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This study constructs a multiple error component Bayesian stochastic frontier model to analyze
production efficiencies of Korean farm households incorporating farm heterogeneity. A sampled
data set of 400 farms for the period 2008-2012 is used. The analysis combines a Bayesian random
effect multilevel/hierarchical model with a panel data stochastic frontier model. The results show
that the usual SFA models without incorporating producer heterogeneity substantially over-estimate
the level and dispersion of farm technical inefficiencies. It is also found that incorporating producer
heterogeneity into the production frontier reduces the contribution of technical efficiency change
to productivity change significantly. The study identifies the sources of frontier heterogeneity using
the constructed multiple error component Bayesian SFA model.
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