```-------------------------------------------------------------------------------
help clogithet
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Title

clogithet -- Heteroscedastic conditional logit model.

Syntax

clogithet depvar [indepvars] [if] [in] [weight] , group(varname) het(
varlist) [options]

options                     Description
-------------------------------------------------------------------------
Model
* group(varname)            matched group variable
* het(varlist)              independent variables to model the variance

SE/Robust
robust                    robust standard errors
cluster(varname)          adjust standard errors for intragroup
correlation
opg                       standard errors based on the outer product of

Reporting
lm                        report Lagrange multiplier test for
heteroscedasticity
clogit                    report (homoscedastic) conditional logit
estimates

-------------------------------------------------------------------------
* group(varname) and het(varlist) are required.
fweights, iweights, and pweights are allowed (see weight), but they are
interpreted to apply to groups as a whole, not to individual
observations.

Description

clogithet fits a heteroscedastic version of McFadden's conditional logit
model. This model is also referred to as the parametrised heteroscedastic
multinomial logit model (Hensher et al., 1999) and the heteroscedastic
logit model (DeShazo and Fermo, 2002; Hole, 2006).

Like hetprob, clogithet models the relationship between the error
variance and a list of user-specified variables. Note that in the case of
clogithet it is the scale parameter which is a function of exp(Z*gamma),
rather than the variance itself.  The scale parameter is inversely
related to the variance (see Hole, 2006, for details). The variables in Z
must be constant within groups, i.e. they must be characteristics of the
decision-maker rather than alternative attributes.

The data setup is the same as for clogit.

See logistic estimation commands for a list of related estimation
commands.

Options

+-------+
----+ Model +------------------------------------------------------------

group(varname) is required; it specifies a numeric identifier variable
for the matched groups.

het(varlist) is required; it specifies the independent variables in the
variance function.

+-----------+
----+ SE/Robust +--------------------------------------------------------

robust, cluster(varname); see estimation options.

opg; standard errors based on the outer product of gradient estimate of
the covariance matrix.

+-----------+
----+ Reporting +--------------------------------------------------------

lm; report Lagrange multiplier test for heteroscedasticity (H0: gamma
=0).

clogit; report (homoscedastic) conditional logit estimates.

+-------------+
----+ Max options +------------------------------------------------------

showstep, hessian, tolerance(#), ltolerance(#) gtolerance(#),
nrtolerance(#), from(init_specs), difficult; see maximize.  Note that
technique(bhhh) is not allowed.

Examples

. webuse travel
. gen aasc = (mode == 1)
. gen tasc = (mode == 2)
. gen basc = (mode == 3)
. clogithet choice aasc tasc basc termtime travelcost, group(id)
het(partysize)
. clogithet choice aasc tasc basc termtime travelcost, group(id)
het(partysize) robust lm

References

DeShazo, J.R., Fermo, G., 2002. Designing choice sets for stated
preference methods: the effects of complexity on choice consistency.
Journal of Environmental Economics and Management 44, 123-143.

Hensher, D., Louviere, J., Swait, J., 1999. Combining sources of
preference data.  Journal of Econometrics 89, 197-221.

Hole, A.R., 2006. Small-sample properties of tests for heteroscedasticity
in the conditional logit model. Economics Bulletin 3, 1-14. Available
at
http://economicsbulletin.vanderbilt.edu/2006/volume3/EB-06C20063A.pdf

Author

This command was written by Arne Risa Hole (a.r.hole@sheffield.ac.uk),
Department of Economics, University of Sheffield. Comments and
suggestions are welcome.

Also see

Manual:  [R] clogit

Online:  clogit
```