Dear Statalist members,
in my research I try to come up with an airline market share model. This model should be implemented as multinomial logit model and as nested logit model and the results should be compared. I am using Stata 13.1 for Windows computer.
The dependent variable is market share (market_share) between 0-1. My independent variables are ticket prices one day prior (TP_day_prior) departure and two month (TP_2m) prior departure and the frequency (freq). The data is collected for every day between April-June 2015 and for three different airlines (two legacy and one low-cost carrier) that are given the numbers 1-3 in the variable airline_code.
Since my dependent variable is continuous between 0-1 I tried to use .glm for the mulitnomial logit model:
. glm market_share TP_day_prior TP_2m freq, family(binomial 1) link(logit) vce(robust)
However this does not take into account the categorical variable airline_code nor the different days that can be seen as different cases. Does someone know how to include the categorical variable and the variable case in the model? I think this is necessary because the passenger have to choose between 3 airlines with different attributes each day and the market share for each day adds up to 1.
Furthermore does someone know if Stata is able to create a nested logit model (nest 1: legacy carriers; nest 2: low-cost carrier) with this data?
I would be really grateful if someone is able to answer my question.
Kind regards and thanks for the effort,
Britta Wilken
in my research I try to come up with an airline market share model. This model should be implemented as multinomial logit model and as nested logit model and the results should be compared. I am using Stata 13.1 for Windows computer.
The dependent variable is market share (market_share) between 0-1. My independent variables are ticket prices one day prior (TP_day_prior) departure and two month (TP_2m) prior departure and the frequency (freq). The data is collected for every day between April-June 2015 and for three different airlines (two legacy and one low-cost carrier) that are given the numbers 1-3 in the variable airline_code.
Since my dependent variable is continuous between 0-1 I tried to use .glm for the mulitnomial logit model:
. glm market_share TP_day_prior TP_2m freq, family(binomial 1) link(logit) vce(robust)
However this does not take into account the categorical variable airline_code nor the different days that can be seen as different cases. Does someone know how to include the categorical variable and the variable case in the model? I think this is necessary because the passenger have to choose between 3 airlines with different attributes each day and the market share for each day adds up to 1.
Furthermore does someone know if Stata is able to create a nested logit model (nest 1: legacy carriers; nest 2: low-cost carrier) with this data?
I would be really grateful if someone is able to answer my question.
Kind regards and thanks for the effort,
Britta Wilken