Jiâqi Xiao, Yiannis Karavias, Artūras Juodis, Vasilis Sarafidis, J. Ditzen
{"title":"Improved tests for Granger noncausality in panel data","authors":"Jiâqi Xiao, Yiannis Karavias, Artūras Juodis, Vasilis Sarafidis, J. Ditzen","doi":"10.1177/1536867X231162034","DOIUrl":null,"url":null,"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 N T 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.","PeriodicalId":51171,"journal":{"name":"Stata Journal","volume":"23 1","pages":"230 - 242"},"PeriodicalIF":3.2000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stata Journal","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1177/1536867X231162034","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 10
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 N T 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.
期刊介绍:
The Stata Journal is a quarterly publication containing articles about statistics, data analysis, teaching methods, and effective use of Stata''s language. The Stata Journal publishes reviewed papers together with shorter notes and comments, regular columns, book reviews, and other material of interest to researchers applying statistics in a variety of disciplines.