From: Achim Zeileis <Achim.Zeileis_at_wu-wien.ac.at>

Date: Wed 20 Apr 2005 - 22:31:44 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Wed Apr 20 22:38:18 2005

Date: Wed 20 Apr 2005 - 22:31:44 EST

Arne:

> we (Ott Toomet and I) would like to add functions for maximum

*> likelihood (ML) estimations of generalized tobit models of type 2 and
**> type 5 (*see below) in my R package for microeconomic analysis
**> "micEcon". So far we have called these functions "tobit2( )" and
**> "tobit5( )". Are these classifications well known?
*

I don't know them, but I'm certainly not an expert in tobit
estimation...

Generally, I prefer functions that have a name like tobit() and where
the rest can be specified by parameters, that can be more easily
understood than abstract categorizations like "type 2" and "type 5".

> How are these

*> functions called in other software packages? Should we keep these
**> names or does anybody have better suggestions?
**>
**> (* T. Amemiya (1984): Tobit models: a survey, Journal of Econometrics,
**> and T. Amemiya (1985): Advanced Econometrics)
*

OK, I haven't checked those now, but I guess that it should be possible to figure out first what the common *conceptual* properties of the different models are and then turn them into *computational* tools. My guess would be that type 2 and type 5 are not the best conceivable abstractions of the underlying conceptual properties...

> Furthermore, the generalized tobit model of type 2 is identical to the

*> Heckman model. Until now the package "micEcon" contains a function
**> "heckit( )" that performs a two-step estimation of the Heckman / Tobit
**> type 2 model. The difference between "heckit( )" and "tobit2( )" is
**> that "heckit( )" performs a two-step estimation, while "tobit2( )"
**> performs a maximum likelihood estimation. At the moment we are
**> debating how to construct the user interface. These are our
**> suggestions:
**>
**> 1) Keep it as it is:
**> heckit( ) does a two-step estimation and
**> tobit2( ) does a ML estimation
**>
**> 2) Having just one function:
**> tobit2( ..., method = "2step" ) does a two-step estimation
**> tobit2( ..., method = "ML" ) does a ML estimation
**> This has the advantage that other methods like a weighted two-step
**> least squares can be added easily.
**>
**> 3) As suggestion 2). Argument "method" has the default "ML" and an
**> additional a wrapper function is added:
**> heckit <- function( ... ) {
**> return( tobit2( ..., method = "2step" ) )
**> }
*

Probably, I would allow both, I guess. Thus go for something like 3).

> Does anybody have a better suggestion?

*> How is this implemented in other software packages?
**> What do you think is the best option?
*

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Wed Apr 20 22:38:18 2005

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