[Felix Bittmann]

The idea is that the entropy balancing approach creates a weight that accounts for all control variables that perfectly balances treatment and control group. So to say, the "effect" of the controls is included in the weight.

[Sattar Khan]

The idea is that the entropy balancing approach creates a weight that accounts for all control variables that perfectly balances treatment and control group. So to say, the "effect" of the controls is included in the weight.

Thank you so much again, Can you please guide me that which tables should I report in my article?

[Felix Bittmann]

First, I would report the output from

kmatch sum

This (hopefully) proves that all controls are balanced after the matching procedure.
Then you can show the distribution of the weights:

graph box weight if weight > 0

Finally, of course, the regression table. I am not sure how you want to present the 3-term-interaction. If the raw regression table is very difficult to interpret, you can use margins to simplify the interpretation:

regress...
margins, dydx(NOe_w) by(affiliation1 thesamenetworkauditor) vce(uncond)