Hi all,

This is the first time that I encountered with choice model in my research, the data we have is discrete choice data at transaction level, further, each customer purchased multiple times, therefore, this is a customer - time panel data.

Besides, the choice structure is well nested, customer first chooses whether to use self-checkout or cashier checkout (only pay with card is available), if self-checkout is chosen, then customer needs to decide whether to pay with smartphone or card. We have no alternative specific variables, only transaction level variables.

Now we want to estimate whether the number of people around at the time of purchase impact focal customer's checkout and payment choice.

My question is, can we run nested logit with customer fixed effect? Or more generally, is there a version of panel data nested logit?

If we can not run a nested logit with customer fixed effect directly, I have two more questions:

1, is there any theoretical background that prohibits people from doing so?
2, is there any other way that we can nested logit to estimate the data we have while kind of take care of customer fixed effect?

your time and knowledge will be deeply appreciated.

JAY