A revisit to bias-adjusted predictive regression

Ke-Li Xu

Journal of Empirical Finance, 2025, vol. 80, issue C

Abstract: We consider robust inference of predictive regression based on bias correction. We propose new variance estimators which can accommodate conditionally heteroskedastic and serially correlated errors, and predictors with unspecified dependence structure. We also present a previously overlooked robustness property of the existing variance estimator. Empirically we illustrate the methods with a classical application to stock return and dividend growth predictability.

Keywords: Bias correction; Conditional heteroskedasticity; Predictive regression; Robust inference (search for similar items in EconPapers)
JEL-codes: C12 C32 C58 G12 G14 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:80:y:2025:i:c:s0927539824001129

DOI: 10.1016/j.jempfin.2024.101578

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