Hi Carlos - I see two likely reasons for this result.

1. When you split the sample the coefficient on trade in the late 
industrializers tells you the effect relative to zero. When you pool the 
late and early industrializers, the coefficient on the interaction tells 
you whether late industrializers are different from early industrializers. 
To test whether they are different from zero, test the sum of the two 
coefficients.

2. Perhaps the restrictions on the other variables implied by pooling are 
incorrect. If the other coefficients are not equal across the two samples, 
then splitting the data relaxes this assumption, which could affect the 
estimate for the trade variable as a consequence.

Good luck with the analysis.

On Mon, 28 Jul 2008, Carlos Rodriguez wrote:

> Date: Mon, 28 Jul 2008 15:03:40 -0700
> From: Carlos Rodriguez <[log in to unmask]>
> Reply-To: Political Methodology Society <[log in to unmask]>
> To: [log in to unmask]
> Subject: [POLMETH] interactions and analyses for subsets of the sample
> 
> Dear POLMETH list,
>
> I am working with TSCS data and would appreciate some advice on this issue.
> I have run some regressions with an interaction between trade and a
> dummy for late industrializers.  The interaction was not significant.
> However, I reran the analysis dividing my dataset into two groups:
> early industrializers and late industrialzers.  It turns out that
> trade iIS significant in the set of late industrializers.  Why would
> the interaction between trade and late industrializers in the whole
> sample fail to achieve significance whereas trade comes up as highly
> significant when the regression is run separtely on the group of
> countries that are late indutrialers?  Can the difference be put down
> to the dissimialr Ns? Moreover, which result shall I "believe"?
>
> thanks for your advice.
> Carlos Rodriguez
>
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