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Nested logit and GEV models Example: Demand for Pharmaceuticals, anti- inflammatory drugs.

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Presentation on theme: "Nested logit and GEV models Example: Demand for Pharmaceuticals, anti- inflammatory drugs."— Presentation transcript:

1 Nested logit and GEV models Example: Demand for Pharmaceuticals, anti- inflammatory drugs

2 Drug 11 Drug 12 Drug 13 Drug21 Drug22 Group 1 Group 2

3 Anti-inflammatory drugs Level1A:Eddiksyrederivater: Level Ak:Confortid, Indocid,,,,, Level 1B: Oksikamer Level Bk:Brexidol,,,, Level 1C: Propionsyrederivater Level Ck: Iboprofen,Naproxen,,, Level 1D:Koksiber Level Dk: Celebra,,,

4 Other examples To evade taxes or not Given evasion, how many hours of work in regular and irregular jobs Given no tax evasion, how many hours of work in regular jobs

5 Other examples Travels; public or private Given public; train, bus or airplane Given private; own car or rental car

6 Other examples Wine; from Spain or Italy Given Spain; what brand Given Italy; what brand

7 Why nested logit A natural tree decision structure Within one branch, correlation across alternatives (with drugs, sideffect may be correlated) No correlation across branches

8 Software programs Stata, not so good, SAS seems ok Gauss, of course TSP also good LIMDEP, perhaps

9 The generalized extreme value model: GEV G is homogenous of degree 1 The kth partial derivative of the G- function exist, is continuous, non- negative if k is odd, and non-positive if k is even, and

10 Then if

11 is a multivariate distribution function, the choice probabilities that result from the maximization of the random utilities for which the multivariate distribution function is given by F(.) are equal to

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13 Example 1 Multinomial Logit

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18 Example 2 A nested structure Two branches, In branch 1, one alternative In branch 2, two alternatives, with correlations in the tasteshifters

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21 Choice probailities The GEV model

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23 Derivaties and elasticities The nested- or rather the corrlation structure- has a strong impact on the price elasticities

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26 Nested logit. Ujk=vjk+  jk j: indicates upper level (Level 1: Groups of pharmaceutical, Lj) k: indicates drugs at lower level k  Lj We will use the GEV structure:

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29 Two stage version of nested logit

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32 The Likelihood

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