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Re: st: DiD


From   inggrid <[email protected]>
To   [email protected]
Subject   Re: st: DiD
Date   Fri, 1 Apr 2011 03:09:58 +0800 (SGT)

Hi Federico,


As your expectations, I have enormous treated individuals in 2007 (since my sample size is larger in 2007 than in 2000). Then, for the sake of testing, I dropped some treated individuals in 2007. But, there were no changes. 

X1 is a standardized score (0-1).

Finally, I converted my dependent variable from real expenditure per capita to real expenditure. It worked fine when I was re-running the model.

Thanks a lot for your help!

Best regards,
Inggrid
--- On Thu, 3/31/11, [email protected] <[email protected]> wrote:

> From: [email protected] <[email protected]>
> Subject: Re: st: DiD
> To: [email protected]
> Date: Thursday, March 31, 2011, 9:32 PM
> > Hello Federico,
> 
> > You are correct, treat and treat_post05 are highly 
> > correlated.Should I drop "treat"? 
> 
> I don't think it would make sense. This variable should
> control for differences between treated and non-treated that
> are already there before the implementation of the program.
> Thus, excluding it would increase bias. 
> When you say your dataset is unbalanced, what do you mean?
> You mean (non-) treated are too many (few), or that you have
> some individuals that are observed only in 2000 (2007)?
> Because if correlation between treat and treat_post05 is
> very high, may be you have too many treated people that are
> observed only in year 2007. 
> 
> > 
> > Indeed, I also created an interaction dummy between 
> 
> > treat_post05 and a covariate (X1). Hence, the full
> model is:
> > 
> > regress  y treat post05  treat_post05
> treat_post05*X1 X2 X3 
> 
> Can you tell me what kind of variable X1 is? Is it binary?
> Are X2 and X3 highly correlated with treat_post05?
> Federico
> 
> 
> 
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