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Improved tests for Granger noncausality in panel data

Author

Listed:
  • Jiaqi Xiao

    (University of Birmingham)

  • Artūras Juodis

    (University of Amsterdam)

  • Yiannis Karavias

    (University of Birmingham)

  • Vasilis Sarafidis

    (BI Norwegian Business School)

  • Jan Ditzen

    (Free University of Bozen-Bolzano)

Abstract

In this article, we introduce the xtgrangert command, which im- plements 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.

Suggested Citation

  • Jiaqi Xiao & Artūras Juodis & Yiannis Karavias & Vasilis Sarafidis & Jan Ditzen, 2023. "Improved tests for Granger noncausality in panel data," Stata Journal, StataCorp LLC, vol. 23(1), pages 230-242, March.
    • Handle: RePEc:tsj:stataj:v:23:y:2023:i:1:p:230-242
    DOI: 10.1177/1536867X231162034
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    JEL classification:

    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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