Re: st: regress with dummys | difference in difference estimator

[Fernando Furquim <ffurquim@gmail.com>]

Hi Julian,

I don't think your interaction of the indicator variables tells you
anything that the two original variables already tell you. Beyond
that, I am not sure of the exact definitions of your model, but there
are lots of possible reasons for the low r^2. Maybe there are temporal
effects, so you need lags? Maybe you have lots of omitted variables
like profitability, industry, business cycle, total debt, etc? I don't
know much about corporate investments, but I think a review of the
relevant literature could hint at what kind of model makes conceptual
sense.

Also remember to -xtset- your panel.

Good luck!
Fernando

On Fri, Mar 28, 2014 at 11:51 AM, Julian Kochan <julian.kochan@gmx.de> wrote:
> Hi,
>
> this is an update to my previous question:
>
> i have a set of data with financial firm characteristics of about 10.000 firms for Year 2000 - Year 2012.
>
> My goal is to use a difference in difference estimator and to do a regression with the dependent variable: corporate_investments and independent variables: dummy pre_post and a dummy for treatment and control.
> I want to see, how investments changed from 2007 to 2008 for the treated / control firms.
>
> I generated a treatment dummy, labeling a firm as treated when Short Term Debt / Total LTDebt > 20 %. All others belong to the control group, such that treatment is equal to 1 and control is equal to 0.
> I did the same for the pre_post dummy.  generate post_2007 = (Year >= 2007)
>
> Then I generated a interaction term: gen interaction = post_2007*treatment_
>
> Finally I regressed: reg corporate_investments post_2007 treatment_ interaction
>
> This lead to an output of R^2 = 0.003 which is pretty bad. What could be the reason ?
> Can someone help me with the difference in difference approach ?
> Did I generate wrong dummys ?
>
> Thanks
>
> Julian
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