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含未观测随机动态效应的非线性时间序列与面板模型的拉普拉斯变换识别AI 解读

We consider nonlinear parametric and semi-parametric models for time series and panel data including unobserved dynamic effects. These regression models have an affine specification with respect to lagged endogenous variables and unobserved dynamic effects. We derive conditional moment restrictions based on suitable Laplace transforms. We show how to deploy these nonlinear moment restrictions to identify the parameters of the affine regression model, and the parametric or…

动态面板模型的间接推断AI 解读

Maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with fixed effects is inconsistent under fixed time series sample size and large cross section sample size asymptotics. This paper proposes a general, computationally inexpensive method of bias reduction that is based on indirect inference, shows unbiasedness and analyzes efficiency. Monte Carlo studies show that our procedure achieves substantial bias reductions with only mild…

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