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Fitting a fractional multinomial logit model by quasi maximum likelihood

fmlogit depvars [weight] [if] [in] [, etavar(varlist) cluster(clustervar) constraints(numlist|matname)} level(#) nolog maximize_options ]

by ... : may be used with betafit; see help by.

fweights, and pweights are allowed; see help weights.

Description

fmlogit fits by quasi maximum likelihood a fractional multinomial logit model. Each variable in depvarlist ranges between 0 and 1 and all variables in depvarlist must, for each observation, add up to 1: for example, they may be proportions. It is a multivariate generalization of the fractional logit model proposed by Papke and Wooldridge (1996).

Note that cases will be ignored if the one or more of the dependent variables has a value less zero or more than one or if the dependent variables don't add up to one.

Also note that fmlogit always implies the robust option because the model is fitted using quasi maximum likelihood.

Options

etavar() specifies the explanatory variables. (The name of this option originates from the symbol commonly used for the linear predictor, the Greek letter eta.)

cluster(clustervar) specifies that the observations are independent across groups (clusters) but not necessarily within groups. clustervar specifies to which group each observation belongs; e.g., cluster(personid) in data with repeated observations on individuals. See [U] 23.14 Obtaining robust variance estimates.

constraints(numlist|matname)} specifies linear constraint(s) that are to be applied to the model; see help constraint.

level(#) specifies the confidence level, in percent, for the confidence intervals of the coefficients; see help level.

nolog suppresses the iteration log.

maximize_options control the maximization process; see help maximize. If you are seeing many "(not concave)" messages in the log, using the difficult option may help convergence.

Example

use http://fmwww.bc.edu/repec/bocode/c/citybudget.dta, clear

fmlogit governing safety education recreation social urbanplanning, /// eta(minorityleft noleft houseval popdens)

dfmlogit, at(minorityleft 0 noleft 0 )

(click to run)

Author

Maarten L. Buis, Universitaet Tuebingen maarten.buis@uni-tuegingen.de

References

Papke, Leslie E. and Jeffrey M. Wooldridge. 1996. Econometric Methods for Fractional Response Variables with an Application to 401(k) Plan Participation Rates. Journal of Applied Econometrics 11(6):619-632.

Also see

Online: help for fmlogit postestimation,