英文文献：Semiparametric Estimation of Dynamic Binary Choice Panel Data Models-动态二元选择面板数据模型的半参数估计
英文文献作者：Fu Ouyang,Thomas Tao Yang
英文文献摘要：
We propose a new approach to the semiparametric analysis of panel data binary choice models with fixed effects and dynamics (lagged dependent variables). The model we consider has the same random utility framework as in Honore and Kyriazidou ?? (2000). We demonstrate that, with additional serial dependence conditions on the process of deterministic utility and tail restrictions on the error distribution, the (point) identification of the model can proceed in two steps, and only requires matching the value of an index function of explanatory variables over time, as opposed to that of each explanatory variable. Our identification approach motivates an easily implementable, two-step maximum score (2SMS) procedure ??“ producing estimators whose rates of convergence, in contrast to Honore and Kyriazidou ?? ???s (2000) methods, are independent of the model dimension. We then derive the asymptotic properties of the 2SMS procedure and propose bootstrap-based distributional approximations for inference. Monte Carlo evidence indicates that our procedure performs adequately in finite samples. We then apply the proposed estimators to study labor market dependence and the effects of health shocks, using data from the Household, Income and Labor Dynamics in Australia (HILDA) survey.

我们提出了一种新的半参数分析方法的面板数据二元选择模型的固定效应和动态(滞后因变量)。我们考虑的模型具有与Honore和Kyriazidou A’(2000)中相同的随机效用框架。我们表明,额外的串行依赖条件的过程中确定的效用和尾巴限制误差分布,模型的(点)识别可以在两个步骤进行,和只需要匹配索引价值的解释变量的函数随着时间的推移,相对于每个解释变量。与Honore和Kyriazidou a’a??s(2000)方法相比，我们的识别方法激发了一种易于实现的两步最高评分(2SMS)过程，即产生一种评估器，其收敛率独立于模型维数。然后我们推导了2SMS过程的渐近性质，并提出了基于bootstrap的分布近似来进行推理。蒙特卡洛的证据表明，我们的程序在有限的样本中执行得很好。然后，我们使用来自澳大利亚家庭、收入和劳动力动态(HILDA)调查的数据，应用所提出的估计器来研究劳动力市场依赖和健康冲击的影响。