Improved tests for Granger noncausality in panel data

Jiaqi Xiao; Yiannis Karavias; Arturas Juodis; Vasilis Sarafidis; Jan Ditzen

doi:10.1177/1536867X231162034

Improved tests for Granger noncausality in panel data

Jiaqi Xiao, Yiannis Karavias, Arturas Juodis, Vasilis Sarafidis, Jan Ditzen

Economics

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Abstract

In this article, we introduce the xtgrangert command, which implements the panel Granger noncausality testing approach developed by Juodis, Karavias, and Sarafidis (2021, Empirical Economics 60: 93–112). This test offers superior size and power performance to existing tests, which stem from the use of a pooled estimator that has a faster √NT convergence rate. The test has several other useful properties: it can be used in multivariate systems; it has power against both homogeneous and heterogeneous alternatives; and it allows for cross-section dependence and cross-section heteroskedasticity.

Original language	English
Pages (from-to)	230-242
Number of pages	13
Journal	Stata Journal
Volume	23
Issue number	1
DOIs	https://doi.org/10.1177/1536867X231162034
Publication status	Published - 5 Apr 2023

Keywords

st0706
xtgrangert
xtgrangert postestimation
panel data
Granger causality
Nickell bias
heterogeneous panels
half-panel jackknife
cross-section dependence

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1177/1536867X231162034Licence: Creative Commons: Attribution (CC BY)

XiaoJ2023ImprovedFinal published version, 358 KBLicence: Creative Commons: Attribution (CC BY)

Cite this

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AU - Ditzen, Jan

PY - 2023/4/5

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KW - Granger causality

KW - Nickell bias

KW - heterogeneous panels

KW - half-panel jackknife

KW - cross-section dependence

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Improved tests for Granger noncausality in panel data

Abstract

Keywords

UN SDGs

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