摘要翻译：
经验主义经济学家常常对固定效应二元选择模型的应用望而却步，主要有两个原因：附带的参数问题和即使在中等规模的面板中的计算挑战。以具有个体和时间固定效应的二元选择模型为例，我们说明了如何通过将渐近偏差校正与计算进展相结合来缓解这两个问题。由于不平衡性在实际工作中经常遇到，我们研究了它对各种偏差校正估计量的有限样本性质的影响。在模拟实验中，我们发现解析偏差校正性能特别好，而分裂面板折刀估计器在不平衡面板中可能会有严重的偏差。
---
英文标题：
《Fixed Effects Binary Choice Models: Estimation and Inference with Long
  Panels》
---
作者：
Daniel Czarnowske and Amrei Stammann
---
最新提交年份：
2020
---
分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
--

---
英文摘要：
  Empirical economists are often deterred from the application of fixed effects binary choice models mainly for two reasons: the incidental parameter problem and the computational challenge even in moderately large panels. Using the example of binary choice models with individual and time fixed effects, we show how both issues can be alleviated by combining asymptotic bias corrections with computational advances. Because unbalancedness is often encountered in applied work, we investigate its consequences on the finite sample properties of various (bias corrected) estimators. In simulation experiments we find that analytical bias corrections perform particularly well, whereas split-panel jackknife estimators can be severely biased in unbalanced panels.
---
PDF链接：
https://arxiv.org/pdf/1904.04217