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动态处理分配AI 解读

We discuss estimation of treatment effects when the timing of treatment is the outcome of a stochastic process. We show that the duration framework in discrete time provides a fertile ground for effect evaluations. We suggest easy-to-use nonparametric survival function matching estimators that can be used to estimate the time profile of the treatment.We study the small-sample properties of the proposed estimators and apply one of them to evaluate the effects of an employment…

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基于级数展开的计数数据回归及其应用AI 解读

A new class of parametric regression models for both under- and over-dispersed count data is proposed. These models are based on squared polynomial expansions around a Poisson baseline density. The approach is similar to that for continuous data using squared Hermite polynomials proposed by Gallant and Nychka and applied to financial data by, among others, Gallant and Tauchen. The count models are applied to underdispersed data on the number of takeover bids received by…