Dear Statalist,
I am wondering whether there is any command or implementable procedure to estimate a model (maybe related to Multinomial Logit or Nested Logit) where I can give the decision tree of alternatives a sequential interpretation.
Basically, I have the following data:
Firm i decides in t whether to invest in a, b or c.
Dependent on this choice it decides in t+1 again between a, b, c, etc. etc.
I consider 5 periods and have a set of explaining variables for t, t+1... t+5 (but I am thinking about only using variables from t to explain subsequent sequential decision making).
I have been using Multinomial Logit (mlogit) so far, but then I have to aggregate the information somehow because I cannot consider so many choices at the same time.
Therefore, I am looking for something more flexible that is explicitly suitable for sequential choices (Nested Logit is not).
Thanks for your consideration!
I am wondering whether there is any command or implementable procedure to estimate a model (maybe related to Multinomial Logit or Nested Logit) where I can give the decision tree of alternatives a sequential interpretation.
Basically, I have the following data:
Firm i decides in t whether to invest in a, b or c.
Dependent on this choice it decides in t+1 again between a, b, c, etc. etc.
I consider 5 periods and have a set of explaining variables for t, t+1... t+5 (but I am thinking about only using variables from t to explain subsequent sequential decision making).
I have been using Multinomial Logit (mlogit) so far, but then I have to aggregate the information somehow because I cannot consider so many choices at the same time.
Therefore, I am looking for something more flexible that is explicitly suitable for sequential choices (Nested Logit is not).
Thanks for your consideration!