Interpretation Beta coefficient regression gamma distribution I am currently working on a panel data model of 30 companies over 10 years where the dependent variable is a score (decimal bounded between 0 and 1, continuous) while the independent are dummies and their lags. 
I ran different models on Stata, but the only one fitting my data is generalized estimating equations (GEE) with family Gamma and link reciprocal, for which I get significant result. 
My question is: how do I interpret the coefficients? they are very big (eg -21, 18) and I know I can't interpret them as in the linear regression. 
 A: The documentation in xtxtgee stata is quite specific as to what this is. 
The reciprocal link is regression with the target (A.K.A., dependent variable linked to) being $\frac{1}{y}$, as contrasted to the usual $y$. In that software, the family(gamma) has link(reciprocal) as its default. The gamma referred to appears to be the gamma distribution PDF, which in stata has the form $$\operatorname{gammaden}(a,b,g,x)=
 \frac{(x-g)^{a-1} e^{-\frac{x-g}{b}}}{\Gamma (a)b^a}\,, \quad x>0 \,,$$ which is often used setting $g=0$ to become a two parameter distribution. 
Now since $a>0$ by definition, I think $a=-21$ says something is very wrong. It might help your cause if you were to show some I/O. It would not be too unusual to write the gamma distribution parameters as $\beta$ and $\theta$ but I cannot confirms this without more information.
The reason I say that this is probably the gamma distribution is because the table in the xtxtgee file lists
family                  Description
______________________________________________________________________ 
gaussian                Gaussian (normal); family(normal) is a synonym   
igaussian               inverse Gaussian
binomial [# | varname]  Bernoulli/binomial 
poisson                 Poisson 
nbinomial [#]           negative binomial 
gamma                   gamma

That is, everything else in the table besides "gamma" is a probability distribution. 
