Example: air traffic controller
Search results with tag "Nested logit"
Lecture 5 Multiple Choice Models Part I –MNL, Nested Logit
bauer.uh.edu•The interpretation of parameters is based on partial effects: –Derivative (marginal effect) –Elasticity (proportional changes) Note: The elasticity is the same for all choices “j.”A change in the cost of air travel has the same effect on all other forms of travel. (This result is called independecnefrom irrelevant alternatives (IIA ...
Nested Logit - Box
psfaculty.ucdavis.eduNested Logit I The “inclusive value” parameter, τ, is the weight accorded each of the branches. I Under CL (or MNL), we assume this weight is fixed at 1. I Estimation is done via full information maximum likelihood: logL = XN i log Pr j|i ×Pr i. I Model has many parameters. I It requires a lot of work to interpret. I My job to show you how ... I Stata is actually quite good w/this model.