Re: st: An econometric question

["Roy,Suryadipta" <suryadipta.roy@lawrence.edu>]

Hi everyone,

Thank you so much for your comments- I am really learning 
a lot out of this. Regarding Austin's suggestion of using 
the cluster(id) option, its true that it makes the reults 
look similar to the collapse version in terms of 
significance. While I really want to take heart from 
Maarten's suggestion of not worrying about the 
significance (my signs are coming out great and exactly as 
predicted by the theoretical model!), I am worried as to 
how the referee's would take to it. Actually the 
explanatory variables are more like institutional measures 
which take a long time to change, but they do differ 
across countries a lot.

In this regard, I was wondering if a cluster(region)- 
option instead of the cluster(country)- option would be 
appropriate. Any suggestion would be highly appreciated.

Thanks!
Suryadipta.



On Mon, 9 Apr 2007 12:46:00 -0400
 "Austin Nichols" <austinnichols@gmail.com> wrote:

> Suryadipta Roy--
> If you use the 1500 observations, or 15 years of data on 
> 100
> countries, and you use the option cluster(country) on 
> your regression
> command, then you take account of dependence of the 
> errors within
> country over time, which allows the "effective sample 
> size" to be some
> number between 100 and 1500.  In the case where there is 
> really no new
> information across years, the cluster() option should 
> make the results
> look more like the -collapse-d version in terms of 
> statistical
> significance of coefficients.  The cluster() option is 
> advisable for
> the 1500 obs case even if you have a lot of 
> within-country variation
> because it is likely you have some kind of serial 
> correlation.
> Example:
> webuse grunfeld, clear
> egen mean_inv=mean(inv), by(comp)
> egen mean_k=mean(k), by(comp)
> reg mean_k mean_inv, nohe
> reg mean_k mean_inv, nohe cluster(comp)
> collapse k inv, by(comp)
> reg kstock inv, nohe
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