[R] Question regarding panel data diagnostic

[Setlhare Lekgatlhamang]

Oops, I misread your email in respect of the number of years you have
for your data. Anyways, my comments still hold.

Lexi

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Setlhare Lekgatlhamang
Sent: Monday, July 26, 2010 8:59 AM
To: amatoallah ouchen; r-help at r-project.org
Subject: Re: [R] Question regarding panel data diagnostic

Dear Lexi,
Thanks a lot for your prompt answers,
The issue i'm confronted to is the following: i have a panel data N=17
T=5  (annual observations) and wanted to check for stationarity  to
avoid a spurious regression, but the question is do i' have the right
do do so??? it's statistically correct? if no is there any alternative
method to verify if our regression is correct?

Thanks again

Ama
==
Dear Ama,
I copy my reply to the list, in case someone needs it.

Spurious regression occurs when correlation between time series
variables results from their common trends - the variables tend to move
together over some cycle. However, it may difficult to decipher whether
or not the variables in your model have significant trends; also trends
differ (see Enders 1995 Time Series Econometrics). So to deal with this,
you must perform formal integration tests.

If the variables have unit root (ie, non-stationary) then you cannot
model the variables in their levels. You must transform them by
appropriate differencing. Then you can model using a dynamic model or
error-correction model (ecm) (if the variables are cointegrated). Use of
ecm makes sense only if the time span of your data is "long enough" - it
is a long run concept.
Long enough depends on the phenomenon under study. If theory suggests
that equilibrium could occur within the time span of your data (17 years
in your case - this is long enough in most cases), then concepts of
cointegration and ecm are relevant.

Hope this helps.
Lexi

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Setlhare Lekgatlhamang
Sent: Saturday, July 24, 2010 1:01 PM
To: amatoallah ouchen; r-help at r-project.org
Subject: Re: [R] Question regarding panel data diagnostic


Let me correct an omission in my response below. The last sentence
should read "But if the data are 10 quarterly or monthly values, these
techniques are not relevant".

Cheers
Lexi

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Setlhare Lekgatlhamang
Sent: Saturday, July 24, 2010 12:54 PM
To: amatoallah ouchen; r-help at r-project.org
Subject: Re: [R] Question regarding panel data diagnostic

My thought is this:
It depends on what you have in the panel. Are your data cross-section
data observed over ten years for, say, 3 countries (or regions within
the same country)? If so, yes you can perform integration properties
(what people usually call unit root test) and then test for
cointegration. But if the data are quarterly or monthly, these
techniques are not relevant.

Hope this helps.
Lexi

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of amatoallah ouchen
Sent: Friday, July 23, 2010 12:18 AM
To: r-help at r-project.org
Subject: [R] Question regarding panel data diagnostic

Good day R-listers,
I'm currently working on a panel data analysis (N=17, T=5), in order
to check for the spurious regression problem, i have to  test for
stationarity but i've read somewhere  that i needn't to test for it as
 my T<10 , what do you think? if yes  is there any other test  i have
to  perform in such case (a kind of cointegration test for small T?)

Any hint would be highly appreciated.

Ama.
*
*   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/

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.



DISCLAIMER:\ Sample Disclaimer added in a VBScript.\\\ ....{{dropped:15}}