摘要翻译：
本文利用C-Lasso（一种最近发展起来的纯数据驱动的分类方法）来识别母性对就业影响中潜在的群体结构。此外，我利用一种识别策略，结合了急剧回归间断设计和预测就业概率的假设检验，评估了2007年德国慷慨的父母福利改革的引入对不同集群群体的影响。C-Lasso方法使母亲之间的就业效应具有异质性，这些就业效应被归类为先验未知数量的集群组，每个集群组都有其特定的群体效应。使用新的德国行政数据，C-Lasso确定了改革前后三个不同的集群组。我的研究结果揭示了母亲就业中显著的未观察到的异质性，改革对所识别的集群群体的就业模式产生了不同的影响。
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英文标题：
《Identifying Latent Structures in Maternal Employment: Evidence on the
  German Parental Benefit Reform》
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作者：
Sophie-Charlotte Klose
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最新提交年份：
2020
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分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
  This paper identifies latent group structures in the effect of motherhood on employment by employing the C-Lasso, a recently developed, purely data-driven classification method. Moreover, I assess how the introduction of the generous German parental benefit reform in 2007 affects the different cluster groups by taking advantage of an identification strategy that combines the sharp regression discontinuity design and hypothesis testing of predicted employment probabilities. The C-Lasso approach enables heterogeneous employment effects across mothers, which are classified into an a priori unknown number of cluster groups, each with its own group-specific effect. Using novel German administrative data, the C-Lasso identifies three different cluster groups pre- and post-reform. My findings reveal marked unobserved heterogeneity in maternal employment and that the reform affects the identified cluster groups\' employment patterns differently.
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