A Caltech Library Service

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 (Unpublished)

[img] PDF (SSWP 1392 - Jul. 2014) - Submitted Version
See Usage Policy.


Use this Persistent URL to link to this item:


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
Series Name:Social Science Working Paper
Issue or Number:1392
Record Number:CaltechAUTHORS:20170726-114922004
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:79417
Deposited By: Hanna Storlie
Deposited On:07 Aug 2017 21:52
Last Modified:03 Oct 2019 18:19

Repository Staff Only: item control page