Hi, I'm doing a difference-in-difference analysis on how the ESG reform in Hong Kong affected firm value. My study period ranges from 2013-2017 with the shock happening in 2016.

I have performed a univariate difference-in-difference but I'm not sure how to interpret the results.
The code I used was: diff tobinq_w if fisc_year>=2014 & fisc_year<=2017, t( treatment_vol) p( crisis)
treatment_vol is a dummy variable that gets a value of 1 if firms have complied with the reform and crisis is a dummy variable that gets a value of 1 if the years are 2016 and 2017
These are my results
DIFFERENCE-IN-DIFFERENCES ESTIMATION RESULTS
Number of observations in the DIFF-IN-DIFF: 6174
Before After
Control: 2846 2906 5752
Treated: 160 262 422
3006 3168
--------------------------------------------------------
Outcome var. | tobin~w | S. Err. | |t| | P>|t|
----------------+---------+---------+---------+---------
Before | | | |
Control | 1.888 | | |
Treated | 1.317 | | |
Diff (T-C) | -0.570 | 0.168 | -3.40 | 0.001***
After | | | |
Control | 1.798 | | |
Treated | 1.515 | | |
Diff (T-C) | -0.283 | 0.133 | 2.12 | 0.034**
| | | |
Diff-in-Diff | 0.288 | 0.215 | 1.34 | 0.180
--------------------------------------------------------
R-square: 0.00
* Means and Standard Errors are estimated by linear regression
**Inference: *** p<0.01; ** p<0.05; * p<0.1
Diff (T-C) is significant for before and after, so does that mean the reform had a positive effect on firm value?

really appreciate any help i can get! Thanks in advance