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含交互固定效应的面板模型的剖面 GMM 估计AI 解读

This paper studies panel data models with interactive fixed effects where the regressors are allowed to be correlated with the idiosyncratic error terms. We propose a two-step profile GMM estimation procedure to estimate the parameters of interest. In the first step we obtain a preliminary consistent estimate of the slope coefficient via a nuclear-norm-regularization (NNR) based profile GMM procedure. In the second step, via an iterative procedure, we conduct post-NNR…

名义分组间部分测量潜在特质的比较AI 解读

This article presents a method for estimating the subgroup distributions of a latent trait measured as a normal variate in the population. This problem occurs in large-scale assessments, such as the National Assessment of Educational Progress, the National Adult Literacy Survey, and other programs where proficiencies are estimated via marginal maximum likelihood through a model based on item-response theory. Heretofore, estimates of subgroup means were often estimated using…

不同类别子群间部分测量潜在特质的比较AI 解读

This article presents a method for estimating the subgroup distributions of a latent trait measured as a normal variate in the population. This problem occurs in large-scale assessments, such as the National Assessment of Educational Progress, the National Adult Literacy Survey, and other programs where proficiencies are estimated via marginal maximum likelihood through a model based on item-response theory. Heretofore, estimates of subgroup means were often estimated using…