Jun Zhou <[email protected]>:
Your existing estimates from
areg expense year, absorb(FirmID) cluster(FirmID)
are fine for estimating a time trend. You only need two observations
per firm (to estimate a very short trend), so 5 is plenty, even with
an unbalanced panel. You can convince youself of this using
simulations, creating 2000 firms and 5 years per firm, dropping some
randomly, then generating an outcome with a known trend, and
estimating that trend. The only issue arises when the missing data is
not randomly distributed--firms that fail during your time window, or
new firms, may have very different trends from the average over firms
in existence at all time periods in the window. But this is a
question about what average trend you wish to estimate--a trend
averaged over all firms during that window, or only firms in existence
at all time periods in the window, etc.
On Fri, Feb 13, 2009 at 11:30 AM, Jun Zhou
<[email protected]> wrote:
> Hello Al,
> Thanks a lot for your reply.
> My biggest concern here is the time dimension is too short, which might affect the inference on the time trend. Can -somersd- address this issue?
> Thanks again.
> Jun
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On Behalf Of Feiveson, Alan H. (JSC-SK311)
> Sent: February 13, 2009 9:17 AM
> To: [email protected]
> Subject: st: RE: time trend in a panel with very SHORT time dimension
>
> You could try a non-parametric within-cluster comparison using -somersd- . This avoids distributional assumptions.
>
> somersd expense year,funtype(wcluster) cluster(FirmID) wstrata(FirmID)
>
>
> Al Feiveson
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On Behalf Of Jun Zhou
> Sent: Thursday, February 12, 2009 7:31 PM
> To: [email protected]
> Subject: st: time trend in a panel with very SHORT time dimension
>
> Dear all,
>
> I have an unbalanced panel dataset with 5 years observations from 2000 firms.
> I would like to test whether there is a positive time-trend in one variable (e.g. expense).
> I tried the following two ways:
> xi: areg expense year, absorb(FirmID) cluster(FirmID)
> reg expense year, cluster(FirmID) Both methods show that the slope (i.e. the coefficient of 'year') is positive and statistically significant. Can I conclude that there is a positive time trend in variable 'expense'?
>
> I understand that it is improper to try to test time trend in a time series of 5 observations, but I am not sure whether 2000 firms can allow me to test the time trend although each firms have no more than 5 observations.
>
> Thanks a lot for your help.
> Jun
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