A New Estimator for Panel Data Sample Selection Models
A New Estimator for Panel Data Sample Selection Models
复制标题
面板数据样本选择模型的新估计器
DOI：
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
M. E. Rochina
中科院分区：
文献类型：
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作者：
M. E. Rochina
本文研究了一个面板数据样本选择模型的估计问题，其中样本选择和回归方程都包含允许与可观测变量相关的个体效应。在这个方向上，最近已经开发了一些估计技术。我们提出了一种新的方法来纠正样本选择偏差。我们的估计过程是一个扩展的熟悉的两步样本选择技术的情况下，一个相关的选择规则在两个不同的时间段产生的样本。允许使用一些非参数组件。通过Monte Carlo模拟实验研究了估计量的有限样本性质。
In this paper we are concerned with the estimation of a panel data sample selection model where both the selection and the regression equation contain individual effects allowed to be correlated with the observable variables. In this direction, some estimation techniques have been recently developed. We propose a new method for correcting for sample selection bias. Our estimation procedure is an extension of the familiar two-step sample selection technique to the case where one correlated selection rule in two different time periods generates the sample. Some non-parametric components are allowed. The finite sample properties of the estimator are investigated by Monte Carlo simulation experiments.