Distinguishing Different Industry Technologies and Localized Technical Change
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When different technologies are present in an industry, assuming a homogeneous technology
will lead to misleading implications about technical change and inefficient policy
recommendations. In this paper a latent class modelling approach and flexible estimation of the
production structure is used to distinguish different technologies for a representative sample of
E.U. dairy producers, as an industry exhibiting significant structural changes and differences in
production systems in the past decades. The model uses a transformation function to recognize
multiple outputs; separate technological classes based on multiple characteristics, a flexible
generalized linear functional form, a variety of inputs, and random effects to capture firm
heterogeneity; and measures of first- and second-order elasticities to represent technical
change and biases. We find that if multiple production frontiers are embodied in the data,
different firms exhibit different output or input intensities and changes associated with different
production systems that are veiled by overall (average) measures. In particular, we find that
farms that are larger and more capital intensive experience greater productivity, technical
progress and labor savings, and enjoy scale economies that have increased over time.