discontinuity design by allowing for an unknown discontinuity point. First, we construct a unified test statistic to check whether there are selection or…