每日简报

因果推断的干预得分几何AI 解读

Let $p(x)$ be the joint density of variables $X$, and let $ψ(x)=\nabla_x\log p(x)$ be its score field. Geometry constructed from $p$ and $ψ$ alone cannot identify causal direction: structural models with the same observational distribution have the same score geometry. I develop an interventional analogue. A hard intervention $\operatorname{do}(X_k=ξ)$ does not merely reweight the joint law; it restricts the distribution to the submanifold ${x_k=ξ}$. Its score should…

利用异方差神经网络学习双向因果交互AI 解读

Estimating contemporaneous bidirectional interactions from observational data is difficult because each outcome is endogenous to the other, while flexible regressions may capture only reduced-form dependence. This paper proposes SEM-DNN, a heteroscedastic neural simultaneous-equation estimator that learns reciprocal structural interactions without external instruments. Identification exploits conditional covariance diagonalization: when structural shocks have zero…

半参数推断的 V 折刀切法：方差、置信区间与同时置信带AI 解读

For decades, the bootstrap has been a default tool for statistical inference because of its broad applicability and minimal analytic requirements. Although its validity is well understood for smooth parametric estimators, its theoretical properties for many modern semiparametric and machine-learning estimators remain largely unstudied. Nevertheless, bootstrap procedures are often used routinely in such settings, even when their validity is unknown and their computational…

固定效应因果森林中的异质性衰减及交叉拟合校正AI 解读

Causal forests that estimate conditional average treatment effects by averaging honest leaf-level effects across trees are widely used in fixed-effects panel settings. We show that this averaging systematically attenuates the estimated heterogeneity: the raw prediction behaves like a + b*tau(x) with slope b < 1, so the spread of the CATEs is compressed toward the average effect, and the additive recentering used to report an unbiased average treatment effect does not fix it.…

非均匀簇期相关下多干预阶梯楔形试验的参数化时变效应框架AI 解读

Stepped wedge design (SWD) trials typically assume that treatment effects are immediate following implementation, but this assumption is often unrealistic in pragmatic settings where effects evolve over exposure time. This impact is further complicated in multiple-intervention stepped wedge designs (M-SWDs), due to their complex crossover patterns. Existing work has addressed time-varying treatment effects for main effects at the analysis stage using nonparametric…

CausalSmith：以形式化验证为基础的自我改进因果推断研究代理框架AI 解读

Automating theoretical research requires generating candidate results and evaluating them reliably. Models keep getting better at the first, while the second remains hard. A common approach asks one large language model (LLM) to review what another produced, yet such reviewers are empirically unreliable: they may accept fabricated papers and catch the fabrication at close to chance rates~\citep{badscientist2025}. We present \textsc{CausalSmith}, a framework for automated…

异质性同伴效应的识别AI 解读

We develop a model of peer effects where each peer has a separate effect depending on their rank in the distribution of peers' outcomes. Our model admits a unique equilibrium, and model parameters can be identified using peers' exogenous characteristics. To obtain a more parsimonious model of peer effects, we introduce a tractable specification based on quantile-dependent peer effect coefficients, and develop a specification test. Applying the model to several student…

处理选择与平行趋势AI 解读

We study the role of selection into treatment in difference-in-differences (DiD) designs. We derive necessary and sufficient conditions for parallel trends assumptions under general classes of selection mechanisms. These conditions characterize the empirical content of parallel trends and clarify the trade-offs between assumptions about selection into treatment and restrictions on the time series properties of the potential outcomes required for DiD methods. We use the…

多个误分类暴露的因果推断：控制变量调整的校准加权方法AI 解读

Exposure misclassification is a common issue prevalent in studies of respiratory infections in cystic fibrosis. Throat swabs are frequently used in place of expectorated or induced sputum cultures, although they have imperfect sensitivity and specificity to detect Pseudomonas aeruginosa and Staphylococcus aureus. We develop calibration weighting and control variate estimators for causal inference with multiple misclassified binary exposures and clustered observations. The…