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Re: st: RE: tobit with autocorrelated and heteroscedastic disturbances


From   marco stampini <marco_stampini@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: tobit with autocorrelated and heteroscedastic disturbances
Date   Tue, 28 Nov 2006 08:17:07 -0800 (PST)

Thank you Scott. I will try to answer myself, with what I found out, and try to stimulate more discussion.

The command intreg can be used to address heteroscedasticity. I copy the code below.

I think that the same could be exploited to address autocorrelation, but I doubt that the code below is correct. Intreg allows modelling the variance of the error term as function of some variables. Would modelling the variance as a function of the lagged dependent variable be equivalent to a Cochrane-Orcut correction of autocorrelation in OLS?

Any help/comment would be much appreciated. Thank you.
Marco Stampini


*the tobit
xi:tobit y $X, ll(0)

*some necessary variables
gen y2 = y
replace y2 = . if y<=0
gen y3 = y
replace y3 =0 if y<=0

*intreg which replicates the tobit
xi:intreg y2 y3 $X

*intreg which replicates the tobit and accounts for heteroscedasticity
xi:intreg y2 y3 $X, r

*intreg which replicates the tobit, accounts for heteroscedasticity 
*and MAYBE(??????) takes care of autocorrelation 
xi:intreg y2 y3 $X, r het(y_lag)



----- Original Message ----
From: Scott Merryman <smerryman@kc.rr.com>
To: statalist@hsphsun2.harvard.edu
Sent: Wednesday, November 22, 2006 9:00:01 PM
Subject: st: RE: tobit with autocorrelated and heteroscedastic disturbances


You might want to try -clad- which allows heteroskedastic errors.

Scott



> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
> statalist@hsphsun2.harvard.edu] On Behalf Of marco stampini
> Sent: Wednesday, November 22, 2006 8:38 AM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: tobit with autocorrelated and heteroscedastic disturbances
> 
> Hello.
> 
> I would need to estimate jointly two tobit equations, in which errors are
> both autocorrelated and heteroscedastic.
> Does anybody have any idea on how to solve at least part of the problem?
> 
> For example, how to take care of autocorrelation and heteroscedasticity in
> each of the two tobits?
> As a second step, if possible, how to estimate jointly?
> 
> Are you aware of any routine doing anything similar?
> 
> Thank you very much in advance,
> Marco Stampini
> 


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