Optimal Cross-Sectional Regression

Zhipeng Liao (), Yan Liu () and Zhenzhen Xie ()
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Zhipeng Liao: University of California Los Angeles, Los Angeles, California 90095
Yan Liu: Tsinghua University, Haidian, Beijing 10084, China
Zhenzhen Xie: Tsinghua University, Haidian, Beijing 10084, China

Management Science, 2024, vol. 70, issue 11, 7911-7942

Abstract: Errors-in-variables (EIV) biases plague asset pricing tests. We offer a new perspective on addressing the EIV issue: instead of viewing EIV biases as estimation errors that potentially contaminate next stage risk premium estimates, we consider them to be return innovations that follow a particular correlation structure. We factor this structure into our test design, yielding a new regression model that generates the most accurate risk premium estimates. We demonstrate the theoretical appeal as well as the empirical relevance of our new estimator.

Keywords: beta uncertainty; efficient estimation; errors in variables; factor models; Fama–MacBeth; GMM; idiosyncratic risk; systematic risk; two-pass regression (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:70:y:2024:i:11:p:7911-7942

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