Background information:
The investigation is under event study framework. The topic is on how the conversion to academies affects students' KS4 performance. The dataset is at school-level. Conversion before 2009 would be in the treatment group while schools converted after 2009 would be in the control group. I have school-level students' performance from year 2002 to year 2009. From year 2006 to year 2009 every year there were conversion taking place.
Therefore, in my dataset, there are two groups: the control group contains schools didn't convert to academies up to the year 2009; the treatment group is those converted to academies before (including year 2009) , but the conversion took place in different years.
Variable explanation:
year is the year when the data is observed
schstdks4_cappedpts is the average KT4 performance of a school
earlyconverters =1 for those converted to academies up to 2009; =0 otherwise
Suppose year=c is the year when the conversion took place;
afterconversion =1 if the $year\geqslant c$
Problem:
I was hoping to get DID coefficient by
regress schstdks4_cappedpts i.year earlyconverters#afterconversion, r
What I found puzzling is:
Linear regression Number of obs = 816
F(9, 806) = 7.81
Prob > F = 0.0000
R-squared = 0.0679
Root MSE = .39251
-------------------------------------------------------------------------------------------------
| Robust
schstdks4_cappedpts | Coef. Std. Err. t P>|t| [95% Conf. Interval]
--------------------------------+----------------------------------------------------------------
year |
2003 | -.2799424 .2312072 -1.21 0.226 -.7337818 .1738969
2004 | -.2039077 .2140511 -0.95 0.341 -.624071 .2162556
2005 | -.200673 .208598 -0.96 0.336 -.6101324 .2087864
2006 | -.1890817 .206715 -0.91 0.361 -.5948449 .2166816
2007 | -.1416356 .2069297 -0.68 0.494 -.5478203 .2645492
2008 | -.0700349 .2070475 -0.34 0.735 -.4764509 .336381
2009 | -.017034 .2091049 -0.08 0.935 -.4274884 .3934205
|
earlyconverters#afterconversion |
0 1 | 0 (empty)
1 0 | .1236718 .0343675 3.60 0.000 .0562113 .1911322
1 1 | .1886763 .0400589 4.71 0.000 .1100443 .2673084
|
_cons | -.3158101 .2065066 -1.53 0.127 -.7211644 .0895441
I don't understand why would I have coefficient for (earlyconverter==1)*(afterconversion=0), shouldn't this combination in theory==0?
If the model set up is correct, (earlyconverters==1#afterconversion==0) is supposed to measure?