Estimating Nonlinear Models with Multiple Fixed Effects: A Computational Note*
提出一种简单变形的偏差校正估计量，利用固定效应的可加性进行数值优化，以解决含多个个体固定效应的非线性面板数据模型估计中系数多、时间维度短导致的偶然参数问题。
Abstract In this paper we consider estimation of nonlinear panel data models that include multiple individual fixed effects. Estimation of these models is complicated both by the difficulty of estimating models with possibly thousands of coefficients and also by the incidental parameters problem; that is, noisy estimates of the fixed effects when the time dimension is short contaminate the estimates of the common parameters due to the nonlinearity of the problem. We propose a simple variation of existing bias‐corrected estimators, which can exploit the additivity of the effects for numerical optimization. We exhibit the performance of the estimators in simulations.