带异质线性趋势的动态二元选择面板模型估计

本文提出了带异质线性趋势的动态二元面板模型的极大似然偏误纠正估计量和近似条件Logit估计量。我们给出了通常极大似然估计量偏误的解析形式，并提供了相应的估计方法。小样本实验表明近似条件似然函数可以很好的消除异质性参数的影响，而偏误纠正估计量可以显著的修正极大似然估计量的偏误。最后我们将本文提出的方法应用到现金红利支付模型。

Estimation For Dynamic Binary Choice Panel Models with Heterogeneous Linear Trends

This article proposes bias correction estimators of MLE and approximate conditional logit estimators for dynamic binary choice models with heterogeneous linear trends. We obtain the analytical bias form of ordinary MLE and show how to estimate the bias. Small sample experiments show that approximate conditional likelihood function can eliminate the affects of heterogeneous parameters greatly, and the bias correction estimators can significantly reduce the bias of MLE. Finally these methods are applied to estimate the model of cash dividends payment.