Olive: a simple method for estimating betas when factors are measured with error

Ginger Meng, Gang Hu and Jushan Bai

MPRA Paper from University Library of Munich, Germany

Abstract: We propose a simple and intuitive method for estimating betas when factors are measured with error: ordinary least squares instrumental variable estimator (OLIVE). OLIVE performs well when the number of instruments becomes large, while the performance of conventional instrumental variable methods becomes poor or even infeasible. In an empirical application, OLIVE beta estimates improve R-squared significantly. More importantly, our results help resolve two puzzling findings in the prior literature: first, the sign of average risk premium on the beta for market return changes from negative to positive; second, the estimated value of average zero-beta rate is no longer too high.

Keywords: betas; factor analysis; GMM; FIML; measurement error (search for similar items in EconPapers)
JEL-codes: C33 G10 G12 (search for similar items in EconPapers)
Date: 2007-03
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Published in The Journal of Financial Research 1.XXXIV(2011): pp. 27-60

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Related works:
Journal Article: OLIVE: A SIMPLE METHOD FOR ESTIMATING BETAS WHEN FACTORS ARE MEASURED WITH ERROR (2011)
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