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本库首次提交范围:2004-06-23 — 2026-10-14。
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Identification and Estimation of Average Causal Effects in Fixed Effects Logit Models

短面板固定效应 Logit 模型中平均因果效应的识别与估计

This paper studies identification and estimation of average causal effects, such as average marginal or treatment effects, in fixed effects logit models with short panels. Relating the identified set of these effects to an extremal moment problem, we first show how to obtain sharp bounds on such effects simply, without any optimization. We also consider even simpler outer bounds, which, contrary to the sharp bounds, do not require any first-step nonparametric estimators. We…

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Estimating Stochastic Block Models in the Presence of Covariates

含协变量的随机块模型估计

In the standard stochastic block model for networks, the probability of a connection between two nodes, often referred to as the edge probability, depends on the unobserved communities each of these nodes belongs to. We consider a flexible framework in which each edge probability, together with the probability of community assignment, are also impacted by observed covariates. We propose a computationally tractable two-step procedure to estimate the conditional edge…

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