Résultat de la recherche
Do cross-border workers cause unemployment in the host country? The case of Switzerland
Switzerland’s labour market traditionally accommodates many cross-border workers: their number is currently above 300,000, corresponding to almost 7% of the workforce. Social acceptance of such workers has however deteriorated over the last years, and questions arise over their potential adverse impacts on the local labour market. Using quarterly data over 1996-2017, we investigate the claim that border workers create unemployment among the local labour force, conducting both time-series analyses at the country-level and longitudinal analyses at the canton-level. Our findings indicate that causality runs mainly from unemployment to border workers, the latter being repelled when unemployment increases. The opposite effect, from border workers to unemployment appears to be weaker or even non-existent.
Testing for Granger causality in panel data
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.