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Lecture 5 Multiple Choice Models Part I –MNL, Nested Logit

RS Lecture 171 Lecture 5 Multiple Choice ModelsPart I MNL, Nested LogitDCM: Different Models Popular Models :1. Probit model 2. Binary Logit Model3. Multinomial Logit Model4. Nested Logit model5. Ordered Logit model Relevant literature:- Train (2003): Discrete Choice Methods with Simulation- Franses and Paap (2001): Quantitative Models in Market Research- Hensher, Rose and Greene (2005): Applied Choice AnalysisRS Lecture 17 Multinomial Logit (MNL) model In many of the situations, discrete responses are more complex than the binary case:- Single Choice out of more than two alternatives: Electoral choices and interest in explaining the vote for a particular party. - Multiple choices: Travel to work in rush hour, and travel to work out of rush hour, as well as the Choice of bus or car. The distinction should not be exaggerated: we could always enumerate travel-time, travel-mode Choice combinations and then treat the problem as making a single decision.

MNL Model –Application -PIM • Data –A.C.Nielsenscanner panel data –117 weeks: 65 for initialization, 52 for estimation –565 households: 300 selected randomly for estimation, remaining hh= holdout sample for validation –Data set for estimation: 30,966 shopping trips, 2,275 purchases in the category (liquid laundry detergent)

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