You can't properly interpret an F-test on two models in the way that you did it. An F-test comparing two models requires them to be nested, in the sense that the predictors in one model form a subset of those in the other, and that the underlying data are the same. See this answer.
The best way to see if there is a difference between the 2 countries (which seems to be your interest) is to combine all the data, include an indicator variable for the
country, and run your regression model with the
country variable added to your set of predictors. The coefficient for the
country variable then represents the systematic difference between the 2 countries, with the other predictors taken into account.
If you perform the analysis that way you can do a proper F-test, comparing models with versus without the
country variable but both models built on all of the data for both countries. That will document the "significance" of the difference between the countries.