Note, we have programmed this methodology to accommodate “external analyses” for comparative hypothesis testing and model comparisons. For example, one can test a derived estimated solution against any proposed alternative solution, and utilize one of the many information heuristics to designate which solution was “better” fit by the data. Here, for example, given an alternative, pre-specified clustering of firms, one can fix the posterior probabilities of membership, average them to obtain estimates of the mixing proportions, and perform one iteration of the M -step to obtain estimates of _s ; and _B by given cluster or group. We will utilize this handy feature of the proposed methodology to compare our derived solution with a one-group solution (i.e. ignoring structural heterogeneity in firm capabilities affecting performance).