PANEL DATA MODELS WITH FINITE NUMBER OF MULTIPLE EQUILIBRIA
研究固定效应具有有限支撑的非线性面板数据模型，发现固定效应估计量的偶然参数问题不如传统情况严重，正确识别固定效应的概率随样本量增加趋近于1，有限样本偏差较小。
We study a nonlinear panel data model in which the fixed effects are assumed to have finite support. The fixed effects estimator is known to have the incidental parameters problem. We contribute to the literature by making a qualitative observation that the incidental parameters problem in this model may not be not as severe as in the conventional case. Because fixed effects have finite support, the probability of correctly identifying the fixed effect converges to one even when the cross sectional dimension grows as fast as some exponential function of the time dimension. As a consequence, the finite sample bias of the fixed effects estimator is expected to be small.