Unifying Estimation and Inference for Linear Regression with Stationary and Integrated or Near-Integrated Variables

Shaoxin Hong, Daniel Henderson (), Jiancheng Jiang and XQingshan Ni

Journal of Financial Econometrics, 2024, vol. 22, issue 5, 1397-1420

Abstract: There is a discrepancy in the limiting distributions of least-squares estimators for stationary and integrated variables. For statistical inference, it must be decided which distribution should be used in advance. This motivates us to develop a unifying inference procedure based on weighted estimation. The asymptotic distributions of the proposed estimators are developed and a random weighting bootstrap method is proposed for constructing confidence regions. The proposed method outperforms existing methods (with time constant or time-varying error variance) in simulations. We further study the predictability of asset returns in a setting where some of our state variables are endogenous.

Keywords: integrated; nearly integrated; random weighting; unit roots; weighted estimation equation (search for similar items in EconPapers)
JEL-codes: C12 C58 G12 (search for similar items in EconPapers)
Date: 2024
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