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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 * * 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/

**Follow-Ups**:**Re: st: RE: Number of observations with ARMA models***From:*Nick Cox <njcoxstata@gmail.com>

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