For this reason it's usually the only accepted choice of estimator in economics, finance or disciplines dealing with observational data.

But I think this advice is misguided in a more fundamental way. The fixed-effects model provides only estimates of within-panel effects. If the research question specifically addresses between-panel effects (as appears to be the case here) then the fixed effects estimator is giving consistent estimates

*of the wrong parameter*. So the inconsistency of an OLS or random effects estimator just has to be accommodated by including as many covariates as you reasonably can and hope that you are left with errors that are uncorrelated or only weakly correlated with the predictors, and then you live with it.

## Comment