Bias From Censored Regressors

We study the bias that arises from using censored regressors in estimation of linear models. We present results on bias in ordinary least aquares (OLS) regression estimators with exogenous censoring and in instrumental variable (IV) estimators when the censored regressor is endogenous. Bound censori...

Full description

Saved in:
Bibliographic Details
Published in:Journal of business & economic statistics 2009-07, Vol.27 (3), p.340-353
Main Authors: Rigobon, Roberto, Stoker, Thomas M.
Format: Article
Language:English
Subjects:
0-1 censoring
Bias
Censored data
Censorship
Coefficients
Economic models
Estimating techniques
Estimation bias
Estimators
Expansion bias
Income estimates
Instrumental variables
Instrumental variables estimation
Linear regression
Proxy reporting
Regression analysis
Regression coefficients
Studies
Top-coding
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We study the bias that arises from using censored regressors in estimation of linear models. We present results on bias in ordinary least aquares (OLS) regression estimators with exogenous censoring and in instrumental variable (IV) estimators when the censored regressor is endogenous. Bound censoring such as top-coding results in expansion bias, or effects that are too large. Independent censoring results in bias that varies with the estimation method-attenuation bias in OLS estimators and expansion bias in IV estimators. Severe biases can result when there are several regressors and when a 0-1 variable is used in place of a continuous regressor.
ISSN:0735-0015
1537-2707
DOI:10.1198/jbes.2009.06119