Distinguishing Different Industry Technologies and Localized Technical Change

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.