Orthogonal Parameters and Panel Data
提出一种针对短面板固定效应模型的一致估计方法，通过正交重参数化并积分掉新效应得到后验众数，该众数在模型中一致，尤其适用于一阶自回归模型。
This paper describes a class of consistent estimators for short panels with fixed effects. The method is to find an orthogonal reparametrization of the fixed effects and then to integrate the new effects from the likelihood with respect to an appropriately chosen prior density. The resulting marginal posterior densities of the common parameters have modes that are shown to be consistent in the models examined here. The main result concerns the first-order autoregressive model with agent specific intercepts where the likelihood is conditional on the set of initial observations. This paper provides a consistent likelihoodbased estimator for this model. Some numerical illustrations are given. The first-order conditions for the posterior mode can also be thought of as new moment conditions for GMM estimation. Copyright 2002, Wiley-Blackwell.