[Limdep Nlogit List] Why estimates remain unaffected when using ordinary weights in rank-ordered logistic regression?

[William Greene]

Juho.  (1) ;Conditional is used for the nested logit model, but the nested
logit model
does not support ranks.  (2) when fitting a clogit model with rank data,
each observation
generates J-1 terms in the log likelihood, not one term. As such, it is not
clear how to
treat weights.  It is also unclear how much information, if any, is
provided by ranks beyond
the most preferred.  For these reasons, nlogit does not attempt to treat a
weighting variable
when ranked data are provided.
Regards
Bill Greene

On Wed, Aug 18, 2021 at 2:57 AM Valtiala Juho (Luke) <juho.valtiala at luke.fi>
wrote:

> Dear list members,
> I am using rank-ordered logit to analyse the data from a questionnaire in
> which people were asked to rank their preferences. Farmers are
> over-represented among the respondents, and I would like to give less
> weight to farmers' responses. I am using the following NLOGIT command:
>
> DISCRETECHOICE; Lhs=RANK; Choices=1,2,3,4,5; Ranks; Conditional;
> Rh2=ONE,HIGH_EDUC$
>
> My problem is that when I apply ordinary weights by adding Wts=FWEIGHT
> argument the results remain unaffected. NLOGIT executes the command
> normally and the weight variable FWEIGHT is shown in output as expected.
> So, why the weight has no effect on estimates? Is there a problem with the
> command or is the problem a theoretic one which I have not considered? The
> weighting variable has effect when I use ordinary multinomial logit with
> the preferred alternative instead of ranked alternatives.
>
> Best regards,
> Juho Valtiala
>
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-- 
William Greene
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Stern School of Business, New York University
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