Understanding Bias in Nonlinear Panel Models: Some Recent Developments ∗
Understanding Bias in Nonlinear Panel Models: Some Recent Developments ∗
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DOI：
10.1017/cbo9780511607547.013
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发表时间：
2005-10
期刊：
影响因子：
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通讯作者：
M. Arellano;J. Hahn
中科院分区：
文献类型：
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作者：
M. Arellano;J. Hahn
本文的目的是回顾最近发展的非线性固定效应面板数据模型的估计方法，减少偏差的性质。我们开始描述固定效应估计和附带参数问题。接下来，我们解释如何构建估计量的分析偏差校正，其次是矩方程的偏差校正，以及集中似然的偏差校正。然后，我们转向讨论其他方法导致偏置校正的基础上正交化及其扩展。其余部分考虑动态模型的准最大似然估计，边际效应的估计和基于模拟的自动方法。
The purpose of this paper is to review recently developed methods of estimation of nonlinear fixed effects panel data models with reduced bias properties. We begin by describing fixed effects estimators and the incidental parameters problem. Next we explain how to construct analytical bias correction of estimators, followed by bias correction of the moment equation, and bias corrections for the concentrated likelihood. We then turn to discuss other approaches leading to bias correction based on orthogonalization and their extensions. The remaining sections consider quasi maximum likelihood estimation for dynamic models, the estimation of marginal effects, and automatic methods based on simulation.