Dear researchers,
I have unbalanced panel data for a set of firms. In 2002 a new standard has been issued, and accordingly, firms started to adopt the standard, but the adoption process is not simultaneous. I mean a group of firms adopted in 2005, other groups adopted in 2003, and so on (i.e., the adoption is in different years). The following table is an example of my dataset.
Firms Year Event Leverage
A 2000 0 1.23
A 2001 0 0.45
A 2002 0 0.435
A 2003 0 0.675
A 2004 0 0.896
A 2005 1 0.6043
A 2006 1 0.56
A 2007 1 0.5157
A 2008 1 0.4714
B 2000 0 0.4271
B 2001 0 0.3828
B 2002 0 0.3385
B 2003 1 0.2942
B 2004 1 0.2499
B 2005 1 0.2056
B 2006 1 0.1613
As far as I know that if I want to see if there is a significant difference in leverage before and after the adoption of the standards, the number of observations before the adoption should equal the number of observation after the adoption, Am I correct? if no, then can I use the Independent sample t-test, or what I should do?
The code that I have used is:
Code:
ttest Leverage, by(Event)


Please advise.

Many thanks in advance.