Hello Stata community,
I try to decide if I should choose a random or fixed model for my analysis.
To do this I utilize:
1. the Mundlak approach following:
https://blog.stata.com/2015/10/29/fi...dlak-approach/
With two time invariant variables. Alternatively I just included one.
bysort FIRM: egen mean_x3 = mean(x3) ... bysort FIRM: egen mean_x6 = mean(x6) quietly xtreg y x1 x2 x3 mean_x2 mean_x3, vce(robust) estimates store mundlak
test mean_x3 ... mean_x6 Result:
chi2( 10) = 28.44
Prob > chi2 = 0.0015
2. Alternatively I utilize xtoverid
xtreg y1 x1 ... x6, re
xtoverid , robust cluster(ID)
Sargan-Hansen statistic 24.298 Chi-sq(5) P-value = 0.0002
My question:
Is it fair to go for a fixed model, instead of a random effects model or did I miss something important/misused the tests?
I think the results suggest with enough confidence that I should utilize fixed effects.
I try to decide if I should choose a random or fixed model for my analysis.
To do this I utilize:
1. the Mundlak approach following:
https://blog.stata.com/2015/10/29/fi...dlak-approach/
With two time invariant variables. Alternatively I just included one.
bysort FIRM: egen mean_x3 = mean(x3) ... bysort FIRM: egen mean_x6 = mean(x6) quietly xtreg y x1 x2 x3 mean_x2 mean_x3, vce(robust) estimates store mundlak
test mean_x3 ... mean_x6 Result:
chi2( 10) = 28.44
Prob > chi2 = 0.0015
2. Alternatively I utilize xtoverid
xtreg y1 x1 ... x6, re
xtoverid , robust cluster(ID)
Sargan-Hansen statistic 24.298 Chi-sq(5) P-value = 0.0002
My question:
Is it fair to go for a fixed model, instead of a random effects model or did I miss something important/misused the tests?
I think the results suggest with enough confidence that I should utilize fixed effects.
Comment