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OLIVE: A SIMPLE METHOD FOR ESTIMATING BETAS WHEN FACTORS ARE MEASURED WITH ERROR
Author(s) -
Meng J. Ginger,
Hu Gang,
Bai Jushan
Publication year - 2011
Publication title -
journal of financial research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.319
H-Index - 49
eISSN - 1475-6803
pISSN - 0270-2592
DOI - 10.1111/j.1475-6803.2010.01284.x
Subject(s) - instrumental variable , estimator , econometrics , ordinary least squares , statistics , mathematics , sign (mathematics) , simple (philosophy) , value (mathematics) , variable (mathematics) , economics , mathematical analysis , philosophy , epistemology
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, whereas the performance of conventional instrumental variable methods becomes poor or even infeasible. In an empirical application, OLIVE beta estimates improve R 2 significantly. More important, 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.