每日简报

当处理发生溢出：时空因果效应估计的神经网络框架AI 解读

Real-world public health policies are often enacted by local jurisdictions, but their effects can ripple through connected populations. For causal evaluation, this creates a difficult spatiotemporal problem: intermittent policy updates create path-level treatments, and because spillover depends on neighboring treatment paths along with the focal-unit's own history, controlling time-varying confounding requires high-dimensional, multimodal information from both sources. To…

TMLE 与 AIPW 中样本分割选择何时重要：交叉拟合、目标化与重复AI 解读

Variants of targeted maximum likelihood estimation (TMLE) and augmented inverse-probability weighting (AIPW) with machine-learning nuisance models differ in which observations train them, how bias is corrected, and whether splits are repeated. In known-truth simulations of a binary-outcome average treatment effect, eight headline estimators shared each setting's library, inner folds and truncation bound; coverage differences were judged against a prespecified…

理性疏忽—加性随机效用模型的估计AI 解读

This paper develops likelihood-based estimation for parametric rational inattention--additive random utility models. We establish consistency and asymptotic normality of the exact maximum likelihood estimator and provide conditions under which the simulated estimator shares its asymptotic distribution. To implement estimation, we develop Newton--BA, a KKT-guided hybrid of Newton--Raphson and Blahut--Arimoto (BA). The algorithm accommodates both interior and boundary…

伪面板事件研究：可信应用的计量经济学基础AI 解读

Event studies with panel data are widely used to estimate treatment effects. With repeated cross-sections, future treatment dates are unobserved for untreated individuals. Pseudo-panel event studies impute pre-treatment outcomes of the treated using matched untreated individuals. This paper establishes identification in such designs and characterizes bias when identification conditions fail. I show that the pseudo-panel regression is equivalent to weighted least squares with…

动态面板多项Logit模型AI 解读

This paper provides moment conditions for dynamic multinomial logit panel data models with individual specific fixed effects. The moment conditions do not depend on the fixed effects and thus form the basis for generalized method of moments estimation. For a leading case, we provide sufficient conditions under which the moment conditions identify the common parameters, and we illustrate their use in an empirical application to household soft drink purchases. The construction…

We study difference-in-differences designs in which all units are initially untreated and later receive heterogeneous, strictly positive treatment doses. When quasi-untreated units receive doses close to zero, a difference-in-difference estimand using those units as the control group identifies a weighted average treatment effect per unit of treatment, under a parallel-trends assumption. We develop a nonparametric estimator and bias-corrected confidence intervals for this…

Under i.i.d. sampling, the maximum score estimator of Manski (1975) converges at the cube-root rate to a non-Gaussian limit. We show that, under multiway dependence and low-level conditions, it is asymptotically normal at a parametric rate in the smallest number of clusters and, when the cluster-level variance is non-degenerate, as fast as regular estimators such as probit. The result rests on a general theory for non-smooth M-estimators, under which a modified bootstrap is…