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多维因子三维面板的CCE估计AI 解读

Abstract We consider the common correlated effects estimation of a three-dimensional panel data model with heterogeneous slope coefficients and multi-level interactive fixed effects. We study the asymptotic properties of the heterogeneous slope coefficient estimators and the mean group (MG) estimators. We find that bias correction is indispensable for the MG estimator and show that the MG estimators exhibit different convergence rates depending on the degree of heterogeneity…

Probit 回归中的强对数凹性AI 解读

Summary We show that strong log-concavity emerges in probit regression likelihoods without ridge penalization (i.e. Gaussian priors), unlike for the logistic case. Specifically, we provide: (a) a non-asymptotic characterization of strong log-concavity for fixed designs, similar to that for the existence of the maximum likelihood estimator (MLE) and (b) an asymptotic analysis for random designs, in the proportional regime when the sample size 𝑛 and the number of covariates…

基于多路离散化的交叉随机效应模型可扩展估计AI 解读

Cross-classified data frequently arise in scientific fields such as education, healthcare, and social sciences. A common modeling strategy is to introduce crossed random effects within a regression framework. However, this approach often encounters serious computational bottlenecks, particularly for non-Gaussian outcomes. In this paper, we propose a scalable and flexible method that approximates the distribution of each random effect by a discrete distribution, effectively…

随机实验中二元数据的因果推断AI 解读

Abstract Estimating treatment effects in networked settings is a central challenge in online controlled experiments, particularly on social media platforms. We investigate a scenario where the unit-level outcome of interest comprises a series of dyadic outcomes that record pairwise interactions between units, ranging from point-to-point messaging at the microscale to bilateral trade flows at the macroscale. Because the response is defined at the dyadic level, the treatment…

政党作为美国政治极化驱动因素：1927—2018AI 解读

The current polarization of elites in the U.S., particularly in Congress, is frequently ascribed to the emergence of cohorts of ideologically extreme legislators replacing moderate ones.Politicians, however, do not operate as isolated agents, driven solely by their preferences.They act within organized parties, whose leaders exert control over the rank-and-file, directing support for and against policies.This paper shows that the omission of party discipline as a driver of…

一类半参数多项选择模型的闭式估计量AI 解读

We consider a semiparametric multinomial choice model that allows for an arbitrary joint distribution of choice specific unobservables that are independent of explanatory variables. This model permits relatively flexible substitution patterns between choices. To minimize computational difficulties, we restrict attention on estimators of the model that can be expressed in closed form. We combine and extend various results from the existing literature to enforce economic…

POLAR：面向动态治疗方案的悲观模型型策略学习算法AI 解读

Dynamic treatment regimes (DTRs) provide a principled framework for optimizing sequential decision-making in domains where decisions must adapt over time in response to individual trajectories, such as healthcare, education, and digital interventions. However, existing statistical methods often rely on strong positivity assumptions and lack robustness under partial data coverage, while offline reinforcement learning approaches typically focus on average training performance,…

表观基因组全研究大规模因果中介检验的尾部似然比方法AI 解读

Large-scale mediation testing has attracted considerable attention in epigenome-wide studies, intending to determine whether the effect of an exposure on an outcome is mediated through specific DNA methylation sites. Statistical inference for the mediation effects is challenged by the complexity of testing a large number of composite null hypotheses. We propose a tail likelihood ratio (TLR) test that is robust to variations in the proportion of null cases, signal strength,…

检验阴性设计的敏感性分析AI 解读

The test-negative design has become popular for evaluating the effectiveness of post-licensure vaccines using observational data. In addition to its logistical convenience on data collection, the design is also believed to control for the differential health-care-seeking behavior between vaccinated and unvaccinated individuals, an important while often unmeasured confounder between the vaccination and infection. Hence, the design has been employed routinely to monitor…

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二元数据二次分配程序的渐近理论AI 解读

Abstract The quadratic assignment procedure (QAP) is a popular tool for analysing dyadic data in medical and social sciences. To test the association between 2 dyadic measurements represented by 2 symmetric matrices, QAP calculates the p-value by permuting the units, or equivalently, by permuting the rows and columns of 1 matrix in the same way. Its extension to the regression setting, known as the multiple regression QAP, has also gained popularity, especially in…

条件双样本检验的一般框架AI 解读

Abstract We study the problem of conditional two-sample testing, which aims to determine whether two populations have the same distribution after accounting for confounding factors. This problem commonly arises in various applications, such as domain adaptation and algorithmic fairness, where comparing two groups is essential while controlling for confounding variables. We begin by establishing a hardness result for conditional two-sample testing, demonstrating that no valid…

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时变面板数据模型中的潜在组结构估计AI 解读

Abstract We consider panel data models where coefficients change smoothly over time and follow a latent group structure, being homogeneous within but heterogeneous across groups. To jointly estimate the group memberships and group-specific coefficient trajectories, we propose FUSE-TIME, a pairwise adaptive group fused-Lasso estimator combined with polynomial spline sieves. We establish consistency, derive the asymptotic distributions of the penalized sieve estimator and its…

含生成回归元的半参数模型自助设定检验AI 解读

This article provides a specification test for semiparametric models with nonparametrically generated regressors. Such regressors are not observed by the researcher but are nonparametrically identified and estimable. Applications of the test include models with endogenous regressors identified by control functions, semiparametric sample selection models, or binary games with incomplete information. The statistic is built from the residuals of the semiparametric model. A…

何时不应将线性IV估计量解释为LATE？AI 解读

Abstract In this paper I revisit the interpretation of the linear instrumental variables (IV) estimand as a weighted average of conditional local average treatment effects (LATEs). I focus on a situation in which additional covariates are required for identification while the reduced-form and first-stage regressions may be misspecified due to an implicit homogeneity restriction on the effects of the instrument. I show that the weights on some conditional LATEs are negative…

Perturb-seq 中基于代理变量与工具变量的混杂稳健因果发现与推断AI 解读

Emerging single-cell technologies that combine CRISPR-based genetic perturbations with single-cell RNA sequencing, such as Perturb-seq, offer unprecedented opportunities to uncover cause-and-effect relationships among genes. Nonetheless, Perturb-seq experiments are subject to unobserved factors that, if not properly handled, can severely bias the inferred causal relationships between genes. These latent factors may arise not only from intrinsic molecular features of the…

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考虑人口流动的多变量连续处理空气污染研究中的空间干扰方法AI 解读

We develop new methodology to improve our understanding of the causal effects of multivariate air pollution exposures on public health accounting for mobility. Typically, in environmental health studies, exposure to air pollution for an individual is assigned based on their residential address, though many people spend time in different regions with potentially different levels of air pollution. To account for this, we incorporate estimates of the mobility of individuals…

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基于流行度回归的潜空间模型：大规模稀疏网络分析AI 解读

Degree heterogeneity is one of the most important properties of network data. It is widely observed that degree heterogeneity is often related to the nodal features. In this study, we investigate the estimation and statistical inference for a popularity regression-based latent space model with nodal features. Given the complex dependence structure induced by the latent space model, we aim to derive analytically tractable objective functions that effectively account for this…

盐税之重：榨取性财政制度的长期发展效应AI 解读

Abstract This paper exploits the historical system of salt taxation in France to study the impact of extractive taxes on long-term economic development. Salt tax rates exhibited significant spatial variation, leading to discontinuous jumps in salt prices. Adopting a spatial regression-discontinuity design, we estimate the causal effect of the tax using original historical data. We extract geolocalized individual-level information on almost 70 million individuals living near…

允许时间效应序列相关的双向聚类标准误AI 解读

Abstract We propose improved standard errors and an asymptotic theory for two-way clustered panels. Our theory allows for arbitrary serial dependence in the common time effects, which is excluded by existing two-way methods. Our asymptotic distribution theory is the first which allows for this level of interdependence. Under weak conditions, we demonstrate that OLS is asymptotically normal, our proposed variance estimator is consistent, and t-ratios are asymptotically…

存在部分服从者时完整处理效应的工具变量估计AI 解读

Abstract The effect of the full treatment is a primary parameter of interest in policy evaluation, while often the effect of a subset of treatment is estimated. We partially identify the local average treatment effect of receiving full treatment (LAFTE) using an instrumental variable that may induce individuals into subsets of treatment (partial compliers). We show that partial compliers violate the standard exclusion restriction, necessary conditions on the absence of…

内生性检验：一种基于矩的贝叶斯方法AI 解读

A standard assumption in the Bayesian estimation of linear regression models is that the regressors are exogenous in the sense that they are uncorrelated with the model error term. In practice, however, this assumption can be invalid. In this article, using the exponentially tilted empirical likelihood (ETEL) framework, we develop a Bayes factor test for endogeneity that compares a base model that is correctly specified under exogeneity but misspecified under endogeneity…

用匹配自适应随机化推断重新评估激素替代疗法对心脏病的影响AI 解读

Matching is an appealing way to design observational studies because it mimics the data structure produced by stratified randomized trials, pairing treated individuals with similar controls. After matching, inference is often conducted using methods tailored for stratified randomized trials in which treatments are permuted within matched pairs. However, in observational studies, matched pairs are not predetermined before treatment; instead, they are constructed based on…

We estimate wage cyclicality using the user cost of labor (UCL), a measure of marginal labor cost. We propose a novel methodology to correct composition bias from cyclical jobto-job upgrading by exploiting school-to-employment flows. We implement the methodology using rich Japanese wage data. The estimated UCL is strongly procyclical, with a semi-elasticity of 2.52 with respect to the unemployment rate, which is 1.6 and 2.3 times as large as that of the new-hire and average…