Re: st: when your sample is the entire population

[Daniel Wilde <dgw24@bath.ac.uk>]

Hi,

I can't answer this. But I would like to make an additional point. Surely 
this has always been commonplace in macro-data. When you do a cross-country 
regression of economic growth and investment for example, you have nearly 
every country, but all the papers I've seen still report the standard 
statistics (p-values etc) Why is this? Are they inferring that we have 
sampled all existing countries from a population of all the countries that 
could have potentially existed? I'm not sure I'm that I'm convinced by such 
logic.

Thanks

Daniel

--On 18 January 2008 09:59 -0800 Lloyd Dumont <lloyddumont@yahoo.com> wrote:


> Hello, everyone.  I am facing a statistical
> "challenge" that must be commonplace as microdata
> becomes more and more accessible.  I have been
> estimating  models using xtreg, as I have people
> coming and going monthly over about a two year period.
>  Some estimates significant, others not.
>
> But, if the people in the "sample" are the entire
> population that I am inferring to, conventional
> measures of significance seem inapprpriate.  But, I
> have never read any social science that presents
> regression estimates, and then says something along
> the lines of, "These are what they are.  Significance
> doesn't apply here."
>
> So...
> -Am I roughly correct?
> -Is there some other measure of "certainty" that might
> be informative in these situations?
> -Is there a name for this type of "sample" or
> estimation issue?  Googling it has been a real
> challenge, though there must be lots of
> writing/commenting on this matter.
>
> Thanks for your thoughts.  Lloyd Dumont
>
>
>
>
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