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Censored Regressors and Expansion Bias

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  • Rigobon, Roberto
  • Stoker, Thomas M.

Abstract

We show how using censored regressors leads to expansion bias, or estimated effects that are proportionally too large. We show the necessity of this effect in bivariate regression and illustrate the bias using results for normal regressors. We study the bias when there is a censored regressor among many regressors, and we note how censoring can work to undo errors-in-variables bias. We discuss several approaches to correcting expansion bias. We illustrate the concepts by considering how censored regressors can arise in the analysis of wealth effects on consumption, and on peer effects in productivity.

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File URL: http://hdl.handle.net/1721.1/5054
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Bibliographic Info

Paper provided by Massachusetts Institute of Technology (MIT), Sloan School of Management in its series Working papers with number 4451-03.

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Date of creation: 12 Mar 2004
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Handle: RePEc:mit:sloanp:5054

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Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), SLOAN SCHOOL OF MANAGEMENT, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA
Phone: 617-253-2659
Web page: http://mitsloan.mit.edu/
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Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), SLOAN SCHOOL OF MANAGEMENT, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA

Related research

Keywords: Censored Regressors; Expansion Bias;

References

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Cited by:
  1. Zhuo Chen & Steven Yen & David Eastwood, 2007. "Does smoking have a causal effect on weight reduction?," Journal of Family and Economic Issues, Springer, Springer, vol. 28(1), pages 49-67, March.

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