IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/4739.html
   My bibliography  Save this paper

Learning By Doing and the Choice of Technology

Author

Listed:
  • Boyan Jovanovic
  • Yaw Nyarko

Abstract

This paper explores a one-agent Bayesian model of learning by doing and technological choice. To produce output, the agent can choose among various technologies. The beneficial effects of learning by doing are bounded on each technology, and so long-run growth in output can take place only if the agent repeatedly switches to better technologies. As the agent repeatedly uses a technology, he learns about its unknown parameters, and this accumulated expertise is a form of human capital. But when the agent switches technologies, part of this human capital is lost. It is this loss of human capital that may prevent the agent from moving up the quality ladder of technologies as quickly as he can, since the loss is greater the bigger is the technological leap. We analyze the global dynamics. We find that a human-capital- rich agent may find it optimal to avoid any switching of technologies, and therefore to experience no long-run growth. On the other hand, a human-capital-poor agent, who because of his lack of skill is not so attached to any particular technology, can find it optimal to switch technologies repeatedly, and therefore enjoy long-run growth in output. Thus the model can give rise to overtaking.

Suggested Citation

  • Boyan Jovanovic & Yaw Nyarko, 1994. "Learning By Doing and the Choice of Technology," NBER Working Papers 4739, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:4739
    Note: PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w4739.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nyarko, Yaw, 1994. "On the Convexity of the Value Function in Bayesian Optimal Control Problems," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 4(2), pages 303-309, March.
    2. Robert Wilson, 1975. "Informational Economies of Scale," Bell Journal of Economics, The RAND Corporation, vol. 6(1), pages 184-195, Spring.
    3. Stephen L. Parente & Edward C. Prescott, 1991. "Technology adoption and growth," Staff Report 136, Federal Reserve Bank of Minneapolis.
    4. Nancy L. Stokey, 1991. "Human Capital, Product Quality, and Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(2), pages 587-616.
    5. Prescott, Edward C, 1972. "The Multi-Period Control Problem Under Uncertainty," Econometrica, Econometric Society, vol. 40(6), pages 1043-1058, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    2. Jorge Saba Arbache, 2001. "Trade Liberalisation and Labor Markets in Developing Countries: Theory and Evidence," Studies in Economics 0112, School of Economics, University of Kent.
    3. Silvio Rendón, 2002. "Informational matching," Economics Working Papers 619, Department of Economics and Business, Universitat Pompeu Fabra.
    4. Matthew F. Mitchell, 2000. "The scale of production in technological revolutions," Staff Report 269, Federal Reserve Bank of Minneapolis.
    5. Assaf Razin & Chi‐Wa Yuen, 1997. "Factor Mobility and Income Growth: Two Convergence Hypotheses," Review of Development Economics, Wiley Blackwell, vol. 1(2), pages 171-190, June.
    6. Ruttan, Vernon W., 1998. "Growth Economics And Development Economics: What Should Development Economists Learn (If Anything) From The New Growth Theory?," Bulletins 12972, University of Minnesota, Economic Development Center.
    7. Raffaello Bronzini & Paolo Piselli, 2006. "Determinants of long-run regional productivity: the role of R&D, human capital and public infrastructure," Temi di discussione (Economic working papers) 597, Bank of Italy, Economic Research and International Relations Area.
    8. Peter John Robinson & W. J. Wouter Botzen & Fujin Zhou, 2021. "An experimental study of charity hazard: The effect of risky and ambiguous government compensation on flood insurance demand," Journal of Risk and Uncertainty, Springer, vol. 63(3), pages 275-318, December.
    9. Richard S. J. Tol & In Chang Hwang & Frédéric Reynès, 2012. "The Effect of Learning on Climate Policy under Fat-tailed Uncertainty," Working Paper Series 5312, Department of Economics, University of Sussex Business School.
    10. Martin Peitz & Sven Rady & Piers Trepper, 2017. "Experimentation in Two-Sided Markets," Journal of the European Economic Association, European Economic Association, vol. 15(1), pages 128-172.
    11. Andersson, Fredrik N.G. & Edgerton, David L. & Opper, Sonja, 2013. "A Matter of Time: Revisiting Growth Convergence in China," World Development, Elsevier, vol. 45(C), pages 239-251.
    12. Liverpool-Tasie, Lenis Saweda O. & Winter-Nelson, Alex, 2009. "Poverty status and the impact of social networks on smallholder technology adoption in rural Ethiopia," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49357, Agricultural and Applied Economics Association.
    13. Qing Li & Long Hai Vo, 2021. "Intangible Capital and Innovation: An Empirical Analysis of Vietnamese Enterprises," Economics Discussion / Working Papers 21-02, The University of Western Australia, Department of Economics.
    14. Andres Rodriguez-Clare, 1996. "The role of trade in technology diffusion," Discussion Paper / Institute for Empirical Macroeconomics 114, Federal Reserve Bank of Minneapolis.
    15. Wieland, Volker, 2000. "Monetary policy, parameter uncertainty and optimal learning," Journal of Monetary Economics, Elsevier, vol. 46(1), pages 199-228, August.
    16. Bobonis, Gustavo J. & Morrow, Peter M., 2014. "Labor coercion and the accumulation of human capital," Journal of Development Economics, Elsevier, vol. 108(C), pages 32-53.
    17. Andrés Rodríguez-Clare, 2005. "Innovation and Technology Adoption in Central America," Research Department Publications 4395, Inter-American Development Bank, Research Department.
    18. Boyan Jovanovic, 1993. "The Diversification of Production," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 24(1 Microec), pages 197-247.
    19. Angelina Shpilevaya, 2022. "Overview of General Equilibrium Models with Imperfect Financial Markets and the Accumulation of Human Capital," Russian Journal of Money and Finance, Bank of Russia, vol. 81(3), pages 54-71, September.
    20. Jiarui Han & Tze Lai & Viktor Spivakovsky, 2006. "Approximate Policy Optimization and Adaptive Control in Regression Models," Computational Economics, Springer;Society for Computational Economics, vol. 27(4), pages 433-452, June.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:4739. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.