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Section II presents our three-level NMNL migration model.
In this section we develop a three-level NMNL migration model with many countries of origin and many provinces of destination within countries.
However, we depart from the literature in that we introduce a function [H.sub.i] that generates the response probabilities of a three-level NMNL model.
We show in Appendix A what precise specification of [H.sub.i] implies the three-level NMNL model, and how to use the function [H.sub.i] in order to derive the following transition probabilities:
In the following we test whether these correlations reflect a causal relationship running from migrant networks to the scale and skill composition of migration, and we provide a structural interpretation of our estimation results in terms of our NMNL migration model.
(16) These include, first, the inclusive value [[PHI].sub.ir], so that this estimation is fully compatible with our three-level NMNL model; and second, they include the cost term cir representing the geographical and cultural distance between country i and region j.
The NMNL constant terms were calibrated to match the sales shares for vehicle configurations in 2010.
As discussed in the section on Consumer Demand, assumptions about price elasticities are used to compute price slopes for the NMNL model.
Note, however, that the coefficients estimated to test for similarity across alternatives in the NMNL models and used to test the NMNL model against the MNL are estimated very imprecisely.
Because the MNL cannot be rejected in favor of the NMNL, the nested logit results are not reported.
The hypothesis that the NMNL model may be simplified to the multinomial logit model is rejected.
As was the case for white collar workers, the hypothesis that the nested decision structure implied by the NMNL can be simplified to a multinomial logit structure is rejected.
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