Sentence examples for location outcome from inspiring English sources
The second approach estimates multinomial logit models of destination location outcomes and uses the estimated model to produce location outcome estimates that control for characteristic differences.
For 1981 1996 the immigrant and counterfactual distributions derived using the basic MNL specification are nearly identical, implying that differences in age, education, and marital status explain virtually none of the migrant group location outcome differences.
The apparent inability of age-education or field of study differences to explain location outcome differences suggests that it is not a combination of measured skill differences and differences in skill-bias of regional labor markets that drives the differences in migrant group locations.
The next section takes a first look at migrant location outcomes.
This gives a set of counterfactual location outcomes (one for each possible source province).
The location outcomes suggest other things are not equal and not equal in ways which produce much different location decisions.
If characteristic differences successfully explain migrant group location differences the counterfactual should be both substantially different from actual immigrant outcomes and more like interprovincial migrant location outcomes.
Multinomial logit (MNL) models of migrant destination location were estimated to provide measures of the relationship between migrant characteristics and location outcomes.
In short, differences in migrant location outcomes will reflect differences in wages, work prospects, non-economic attractiveness of regions as well as migration costs.
The differences and divergence in migrant group location outcomes examined in the paper suggests that future work examining the link between these differences and other economic outcomes may be worthwhile.
In the first, MNL models are estimated by sex for each year on the immigrant sample, and the estimates are then applied to the interprovincial migrant sample to create a counterfactual set of location outcomes.
