In the field of regional science, several empirical conclusions rely on significance tests. The statistical significance of parameter estimates in regression models is particularly important for researchers. However, the calculation of classical significance tests (t-test of F-test) relies on assumptions that, if not respected, may lead to bias in the tests themselves. The purpose of this technical note is to present an alternative approach, a non-parametric test, that allows us to test for significance using a randomization test. Such an approach is more flexible than conventional parametric tests and its application is relatively simple. To show the relevance of this alternative approach, we present a detailed application in Stata using synthetic data.