摘要翻译：
跟随经验福利最大化文献的脚步，本文希望通过一个最优政策分配问题的实际说明来强调政策制定者的观点。更具体地说，通过聚焦于基于阈值的政策类别，我们首先建立了政策制定者选择问题的理论基础，然后通过使用流行的LaLonde(1986)培训计划数据集的实证说明为该问题提供了一个实用的解决方案。本文提出了一种简单实用、易于用标准统计软件编程的最优解实现协议。
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英文标题：
《Optimal Policy Learning: From Theory to Practice》
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作者：
Giovanni Cerulli
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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：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
Following in the footsteps of the literature on empirical welfare maximization, this paper wants to contribute by stressing the policymaker perspective via a practical illustration of an optimal policy assignment problem. More specifically, by focusing on the class of threshold-based policies, we first set up the theoretical underpinnings of the policymaker selection problem, to then offer a practical solution to this problem via an empirical illustration using the popular LaLonde (1986) training program dataset. The paper proposes an implementation protocol for the optimal solution that is straightforward to apply and easy to program with standard statistical software.
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