On the Performance of Some Robust Instrumental Variables Estimators

Bo E. Honoré; Luojia Hu

doi:10.1198/073500103288619368

On the Performance of Some Robust Instrumental Variables Estimators

Bo E. Honoré
, Luojia Hu

Research output: Contribution to journal › Article › peer-review

28 Scopus citations

Abstract

This article considers instrumental variables versions of the quantile and rank regression estimators. The asymptotic properties of the estimators are discussed, and a small-scale Monte Carlo study is used to illustrate the potential advantages of the approach. Finally, the proposed methods are implemented for two empirical examples.

Original language	English (US)
Pages (from-to)	30-39
Number of pages	10
Journal	Journal of Business and Economic Statistics
Volume	22
Issue number	1
DOIs	https://doi.org/10.1198/073500103288619368
State	Published - Jan 2004

All Science Journal Classification (ASJC) codes

Statistics and Probability
Social Sciences (miscellaneous)
Economics and Econometrics
Statistics, Probability and Uncertainty

Keywords

Endogeneity
Quantile regression
Rank regression

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10.1198/073500103288619368

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title = "On the Performance of Some Robust Instrumental Variables Estimators",

abstract = "This article considers instrumental variables versions of the quantile and rank regression estimators. The asymptotic properties of the estimators are discussed, and a small-scale Monte Carlo study is used to illustrate the potential advantages of the approach. Finally, the proposed methods are implemented for two empirical examples.",

keywords = "Endogeneity, Quantile regression, Rank regression",

author = "Honor{\'e}, \{Bo E.\} and Luojia Hu",

note = "Funding Information: The authors thank Anne Case and Dvid Jaaer foer heglp-ing obtain the data used in this article and to Alan Kruger, the referees, and the editors for valuable comments. The authors gratefully acknowledge {\v Z} nancial support from the National Science Foundation (SES-0111342, SBR-9709598, and SES-0111799), the Wisoln Scieto, ythe Danish National Research Foundation, and the Econometric Research Program at Princeton University. Part of this research was conducted when Bo Honor{\'e} visited the University of Copenhagen in the Fall of 1997. Their hospitality is also gratefully acknowledged.",

year = "2004",

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doi = "10.1198/073500103288619368",

language = "English (US)",

volume = "22",

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AU - Honoré, Bo E.

AU - Hu, Luojia

N1 - Funding Information: The authors thank Anne Case and Dvid Jaaer foer heglp-ing obtain the data used in this article and to Alan Kruger, the referees, and the editors for valuable comments. The authors gratefully acknowledge Ž nancial support from the National Science Foundation (SES-0111342, SBR-9709598, and SES-0111799), the Wisoln Scieto, ythe Danish National Research Foundation, and the Econometric Research Program at Princeton University. Part of this research was conducted when Bo Honoré visited the University of Copenhagen in the Fall of 1997. Their hospitality is also gratefully acknowledged.

PY - 2004/1

Y1 - 2004/1

N2 - This article considers instrumental variables versions of the quantile and rank regression estimators. The asymptotic properties of the estimators are discussed, and a small-scale Monte Carlo study is used to illustrate the potential advantages of the approach. Finally, the proposed methods are implemented for two empirical examples.

AB - This article considers instrumental variables versions of the quantile and rank regression estimators. The asymptotic properties of the estimators are discussed, and a small-scale Monte Carlo study is used to illustrate the potential advantages of the approach. Finally, the proposed methods are implemented for two empirical examples.

KW - Endogeneity

KW - Quantile regression

KW - Rank regression

UR - https://www.scopus.com/pages/publications/0742306365

UR - https://www.scopus.com/pages/publications/0742306365#tab=citedBy

U2 - 10.1198/073500103288619368

DO - 10.1198/073500103288619368

M3 - Article

AN - SCOPUS:0742306365

SN - 0735-0015

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SP - 30

EP - 39

JO - Journal of Business and Economic Statistics

JF - Journal of Business and Economic Statistics

IS - 1

ER -

On the Performance of Some Robust Instrumental Variables Estimators

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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