When should I use a fixed effects option versus random effects option?

When it is statistically justifiable with respect to a specific data set, the random effects option is to be preferred because the estimates will have higher precision than those obtained from the fixed effects model option. However, the random effects model is based on a strong assumption, namely, the unobserved effects due to an entity are uncorrelated with the values of the other independent variables. The Hausman test is used to assess the validity of this assumption. On the other hand, if the random effects model is not justified, we use the fixed effects model (provided there are statistically significant differences between the estimated fixed effects associated with the entities). One disadvantage of the fixed effects specification is that we cannot include in the analysis independent variables that are entity-specific and do not vary across occasions for the same entity (e.g., gender of an individual, if the entity is an individual).