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Resolving the Errors-in-Variables Bias in Risk Premium Estimation

Pukthuanthong, Kuntara and Roll, Richard and Wang, Junbo (2014) Resolving the Errors-in-Variables Bias in Risk Premium Estimation. Social Science Working Paper, 1392. California Institute of Technology , Pasadena, CA. (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20170726-114922004

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Abstract

The Fama-Macbeth (1973) rolling-B method is widely used for estimating risk premiums, but its inherent errors-in-variables bias remains an unresolved problem, particularly when using individual assets or macroeconomic factors. We propose a solution with a particular instrumental variable, B calculated from alternate observations. The resulting estimators are unbiased. In simulations, we compare this new approach with several existing methods. The new approach corrects the bias even when the sample period is limited. Moreover, our proposed standard errors are unbiased, and lead to correct rejection size in finite samples.


Item Type:Report or Paper (Working Paper)
Group:Social Science Working Papers
Record Number:CaltechAUTHORS:20170726-114922004
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170726-114922004
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:79417
Collection:CaltechAUTHORS
Deposited By: Hanna Storlie
Deposited On:07 Aug 2017 21:52
Last Modified:07 Aug 2017 21:52

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