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Implementing Technology

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  • Diego Comin
  • Bart Hobijn

Abstract

We introduce a tractable model of endogenous growth in which the returns to innovation are determined by the technology adoption decisions of the users of new technologies. Technology adoption involves an implementation investment that determines the initial productivity of a new technology. After implementation, learning increases the productivity of a technology to its full potential. In this framework, implementation enhances growth, while growth increases obsolescence and reduces implementation. In a calibrated version of our model, the optimal policy involves a subsidy to capital and to implementation and a R&D tax. This policy would lead to a welfare improvement of 7.6 percent. Out of steady-state analysis yields that the transitional dynamics of the detrended variables after a shock to capital are very similar to the dynamics of the neoclassical growth model, but transitory shocks have permanent effects on the level of productivity.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 12886.

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Date of creation: Feb 2007
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Handle: RePEc:nbr:nberwo:12886

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  1. Caselli, F. & Ventura, J., 1996. "A Representative Consumer Theory of Distribution," Working papers 96-11, Massachusetts Institute of Technology (MIT), Department of Economics.
  2. Acemoglu, Daron & Zilibotti, Fabrizio, 1998. "Productivity Differences," Seminar Papers 660, Stockholm University, Institute for International Economic Studies.
  3. Susanto Basu & David N. Weil, 1996. "Appropriate Technology and Growth," NBER Working Papers 5865, National Bureau of Economic Research, Inc.
  4. Diego Comin & Mark Gertler, 2006. "Medium-Term Business Cycles," American Economic Review, American Economic Association, vol. 96(3), pages 523-551, June.
  5. Parente, Stephen L & Prescott, Edward C, 1994. "Barriers to Technology Adoption and Development," Journal of Political Economy, University of Chicago Press, vol. 102(2), pages 298-321, April.
  6. Edward C. Prescott, 1997. "Needed: a theory of total factor productivity," Staff Report 242, Federal Reserve Bank of Minneapolis.
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  8. John C. Williams & Charles I. Jones, 1995. "Too much of a good thing? The economics of investment in R&D," Finance and Economics Discussion Series 95-39, Board of Governors of the Federal Reserve System (U.S.).
  9. Jan Eeckhout & Boyan Jovanovic, 2002. "Knowledge Spillovers and Inequality," American Economic Review, American Economic Association, vol. 92(5), pages 1290-1307, December.
  10. Aghion, P. & Howitt, P., 1989. "A Model Of Growth Through Creative Destruction," UWO Department of Economics Working Papers 8904, University of Western Ontario, Department of Economics.
  11. Charles I. Jones & John C. Williams, . "Measuring the Social Return to R&D," Working Papers 97002, Stanford University, Department of Economics.
  12. Reinganum, Jennifer F., 1989. "The timing of innovation: Research, development, and diffusion," Handbook of Industrial Organization, in: R. Schmalensee & R. Willig (ed.), Handbook of Industrial Organization, edition 1, volume 1, chapter 14, pages 849-908 Elsevier.
  13. Erik Brynjolfsson & Loren Hitt & Shinkyu Yang, 2002. "Intangible Assets: How the Interaction of Computers and Organizational Structure Affects Stock Market Valuations," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(1), pages 137-198.
  14. Carol A. Corrado & Charles R. Hulten & Daniel E. Sichel, 2006. "Intangible Capital and Economic Growth," NBER Working Papers 11948, National Bureau of Economic Research, Inc.
  15. Elias Dinopoulos & Douglas Waldo, 2005. "Gradual Product Replacement, Intangible-Asset Prices and Schumpeterian Growth," Journal of Economic Growth, Springer, vol. 10(2), pages 135-157, 06.
  16. Bahk, Byong-Hong & Gort, Michael, 1993. "Decomposing Learning by Doing in New Plants," Journal of Political Economy, University of Chicago Press, vol. 101(4), pages 561-83, August.
  17. Parente Stephen L., 1994. "Technology Adoption, Learning-by-Doing, and Economic Growth," Journal of Economic Theory, Elsevier, vol. 63(2), pages 346-369, August.
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Citations

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Cited by:
  1. Antonio Navas & Davide Sala, 2013. "Innovation and Trade Policy Coordination: the Role of Firm Heterogeneity," Working Papers 2013017, The University of Sheffield, Department of Economics.
  2. Antonio Navas-Ruiz & Davide Sala, 2007. "Technology Adoption and the Selection Effect of Trade," Economics Working Papers ECO2007/58, European University Institute.
  3. Diego Comin & Bart Hobijn, 2010. "Technology diffusion and postwar growth," Working Paper Series 2010-16, Federal Reserve Bank of San Francisco.
  4. Steven Cassou & Emanuel Xavier de Oliveira, 2011. "Barriers to technological adoption in Spain and Portugal," Portuguese Economic Journal, Springer, vol. 10(3), pages 189-209, December.
  5. Esteban Rossi-Hansberg & Luis Garicano, 2008. "Organizing Growth," 2008 Meeting Papers 247, Society for Economic Dynamics.
  6. Diego Comin & Bart Hobijn & Emilie Rovito, 2008. "Technology usage lags," Journal of Economic Growth, Springer, vol. 13(4), pages 237-256, December.
  7. Diego Comin & Bart Hobijn & Emilie Rovito, 2008. "A new approach to measuring technology with an application to the shape of the diffusion curves," The Journal of Technology Transfer, Springer, vol. 33(2), pages 187-207, April.

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