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Modeling the transition to a new economy: lessons from two technological revolutions

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  • Andrew Atkeson
  • Patrick J. Kehoe

Abstract

Many view the period after the Second Industrial Revolution as a paradigmatic example of a transition to a new economy following a technological revolution and conjecture that this historical experience is useful for understanding other transitions, including that after the Information Technology Revolution. We build a model of diffusion and growth to study transitions. We quantify the learning process in our model using data on the life cycle of U.S. manufacturing plants. This model accounts quantitatively for the productivity paradox, the slow diffusion of new technologies, and the ongoing investment in old technologies after the Second Industrial Revolution. The main lesson from our model for the Information Technology Revolution is that the nature of transition following a technological revolution depends on the historical context: transition and diffusion are slow only if agents have built up through learning a large amount of knowledge about old technologies before the transition begins.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Minneapolis in its series Staff Report with number 296.

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Date of creation: 2006
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Publication status: Published in American Economic Review> (Vol. 97, No. 1, March 2007, pp. 64-88)
Handle: RePEc:fip:fedmsr:296

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Keywords: Technological innovations;

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References

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Citations

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Cited by:
  1. Hernan Moscoso Boedo & Pablo D'Erasmo, 2010. "Financial Structure, Informality and Development," 2010 Meeting Papers 319, Society for Economic Dynamics.
  2. Klaus Desmet & Esteban Rossi-Hansberg, 2007. "Spatial Growth and Industry Age," NBER Working Papers 13302, National Bureau of Economic Research, Inc.
  3. Parantap Basu & Alessandra Guariglia, 2008. "Does Low Education Delay Structural Transformation?," Southern Economic Journal, Southern Economic Association, vol. 75(1), pages 104-127, July.
  4. Dan Cao & Jean-Paul L'Huillier, 2012. "Technological Revolutions and Debt Hangovers - Is There a Link?," EIEF Working Papers Series 1216, Einaudi Institute for Economics and Finance (EIEF), revised Feb 2013.
  5. Hanno Lustig & Chad Syverson & Stijn Van Nieuwerburgh, 2009. "Technological Change and the Growing Inequality in Managerial Compensation," NBER Working Papers 14661, National Bureau of Economic Research, Inc.
  6. Yi-Chan Tsai, 2010. "News Shocks and Costly Technology Adoption," 2010 Meeting Papers 567, Society for Economic Dynamics.
  7. Virgiliu Midrigan & Daniel Yi Xu, 2014. "Finance and Misallocation: Evidence from Plant-Level Data," American Economic Review, American Economic Association, vol. 104(2), pages 422-58, February.
  8. Solomon, Bernard Daniel, 2010. "Firm leverage, household leverage and the business cycle," MPRA Paper 26504, University Library of Munich, Germany.
  9. Safarzyńska, Karolina & Frenken, Koen & van den Bergh, Jeroen C.J.M., 2012. "Evolutionary theorizing and modeling of sustainability transitions," Research Policy, Elsevier, vol. 41(6), pages 1011-1024.
  10. Daniel Schiess & Roger Wehrli, 2008. "The Calm Before the Storm? - Anticipating the Arrival of General Purpose Technologies," CER-ETH Economics working paper series 08/81, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
  11. Safarzynska, Karolina & van den Bergh, Jeroen C.J.M., 2011. "Industry evolution, rational agents and the transition to sustainable electricity production," Energy Policy, Elsevier, vol. 39(10), pages 6440-6452, October.

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