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.

Identifying outliers in multivariate data is computationally intensive. The bacon command, presented in this article, allows one to quickly identify outliers, even on large datasets of tens of thousands of observations. bacon constitutes an attractive alternative to hadimvo, the only other command available in Stata for the detection of outliers.

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.

Obtaining the routing distance between two addresses should not be a hassle with current technology. Unfortunately, this is more complicated than it first seems. Recently, several commands have been implemented for this purpose (traveltime, traveltime3, mqtime, osrmtime), but most of them became obsolete only a few months after their introduction or appear complicated to use. In this article, we introduce the community-contributed command georoute, which retrieves travel distance and travel time between two points defined either by their addresses or by their geographical coordinates. Compared with other existing commands, it is simple to use, efficient in terms of computational speed, and versatile regarding the information that can be provided as input.