[Limdep Nlogit List] Question on socio-demographic characteristicsand the MNL model

[Durham, Cathy]

They are meaningful in changing the relative probability of each choice.
Specifically parameters on consumer variables measure how the utility
changes relative to the final choice in which it is not included, thus
if positive it increases the first two choices relative to your third.
You can get the marginal effects from a change in age to the probability
of the three choices by adding. 
; Effects; Age[*] $ 
You can also use different parameters for the two choices if you think
age effects the first choices differently relative to the choice of
hotline, which seems possible. Though if you do you will need to add up
the effects on the three diffent probabilities tables. Or in that case
you might want to simulate the impact controlling to make age change in
all choices simultaneously. For the latter you have to run the model
normally (baseline scenario) and then something like this-
	;Simulation;Scenario:age(store)=[=]1 /age(internet)=[=]1$
Which will give prob changes for a 1 unit change in age averaged over
all the observations.
I've recently discovered all sorts of fun stuff in the Nlogit guide.

-----Original Message-----
From: limdep-bounces at limdep.itls.usyd.edu.au
[mailto:limdep-bounces at limdep.itls.usyd.edu.au] On Behalf Of Oliver
Ehrlich
Sent: Thursday, October 01, 2009 7:29 AM
To: limdep at limdep.itls.usyd.edu.au
Subject: [Limdep Nlogit List] Question on socio-demographic
characteristicsand the MNL model

Dear all,

I have a question concerning the inclusion of socio-demographic
characteristics (SDCs) in discrete choice MNL models:

Let's say I want to model 1) the influence of perceived sales channel
quality (service quality, convenience, relative product price) as stated
by consumers and 2) the influence of SDC "age" of consumers on sales
channel choice (store, internet, hotline) with a classical MNL model.

In NLOGIT 4.0, I would use the NLOGIT command with lhs=choice;
choices=store,internet,hotline;
model:
U(store)=asc_s+par_qual*quality+par_conv*convenience+par_price*price+par
_age*age/
U(internet)=asc_i+par_qual*quality+par_conv*convenience+par_price*price+
par_age*age/
U(hotline)=par_qual*quality+par_conv*convenience+par_price*price $

The question for me now is: is there any meaningful interpretation of
the parameter "par_age" for the SDC "age"? For the channel attributes,
the interpretation is of course straightforward (e.g., positive
parameter "par_qual" = the higher service quality in a channel, the
higher its channel choice probability); but as age is by definition
invariant across the alternative channels, the interpretation of a
positive/negative parameter par_age would be "the older/younger a
consumer, the higher his overall channel choice probability" - which
doesn't make too much sense...

I have also tried alternative-specific parameters for the SDC; however,
the sign of these parameters turned out to be either always positive or
always negative across alternatives, which leads to the same meaningless
interpretation as in the generic parameter case.

Against this background, I can't currently think of a setup where a SDC
would lead to a meaningful interpretation in my model setting... Maybe
some of you have an idea how SDCs could be included in the model in a
meaningful way - or if they in general should be left out completely in
such a model setting.

Thanks in advance for your help,
regards

Oliver


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