I'm learning the basic of panel data regression and there is something that i'm not sure about. There seems to be 2 different approachs to estimate FE models:
(1) Assuming that the slope is constant, and estimate the equation:
$$Y_{it} = \alpha_i + \beta X_{it} + e_{it} $$
Which is equal to using the normal OLS to each sample $i$ individually.
(2) By applying the Fixed Effects Transformation to estimate: $$( Y_{it} - \overline{Y_i}) = \beta ( X_{it} - \overline{X_i}) + (\epsilon_{it} - \overline{\epsilon_i})$$
Is the result of the two estimation methods (significantly) different? What are the pros and cons of each method and how do you choose one or another?
I've noticed in STATA the command xtreg,fe
uses the latter method(2), then how is the intercept estimated by this command and is it equal the mean of $\alpha_i$ estimated by method(1)?
English is not my native language and I'm fairly new to this site so I'm well open for advices. Thank you.