[Guest]

reghdfe is straight up DID.

The first two regressions are simply separating it out by country to tell you how they changed. The DID estimator can be computed, but hypothesis testing is straightforward with the reghdfe model.

the second set of regressions is similar but includes an industry fixed effect.

try this.

preserve
collapse (mean) sdq_score , by(industry post treated)
* you'll have 60 observations in each period.
reg sdq_score c.treated#c.post post treated
restore

or

preserve
collapse (mean) sdq_score [aw=companysize], by(industry post treated)
reg sdq_score c.treated#c.post post treated
restore

The latter weights the sdq_score by company size when computing the mean.

Hi George, here is an update, hopefully you could help me fix it. I did not use your approach because I do not find the postestimator to extract graphs afterwards. Instead I used the DID Panel Data from menu.

gen id = _n
order id
reshape long x , i(id) j(year)
xtset id
encode country, generate (country_n)
encode companyname, generate (company_n)
egen panel_id = group (year company_n)
xtset panel_id
g lcompanysize = ln(companysize
g post = year>=2017
g treated = country == "treatedcountry"
 g posttreated = post * treated

It seems all fine until here, then when I try to use DID Panel-Data Fe

xtdidregress (esgscore) (post), group(treated) time(year)

this is the error I get: invalid group specification
None of the groups defined by treated is a control.

Thank you!

[Guest]

I need to have a similar graph to this one:

[George Ford]

ssc install lgraph

lgraph esgscore year, by(treated)

[Guest]

I am getting a linear upward trend for the untreated post-treatment. Wondering, if that is realistic or anything wrong with the calculation..?

[Guest]

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