Mike,
You could bootstrap or simulate those confidence intervals.
Cheers,
Bob
Robert A. Yaffee, Ph.D.
Research Professor
Silver School of Social Work
New York University
Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2009.pdf
CV: http://homepages.nyu.edu/~ray1/vita.pdf
----- Original Message -----
From: Michael Bechtel <[email protected]>
Date: Wednesday, July 29, 2009 8:44 am
Subject: st: Out-of sample ARMA forecast error variance for confidence bands
To: [email protected]
> Dear Statalist members
>
> is there a convenient way to obtain confidence bands for ARMA (out-of
>
> sample) forecasts in Stata? Computing this for a one-step ahead
> forecast is simple, but more steps get complicated and also strongly
>
> increase in complexity when using ARMA models with several AR and MA
>
> terms. Any suggestions are greatly appreciated!
>
> Many thanks in advance!
>
> Michael Bechtel
>
> PS: I read Robert Yaffee's reply back in 2006, but unfortunately this
>
> advice only applies to one-step ahead forecasts
> (http://www.stata.com/statalist/archive/2006-06/msg00335.html
> )
>
> --
> ETH Zürich
> Dr. Michael M. Bechtel
> Swiss Federal Institute of Technology Zurich
> Center for Comparative and International Studies
> WEC C 25
> Weinbergstrasse 11
> 8092 Zürich
>
> [email protected]
> http://www.ib.ethz.ch/people/mbechtel
>
> +41 44 632 62 68 Phone
> +41 44 632 12 89 Fax
> --------------------------------------------------------------
>
> Am 29.07.2009 um 14:14 schrieb Giorgia Maffini:
>
> > Dear Statalist Members,
> >
> > I wonder if anybody could kindly help me out with the following
> > problem.
> >
> > I am using a difference-GMM estimator (Arellano and Bond (1991),
> > Review of
> > Economic Studies - AB) employing -xtabond2-. Instead of first-
> > differencing, I
> > would like to second-difference the equation and instrument some of
>
> > its
> > endogenous covariates with suitable lags of their own levels.
> >
> > In other words, the dependent variable in the newly differenced
> > equation would
> > need to be D2.y = y_(it)-y_(it-2) [instead of D.y = y_(it)-y_(it-1),
>
> > as in the
> > standard AB framework]. The endogenous covariate would be D2.x =
> > x_(it)-x_(it-2)
> > [instead of D.x = x_(it)-x_(it-1), as in the standard AB framework].
>
> > I would
> > instrument D2.x with the levels x_(it-3), x_(it-4), etc. and other
>
> > suitable
> > instruments (e.g. z_it).
> >
> > The following command does NOT seem to produce the requested
> > procedure:
> >
> > xi: xtabond2 D2.y L.D2.y D2.x , /*
> > */ gmm( y x , lag(3 4) collapse ) iv( z , passthru ) /*
> > noleveleq two robust
> >
> > Does anybody know how to implement the aforementioned estimation
> > using -xtabond2- ?
> >
> > The version of Stata that I am using is the following:
> >
> > Stata/MP 10.1 for Windows 64-bit x86-64
> > Born 02 Feb 2009
> >
> > Thank you for your consideration.
> >
> > Regards,
> >
> > Giorgia
> >
> > -
> > Giorgia Maffini - Research Fellow
> > Oxford University Centre for Business Taxation - Said Business School
> > Park End Street, Oxford OX1 1HP
> > Tel: 01865 614847
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/help.cgi?search
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
>
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
