Published August 7, 2017
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Resolving the Errors-in-Variables Bias in Risk Premium Estimation
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.
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Additional details
- Eprint ID
- 79417
- Resolver ID
- CaltechAUTHORS:20170726-114922004
- Created
-
2017-08-07Created from EPrint's datestamp field
- Updated
-
2019-10-03Created from EPrint's last_modified field
- Caltech groups
- Social Science Working Papers
- Series Name
- Social Science Working Paper
- Series Volume or Issue Number
- 1392