Testing for Granger causality in panel data
Abstract. 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.
View all articles by these authors:
Luciano Lopez, Sylvain Weber
View all articles with these keywords:
xtgcause, Granger causality, panel datasets, bootstrap
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