摘要翻译:
极值分位数回归,即应用于条件分布尾部的分位数回归,随着越来越多的经济和金融应用,如风险价值、生产前沿、低婴儿出生体重的决定因素和拍卖模型而计算。本章概述了极值分位数回归的理论和经验的最新发展。理论上的进步依赖于对Koenker和Bassett(1978)分位数回归估计量定律的极值逼近的使用。极值律不仅在尾部提供了比高斯律更精确的近似,而且还作为利用仿真和适当的自举和二次采样变化来开发偏差校正估计器和推理方法的基础。通过两个关于条件风险价值和金融传染的实证例子说明了这些方法的适用性。
---
英文标题:
《Extremal Quantile Regression: An Overview》
---
作者:
Victor Chernozhukov, Iv\'an Fern\'andez-Val, and Tetsuya Kaji
---
最新提交年份:
2017
---
分类信息:
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
--
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。
--
---
英文摘要:
Extremal quantile regression, i.e. quantile regression applied to the tails of the conditional distribution, counts with an increasing number of economic and financial applications such as value-at-risk, production frontiers, determinants of low infant birth weights, and auction models. This chapter provides an overview of recent developments in the theory and empirics of extremal quantile regression. The advances in the theory have relied on the use of extreme value approximations to the law of the Koenker and Bassett (1978) quantile regression estimator. Extreme value laws not only have been shown to provide more accurate approximations than Gaussian laws at the tails, but also have served as the basis to develop bias corrected estimators and inference methods using simulation and suitable variations of bootstrap and subsampling. The applicability of these methods is illustrated with two empirical examples on conditional value-at-risk and financial contagion.
---
PDF链接:
https://arxiv.org/pdf/1612.06850