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The Long-Run Productivity Effects of Technology Adoption: Evidence from France - Mara Squicciarini (Bocconi University)

DeFiPP Seminar

Catégorie : animation
Date : 03/12/2019 16:00 - 03/12/2019 17:30
Lieu : Salle C. Joset
Organisateur(s) : Guilhem Cassan

Abstract: We construct a unique dataset to examine the evolution of firm productivity during a period of rapid technological change: The diffusion of mechanized cotton spinning during the Industrial Revolution in France. Before mechanization, cotton spinning was performed in households. Production in firms only emerged with the new technology around 1800, allowing us to isolate the productivity distribution for firms that use the new technology. We contrast the long-run productivity effects of technology adoption in cotton spinning with two comparison sectors – metallurgy and paper milling. We document several stylized facts that can explain the well-documented puzzle that major technological breakthroughs tend to be adopted slowly across firms and – even after being adopted – take time to be reflected in higher aggregate productivity: Relative to the comparison sectors, the productivity of firms in cotton spinning was initially highly dispersed and characterized by low firm survival. Over the subsequent decades, cotton spinning experienced dramatic productivity growth that was almost entirely driven by a disappearance of firms in the lower tail, while innovations in the comparison sectors shifted the whole productivity distribution. Rich historical evidence suggests that these patterns were driven by the need to re-organize production under the new technology. This process of ‘trial and error’ led to widely dispersed initial productivity ‘draws,’ low initial average productivity, and – in the subsequent decades – to high productivity growth as new entrants adopted improved methods of production and organization. We show document several pieces of evidence consistent with our proposed mechanism. 

This work is co-authored with Reka Juhasz and Nico Voigtlaender.

Contact : Guilhem Cassan - guilhem.cassan@unamur.be
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