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摘要翻译：
本文介绍了面板数据分位数回归中分组潜在异质性的估计方法。我们假设被观察的个体来自一个具有有限数量类型的异质群体。该算法不假定预先已知类型数和组成员数，而是通过凸优化问题来估计类型数和组成员数。我们给出了一致估计群隶属度的条件，并证明了所得估计量的渐近正态性。仿真结果表明，当T相当大时，该方法能在有限样本中很好地工作。为了说明所提出的方法，我们使用1977-2010年美国51个州的面板数据，研究了通过携带隐藏武器权利法对暴力犯罪率的影响。
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英文标题：
《Panel Data Quantile Regression with Grouped Fixed Effects》
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作者：
Jiaying Gu and Stanislav Volgushev
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最新提交年份：
2018
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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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一级分类：Statistics 统计学
二级分类：Methodology 方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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英文摘要：
This paper introduces estimation methods for grouped latent heterogeneity in panel data quantile regression. We assume that the observed individuals come from a heterogeneous population with a finite number of types. The number of types and group membership is not assumed to be known in advance and is estimated by means of a convex optimization problem. We provide conditions under which group membership is estimated consistently and establish asymptotic normality of the resulting estimators. Simulations show that the method works well in finite samples when T is reasonably large. To illustrate the proposed methodology we study the effects of the adoption of Right-to-Carry concealed weapon laws on violent crime rates using panel data of 51 U.S. states from 1977 - 2010.
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PDF链接：
https://arxiv.org/pdf/1801.05041
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