Re: [R] Fwd: time series regression

From: Mark Leeds <markleeds_at_verizon.net>
Date: Thu, 20 Mar 2008 12:09:55 -0400


Your entering into a complex danger zone here because you really need to check first if all the dependent and independent variables are stationary. Otherwise, your lm results are meaningless ( you're estimation a spurious regression ). I would look at Bernhard Pfaff's yellow book or any other decent time series econometrics text ( hayashi, hamilton ) for more on this topic. It's a quite complex problem you are working on so you need to get familiar with the cointegration/unit root concepts, if you aren't already.

-----Original Message-----
From: r-help-bounces_at_r-project.org [mailto:r-help-bounces_at_r-project.org] On Behalf Of bereket weldeslassie
Sent: Thursday, March 20, 2008 11:54 AM
To: r-help_at_stat.math.ethz.ch; r-help_at_r-project.org Subject: [R] Fwd: time series regression

 Hi Everyone,
One more information to my question. I am trying to do a time series regression using the lm function. *My intention is to investigate the relationship between a dependent time series variable and several independent time series variables.* According to the durbin watson test the errors are autocorrelated. And then I tried to use the gls function to accomodate for the autocorrelated errors. My question is how do I know what ARMA process (order) to use in the gls function? Or is there any other way to do the time series regression in R? I highly appreciate your help. Thanks,
Bereket

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