Thank you very much, Sven. I get "Data error" when trying to run tbar =
meanc(tstats), following your instructions.
Cheers,
Bruno
-----Mensagem original-----
De: gretl-users-bounces(a)lists.wfu.edu
[mailto:gretl-users-bounces@lists.wfu.edu] Em nome de Sven Schreiber
Enviada em: sexta-feira, 8 de janeiro de 2010 21:24
Para: Gretl list
Assunto: Re: [Gretl-users] RES: Panel models tests
Well I don't have a complete solution for you, but AFAIR some of these tests
rely on average ADF test statistics. So here is an example script showing
how to calculate such averages across panel units:
open greene14_1.gdt # example of a panel dataset
# which variable?
series tested = C
lagorder = 0
scalar numofunits = max($unit)
matrix tstats = {}
loop for i=1..numofunits
smpl $unit=i --restrict
adf lagorder tested --c
matrix tstats = tstats | $test
smpl full
endloop
tbar = meanc(tstats)
print tbar
For averaging p-values instead just replace $test with $pvalue. After some
polishing (and generalization) all this stuff could be wrapped in function
packages, but currently I don't have time for that, sorry.
Anybody else?
cheers,
sven
Bruno Thiago Tomio schrieb:
Right... I'm aware of some limitations of these kind of tests.
Anyway,
tests like IPS, Maddala-Wu or Levin-Lin-Chou (2002) would be welcome.
I was hoping to find a R package for these tests, but no success. Last
but not least, thank you for answering, Sven.
Sincerely,
Bruno
-----Mensagem original-----
De: gretl-users-bounces(a)lists.wfu.edu
[mailto:gretl-users-bounces@lists.wfu.edu] Em nome de Sven Schreiber
Enviada em: quarta-feira, 6 de janeiro de 2010 13:57
Para: Gretl list
Assunto: Re: [Gretl-users] Panel models tests
Bruno Thiago Tomio schrieb:
> Hello,
>
> It's really lacking some tests when you estimate a panel model. Could
> it be added some panel unit root tests, for example, please?
>
In principle you're right, but I guess it's a barrel without bottom
(old German proverb). What test in particular would you be interested
in? BTW the earlier panel unit root tests have ridiculously strong
independence assumptions IMHO. Also this may be a good case for
contributed function packages (I'm not 100% sure if it's really that
convenient for panel data,
though.)
cheers,
sven
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