Counts with an endogenous binary regressor: A series expansion approach
Counts with an endogenous binary regressor: A series expansion approach
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使用内生二元回归器进行计数：级数展开方法
DOI：
10.1111/j.1368-423x.2005.00148.x
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发表时间：
2005
影响因子：
1.9
通讯作者：
M. Vera
中科院分区：
文献类型：
--
作者：
Andrés Romeu;M. Vera
我们提出了计数数据回归模型的估计量，其中二元回归量是内生决定的。该估计器与以前的方法不同，它使用了计数的条件概率函数的灵活形式。使用蒙特卡罗实验，我们表明，与将平均值限制为线性指数的替代方案相比，我们的估计器改善了拟合，并提供了对回归量对计数影响的更可靠的估计。在对美国家庭旅行次数的应用中，我们发现所获得的处理效果的估计与在线性指数平均规范下获得的估计有很大不同。
We propose an estimator for count data regression models where a binary regressor is endogenously determined. This estimator departs from previous approaches by using a flexible form for the conditional probability function of the counts. Using a Monte Carlo experiment we show that our estimator improves the fit and provides a more reliable estimate of the impact of regressors on the count when compared to alternatives which do restrict the mean to be linear-exponential. In an application to the number of trips by households in the United States, we find that the estimate of the treatment effect obtained is considerably different from the one obtained under a linear-exponential mean specification.
影响因子：
6.1
作者：
GALLANT, AR;NYCHKA, DW
通讯作者：
NYCHKA, DW