离散面板数据的中位回归

IF 17.7 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2024-05-15 DOI:10.1080/00949655.2024.2352527

Alfonso Russo, Alessio Farcomeni, Marco Geraci

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引用次数: 0

摘要

摘要：我们为离散纵向数据的量值回归提出了一种新方法。该方法基于条件中位数的概念，即使在存在联系的情况下也具有良好的理论特性，同时基于一个 Ridge 类型的均衡框架，以适应依赖性数据。我们通过模拟研究和对一百多个国家十五年来宏观审慎政策使用情况的原创应用来说明这些方法。

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Mid-quantile regression for discrete panel data

A BSTRACT : We propose a novel method for quantile regression for discrete longitudinal data. The approach is based on the notion of conditional mid-quantiles, which have good theoretical properties even in the presence of ties, and a Ridge-type pe-nalised framework to accommodate dependent data. We illustrate the methods with a simulation study and an original application to the use of macroprudential policies in more than one hundred countries over a period of fifteen years.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.