Many researchers have used the conditional logit model to examine migration. One common objection to this model is that it carries the independence from irrelevant alternatives (IIA) assumption, which may be too restrictive. This study compares the conditional logit with models that partially relax (nested logit) or fully relax (mixed logit) the IIA assumption. We will begin to learn whether as...

Summary This paper introduces a new data-driven methodology for estimating sparse covariance matrices of the random coefficients in logit mixture models. Researchers typically specify models under one two extreme assumptions: either an unrestricted full matrix (allowing correlations between all coefficients), or restricted diagonal no at all). Our objective is to find optimal subsets correlated...