摘要翻译:
本文提出了一种新的删失分位数工具变量(CQIV)估计量,并描述了它的性质和计算方法。CQIV估计量结合了Powell(1986)的删失分位数回归(CQR)来处理删失问题,并结合了内生回归的控制变量方法。CQIV估计量是在不可观测项下分两个阶段得到的,这两个阶段是非加性的。第一阶段估计控制变量具有无限维参数的非加性模型,如分位数或分布回归模型。第二阶段对感兴趣的响应变量估计一个非加性删失分位数回归模型,包括估计的控制变量来处理内生性。在计算方面,我们扩展了Chernozhukov和Hong(2002)提出的CQR算法,将控制变量的估计纳入其中。给出了CQIV估计渐近正态性的一般正则性条件,以及逼近其渐近分布的重采样方法的有效性。我们对控制变量的分位数和分布回归估计的这些条件进行了验证。我们的分析包括两阶段(未删失)分位数回归,第一阶段非加性是一个重要的特例。通过Monte-Carlo数值算例和在酒精恩格尔曲线估计中的经验应用,说明了CQIV估计量的计算和适用性。
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英文标题:
《Quantile Regression with Censoring and Endogeneity》
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作者:
Victor Chernozhukov, Ivan Fernandez-Val, and Amanda Kowalski
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最新提交年份:
2014
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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
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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:
In this paper, we develop a new censored quantile instrumental variable (CQIV) estimator and describe its properties and computation. The CQIV estimator combines Powell (1986) censored quantile regression (CQR) to deal with censoring, with a control variable approach to incorporate endogenous regressors. The CQIV estimator is obtained in two stages that are non-additive in the unobservables. The first stage estimates a non-additive model with infinite dimensional parameters for the control variable, such as a quantile or distribution regression model. The second stage estimates a non-additive censored quantile regression model for the response variable of interest, including the estimated control variable to deal with endogeneity. For computation, we extend the algorithm for CQR developed by Chernozhukov and Hong (2002) to incorporate the estimation of the control variable. We give generic regularity conditions for asymptotic normality of the CQIV estimator and for the validity of resampling methods to approximate its asymptotic distribution. We verify these conditions for quantile and distribution regression estimation of the control variable. Our analysis covers two-stage (uncensored) quantile regression with non-additive first stage as an important special case. We illustrate the computation and applicability of the CQIV estimator with a Monte-Carlo numerical example and an empirical application on estimation of Engel curves for alcohol.
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PDF链接:
https://arxiv.org/pdf/1104.4580