IDEAS home Printed from https://ideas.repec.org/a/bla/econom/v86y2019i342p396-408.html
   My bibliography  Save this article

Note on Idea Diffusion Models with Cohort Structures

Author

Listed:
  • Santiago Caicedo

Abstract

In this note I propose two alternative frameworks to study idea diffusion models with cohort structures. Both frameworks fix the Lucas (2009) aggregation mistake while keeping the analytical tractability of the model and its insights. The frameworks differ in their assumptions on the meeting process. I study first a continuous arrival process where agents meet at each point in time, and then a more commonly used Poisson process where meeting opportunities arrive stochastically at some given Poisson rate. I generalize the growth formula in Lucas (2009) and show that both models yield the same growth rate on a balanced growth path. Moreover, I show that the continuous arrival process can be viewed as the limit of Poisson processes where the meeting rate increases but the quality of meetings decreases.

Suggested Citation

  • Santiago Caicedo, 2019. "Note on Idea Diffusion Models with Cohort Structures," Economica, London School of Economics and Political Science, vol. 86(342), pages 396-408, April.
  • Handle: RePEc:bla:econom:v:86:y:2019:i:342:p:396-408
    DOI: 10.1111/ecca.12273
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/ecca.12273
    Download Restriction: no

    File URL: https://libkey.io/10.1111/ecca.12273?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Robert E. Lucas Jr. & Benjamin Moll, 2014. "Knowledge Growth and the Allocation of Time," Journal of Political Economy, University of Chicago Press, vol. 122(1), pages 1-51.
    2. Robert E. Lucas, 2009. "Ideas and Growth," Economica, London School of Economics and Political Science, vol. 76(301), pages 1-19, February.
    3. Jess Benhabib & Jesse Perla & Christopher Tonetti, 2021. "Reconciling Models of Diffusion and Innovation: A Theory of the Productivity Distribution and Technology Frontier," Econometrica, Econometric Society, vol. 89(5), pages 2261-2301, September.
    4. Fernando E. Alvarez & Francisco J. Buera & Robert E. Lucas, Jr., 2008. "Models of Idea Flows," NBER Working Papers 14135, National Bureau of Economic Research, Inc.
    5. Erzo G. J. Luttmer, 2012. "Eventually, noise and imitation implies balanced growth," Working Papers 699, Federal Reserve Bank of Minneapolis.
    6. Francisco J. Buera & Ezra Oberfield, 2020. "The Global Diffusion of Ideas," Econometrica, Econometric Society, vol. 88(1), pages 83-114, January.
    7. Stantcheva, Stefanie & Akcigit, Ufuk & Caicedo Soler, Santiago & Miguelez, Ernest & Sterzi, Valerio, 2018. "Dancing with the Stars: Innovation through Interactions," CEPR Discussion Papers 12819, C.E.P.R. Discussion Papers.
    8. Staley, Mark, 2011. "Growth and the diffusion of ideas," Journal of Mathematical Economics, Elsevier, vol. 47(4-5), pages 470-478.
    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. Nelson Lind & Natalia Ramondo, 2023. "Global Innovation and Knowledge Diffusion," American Economic Review: Insights, American Economic Association, vol. 5(4), pages 494-510, December.
    2. Nelson Lind & Natalia Ramondo, 2018. "Innovation, Knowledge Diffusion, and Globalization," NBER Working Papers 25071, National Bureau of Economic Research, Inc.
    3. Jess Benhabib & 'Eric Brunet & Mildred Hager, 2020. "Innovation and imitation," Papers 2006.06315, arXiv.org, revised Aug 2020.
    4. Francisco J. Buera & Ezra Oberfield, 2020. "The Global Diffusion of Ideas," Econometrica, Econometric Society, vol. 88(1), pages 83-114, January.
    5. Eero Mäkynen, 2021. "Economic Growth through Worker Reallocation: The Role of Knowledge Spillovers," Discussion Papers 147, Aboa Centre for Economics.
    6. Gao, Yijin, 2020. "Knowledge Diffusion and economic Growth based on Fourier’s law," Research in Economics, Elsevier, vol. 74(2), pages 174-185.
    7. Olivier Gallay & Fariba Hashemi & Max-Olivier Hongler, 2019. "Imitation, Proximity, And Growth — A Collective Swarm Dynamics Approach," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-43, August.
    8. Jess Benhabib & Jesse Perla & Christopher Tonetti, 2021. "Reconciling Models of Diffusion and Innovation: A Theory of the Productivity Distribution and Technology Frontier," Econometrica, Econometric Society, vol. 89(5), pages 2261-2301, September.
    9. Tubiana, Matteo & Miguelez, Ernest & Moreno, Rosina, 2022. "In knowledge we trust: Learning-by-interacting and the productivity of inventors," Research Policy, Elsevier, vol. 51(1).
    10. Erzo G. J. Luttmer, 2014. "An Assignment Model of Knowledge Diffusion and Income Inequality," Working Papers 715, Federal Reserve Bank of Minneapolis.
    11. Erzo G. J. Luttmer, 2015. "Four Models of Knowledge Diffusion and Growth," Working Papers 724, Federal Reserve Bank of Minneapolis.
    12. Jonathan Chiu & Cesaire Meh & Randall Wright, 2011. "Innovation and growth with financial, and other, frictions," Working Papers 688, Federal Reserve Bank of Minneapolis.
    13. , & Lorenz, Jan & ,, 2016. "Innovation vs. imitation and the evolution of productivity distributions," Theoretical Economics, Econometric Society, vol. 11(3), September.
    14. Gregor Jarosch & Ezra Oberfield & Esteban Rossi‐Hansberg, 2021. "Learning From Coworkers," Econometrica, Econometric Society, vol. 89(2), pages 647-676, March.
    15. Staley, Mark, 2015. "Firm Growth and Selection in a Finite Economy," MPRA Paper 67291, University Library of Munich, Germany.
    16. Kjetil Storesletten & Bo Zhao & Fabrizio Zilibotti, 2019. "Business Cycle during Structural Change: Arthur Lewis' Theory from a Neoclassical Perspective," Cowles Foundation Discussion Papers 2191, Cowles Foundation for Research in Economics, Yale University.
    17. Jean Imbs & Basile Grassi, 2015. "Why Do Risky Sectors Grow Fast?," 2015 Meeting Papers 449, Society for Economic Dynamics.
    18. Erzo G. J. Luttmer, 2020. "Bounded Learning from Incumbent Firms," Working Papers 771, Federal Reserve Bank of Minneapolis.
    19. Basile Grassi & Vasco Carvalho, 2015. "Firm Dynamics and the Granular Hypothesis," 2015 Meeting Papers 617, Society for Economic Dynamics.
    20. Kishi, Keiichi & Okada, Keisuke, 2018. "Trade Liberalization, Technology Diffusion, and Productivity," MPRA Paper 88597, University Library of Munich, Germany.

    More about this item

    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:bla:econom:v:86:y:2019:i:342:p:396-408. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.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.