Serial-dependence and persistence robust inference in predictive regressions
Serial-dependence and persistence robust inference in predictive regressions
This paper introduces a new method for testing the statistical significance of estimated parameters in predictive regressions. The approach features a new family of test statistics that are robust to the degree of persistence of the predictors. Importantly, the method accounts for serial correlation and conditional heteroskedasticity without requiring any corrections or adjustments. This is achieved through a mechanism embedded within the test statistics that effectively decouples serial dependence present in the data. The limiting null distributions of these test statistics are shown to follow a chi-square distribution, and their asymptotic power under local alternatives is derived. A comprehensive set of simulation experiments illustrates their finite sample size and power properties.
econ.EM, stat.ME
Pitarakis, Jean-Yves
ee5519ae-9c0f-4d79-8a3a-c25db105bd51
1 February 2025
Pitarakis, Jean-Yves
ee5519ae-9c0f-4d79-8a3a-c25db105bd51
[Unknown type: UNSPECIFIED]
Abstract
This paper introduces a new method for testing the statistical significance of estimated parameters in predictive regressions. The approach features a new family of test statistics that are robust to the degree of persistence of the predictors. Importantly, the method accounts for serial correlation and conditional heteroskedasticity without requiring any corrections or adjustments. This is achieved through a mechanism embedded within the test statistics that effectively decouples serial dependence present in the data. The limiting null distributions of these test statistics are shown to follow a chi-square distribution, and their asymptotic power under local alternatives is derived. A comprehensive set of simulation experiments illustrates their finite sample size and power properties.
Text
2502.00475v1
- Author's Original
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Published date: 1 February 2025
Keywords:
econ.EM, stat.ME
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Local EPrints ID: 510540
URI: http://eprints.soton.ac.uk/id/eprint/510540
PURE UUID: b4a70f39-a5e6-46a4-83cf-d0da92fc033a
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Date deposited: 13 Apr 2026 16:41
Last modified: 14 Apr 2026 01:39
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