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Productivity Decomposition in Heterogeneous Industries

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  • Giovanni Dosi
  • Marco Grazzi
  • Le Li
  • Luigi Marengo
  • Simona Settepanella

Abstract

We propose a novel methodology for computing variations of aggregate productivity and its decomposition into changes of individual firms’ productivities and of industry composition. Industry productivity should be measured in principle on industry total inputs and outputs but it is believed that this measure does not allow for such decomposition. Thus, weighted averages of individual productivities are used which introduce serious biases especially when industries are heterogeneous. We propose a geometric approach where aggregate productivity can be measured directly on industry data, but nevertheless its variations can be decomposed into between and within effects plus a heterogeneity effect.

Suggested Citation

  • Giovanni Dosi & Marco Grazzi & Le Li & Luigi Marengo & Simona Settepanella, 2021. "Productivity Decomposition in Heterogeneous Industries," Journal of Industrial Economics, Wiley Blackwell, vol. 69(3), pages 615-652, September.
  • Handle: RePEc:bla:jindec:v:69:y:2021:i:3:p:615-652
    DOI: 10.1111/joie.12252
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    References listed on IDEAS

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    4. S. Settepanella & A. Terni & M. Franciosi & L. Li, 2022. "The robustness of the generalized Gini index," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(2), pages 521-539, December.

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