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Counts with an endogenous binary regressor: A series expansion approach

机译:用内生二进制回归数进行计数:序列扩展方法

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摘要

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.
机译:我们为计数数据回归模型提出了一个估计器,其中内生确定了二进制回归器。该估计器通过对计数的条件概率函数使用灵活形式来偏离先前的方法。通过使用蒙特卡洛实验,我们证明了我们的估计器与将均值限制为线性指数的替代方法相比,可以提高拟合度,并提供更可靠的回归变量对计数影响的估计。在一项针对美国家庭出行次数的应用中,我们发现,所获得的治疗效果的估算值与线性指数平均规格下获得的估算效果有很大不同。

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