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re: st: RE: Number of observations with ARMA models


From   Christopher Baum <kit.baum@bc.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   re: st: RE: Number of observations with ARMA models
Date   Tue, 17 Jan 2012 09:04:41 -0500

<>
Nick wrote

> Your second question has no easy answer that I can see, because of the two different perspectives on the first. If this were my problem, I would fit each model to the largest amount of data possible. 
> 
> Nick 
> n.j.cox@durham.ac.uk 
> 
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Steven Trypsteen
> 
> ...

> I would like to understand this because I would like to use the Log likelihood test (command: lrtest) to determine if two models are equivalent. For example I would like to check if AR(8) is equivalent to AR(2). How should I restrict my sample then to make sure the estimation procedure uses the same number of observations?


I beg to differ. If you are using a test to determine optimal lag length, it is imperative that all models be fit over the same observations. (Think about R^2: the total sum of squares will be changing otherwise). The easiest way to implement this is to do something like

reg y L(1/8).y
g byte es = e(sample)
reg y L(1/4).y is es
reg y L(1/2).y if es

etc. Then all regressions will be run over the common (shortest) sample. 

Such logic is implemented in many time-series routines in Stata (e.g., unit root tests).

Kit

Kit Baum   |   Boston College Economics & DIW Berlin   |   http://ideas.repec.org/e/pba1.html
                             An Introduction to Stata Programming  |   http://www.stata-press.com/books/isp.html
  An Introduction to Modern Econometrics Using Stata  |   http://www.stata-press.com/books/imeus.html


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