When people think about potential destinations for location choice, they may prefer countries along a set of shared characteristics like language, economic structure, governance, or geography. Similarities and substitution effects across these dimensions have often been neglected in migration choice models. We motivate their implementation in discrete choice models, in particular a cross-nested logit, by a case study.
The 2016 US presidential election ended with a rather surprising outcome when Donald J. Trump became the president-elect. Given Trump’s controversial rhetoric against Latin American immigrants, and in particular Mexicans, we examine to what extent Mexicans may have reevaluated their migration aspiration which primarily focuses on the US. We apply a difference-in-differences model to gauge the impact of Trump’s election on Mexican migration aspiration in the Gallup World Poll to establish the existence of substitution effects. Our results indicate that Mexicans are less likely to state a preference for the US after Trump’s inauguration, and instead aspire to move to similar countries, especially Canada. We assess that accounting for substitution across shared characteristics in binary choice models improves statistical properties and inference and enables us to forecast the immigration pressure in alternative destinations.