No need to generate interaction while using the hashtag method.The effect is significant at 10% level, with the treatment having a negative effect. The coefficient for ‘did’ is the difference-in-differences estimator.reg y time treated did, r Linear regression Number of obs = 70 F(3, 66) = 2.17 Prob > F = 0.0998 R-squared = 0.0827 Root MSE = 3.0e+09 - | Robust y | Coefficient std. Create an interaction between time and treated.Gen treated = (country>4) & !missing(country) In this example, let's assume that countries with codes 5, 6, and 7 were treated (=1). Create a dummy variable to identify the group exposed to the treatment.In this case, years before 1994 will have a value of 0, and years from 1994 onward a 1. Let's assume that the treatment started in 1994. Create a dummy variable to indicate the time when the treatment started.
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