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Learning-by-doing and the sources of productivity growth: A dynamic model with application to U.S. agriculture

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Abstract

The significance of learning to productivity growth is formulated within a dynamic adjustment-cost framework. Explicitly treating the acquisition of knowledge as a firm-specific capital good entering the production function along with other conventional inputs, the dynamic optimization model integrates the learning-by-doing hypothesis with technical change, scale, and disequilibrium input use effects in the aggregate productivity analysis. The theoretical framework is applied to examining the dynamic components accounting for the growth of U.S. production agriculture over the 1950–82 period. The results imply a less important role for technical change and assign a substantial role to the previously unmeasured contribution of learning-by-doing to the growth of aggregate agriculture industry.

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The editor for this paper was Melvyn Fuss.

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Luh, Y., Stefanou, S.E. Learning-by-doing and the sources of productivity growth: A dynamic model with application to U.S. agriculture. J Prod Anal 4, 353–370 (1993). https://doi.org/10.1007/BF01073544

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Keywords

  • Optimization Model
  • Production Function
  • Productivity Growth
  • Technical Change
  • Productivity Analysis