That's just the problem, neither the time dummies nor the time variable (indicating
2004, 2005 etc..) are significant..
Date: Thu, 29 Jan 2009 17:54:27 +0100> From: svetosch(a)gmx.net>
To: gretl-users(a)lists.wfu.edu> Subject: Re: [Gretl-users] help> > Am 29.01.2009
17:32, Dennis van Amelsfort schrieb:> > > > I hope someone can help me..>
> > > When I run a fixed and random effects model for my data, I obtain very>
> differing results my variable of interest when using time dummies or a> >
continuous year variable.. When I use a year variable my variable of> > interest
(AS5) is only just insignificant (p=0,15) nut when I use time> > dummies it is
totally insignificant (p=0,73). The hausman test is also> > inconclusive when I use
the year variable, but points towards fixed> > effects when using time dummies.>
> Time dummies of course are more flexible than a single time trend (if> that's
what you mean by 'continuous year variable'). So provided the> time dummies
themselves are significant, you seem to be looking at an> omitted variable bias when
you don't include the dummies.> > > > > When I insert an interaction
term between AS5 and MW (another variable> > already in the model), both the
interaction term and AS5 become> > significant when using the year variable, but
only the interaction term> > becomes significant when using time dummies.> >
Same thing here, the time dummies soak up a lot of variation that> otherwise are
(probably spuriously?) attributed to other variables.> > without having looked at
your results (sorry, no time), IMHO keep the> time dummies and throw out everything
else that isn't significant.> > (that's of course a quick-and-dirty advice
over the net, you probably> should go see a local doctor -- ahem, econometrician)>
> good luck,> sven> _______________________________________________>
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