| dc.contributor.author | Xiao, Jiaqi | |
| dc.contributor.author | Karavias, Yiannis | |
| dc.contributor.author | Juodis, Artūras | |
| dc.contributor.author | Sarafidis, Vasilis | |
| dc.contributor.author | Ditzen, Jan | |
| dc.date.accessioned | 2024-05-27T13:49:13Z | |
| dc.date.available | 2024-05-27T13:49:13Z | |
| dc.date.created | 2023-06-13T17:58:42Z | |
| dc.date.issued | 2023 | |
| dc.identifier.citation | The Stata Journal. 2023, 23 (1), 230-242. | |
| dc.identifier.issn | 1536-867X | |
| dc.identifier.uri | https://hdl.handle.net/11250/3131599 | |
| dc.description.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. | |
| dc.description.abstract | Improved tests for Granger noncausality in panel data | |
| dc.language.iso | eng | |
| dc.title | Improved tests for Granger noncausality in panel data | |
| dc.title.alternative | Improved tests for Granger noncausality in panel data | |
| dc.type | Peer reviewed | |
| dc.type | Journal article | |
| dc.description.version | publishedVersion | |
| dc.source.pagenumber | 230-242 | |
| dc.source.volume | 23 | |
| dc.source.journal | The Stata Journal | |
| dc.source.issue | 1 | |
| dc.identifier.doi | 10.1177/1536867X231162034 | |
| dc.identifier.cristin | 2154257 | |
| cristin.ispublished | true | |
| cristin.fulltext | original | |
| cristin.qualitycode | 1 | |
