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首页> 外文期刊>Portuguese Economic Journal >Treatment effect analysis of early reemployment bonus program: panel MLE and mode-based semiparametric estimator for interval truncation
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Treatment effect analysis of early reemployment bonus program: panel MLE and mode-based semiparametric estimator for interval truncation

机译：早期再就业奖金计划的治疗效果分析：面板MLE和基于模式的半参数估计器用于区间截断

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摘要

We use Korean data to find the effects of Early Reemployment Bonus (ERB) on unemployment duration; ERB is a bonus that the eligible unemployed receive if they find a job before their unemployment insurance benefit expires. A naive approach would be comparing the ERB receiving group with the non-receiving group, but the ERB receipt is partly determined by the unemployment duration itself (thus, an endogeneity problem). Interestingly, there were many individuals who did not receive the ERB despite being fully eligible, and this is attributed to being unaware of the ERB scheme. Taking this as a ‘pseudo randomization’, we construct treatment and control groups using only the eligible. Our data set is an unbalanced panel with the response variable interval-truncated due to eligibility requirement of the ERB. We propose a panel random-effect MLE and a semiparametric ‘mode-based’ estimator for the interval-truncated response. Our empirical finding is that the effect varies much, depending on individual characteristics. As for the mean effects, whereas the MLE indicates large duration-shortening effects, the semiparametric estimator shows much weaker and mostly insignificant effects.
机译：我们使用韩国的数据来发现早期再就业奖金（ERB）对失业时间的影响；如果符合条件的失业者在失业保险金到期之前找到工作，则他们将获得ERB奖金。一个幼稚的方法是将ERB接收组与非接收组进行比较，但是ERB接收部分取决于失业时间本身（因此，是一个内生性问题）。有趣的是，尽管有充分资格，但仍有许多人没有收到ERB，这是由于没有意识到ERB计划。将其作为“伪随机化”，我们仅使用符合条件的人来构建治疗和对照组。由于ERB的资格要求，我们的数据集是一个不平衡的面板，响应变量的间隔被截断了。我们针对间隔截断的响应提出了面板随机效应MLE和半参数“基于模式”的估计器。我们的经验发现是，效果因个人特征而异。至于平均效果，而MLE表示持续时间缩短的效果较大，而半参数估计量则显示出较弱的效果，且几乎没有意义。

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