Testing for Granger causality in panel data
Résumé With the development of large and long panel databases, the theory surrounding panel causality evolves quickly, and empirical researchers might find it difficult to run the most recent techniques developed in the literature. In this article, we present the community-contributed command xtgcause, which implements a procedure proposed by Dumitrescu and Hurlin (2012, Economic Modelling 29: 1450–1460) for detecting Granger causality in panel datasets. Thus, it constitutes an effort to help practitioners understand and apply the test. xtgcause offers the possibility of selecting the number of lags to include in the model by minimizing the Akaike information criterion, Bayesian information criterion, or Hannan–Quinn information criterion, and it offers the possibility to implement a bootstrap procedure to compute p-values and critical values.
Mots-clés Stata, Granger causality, panel datasets, bootstrap
Citation Lopez, L., & Weber, S. (2017). Testing for Granger causality in panel data. Stata Journal, 17(4), 972-984.
Type Article de périodique (Anglais)
Date de publication 12-2017
Nom du périodique Stata Journal
Volume 17
Numéro 4
Pages 972-984
URL http://www.stata-journal.com/article.html?article=st0507