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Diversity and Technological Progress

In: The Rate and Direction of Inventive Activity Revisited

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  • Daron Acemoglu

Abstract

This paper proposes a tractable model to study the equilibrium diversity of technological progress and shows that equilibrium technological progress may exhibit too little diversity (too much conformity), in particular, foregoing socially beneficial investments in "alternative" technologies that will be used at some point in the future. The presence of future innovations that will replace current innovations imply that social benefits from innovation are not fully internalized. As a consequence, the market favors technologies that generate current gains relative to those that will bear fruit in the future; current innovations in research lines that will be profitable in the future are discouraged because current innovations are typically followed by further innovations before they can be profitably marketed. A social planner would choose a more diverse research portfolio and would induce a higher growth rate than the equilibrium allocation. The diversity of researchers is a partial (imperfect) remedy against the misallocation induced by the market. Researchers with different interests, competences or ideas may choose non-profit maximizing and thus more diverse research portfolios, indirectly contributing to economic growth.
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Suggested Citation

  • Daron Acemoglu, 2011. "Diversity and Technological Progress," NBER Chapters, in: The Rate and Direction of Inventive Activity Revisited, pages 319-356, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberch:12358
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    Cited by:

    1. Miles Parker & Andrew Acland & Harry J Armstrong & Jim R Bellingham & Jessica Bland & Helen C Bodmer & Simon Burall & Sarah Castell & Jason Chilvers & David D Cleevely & David Cope & Lucia Costanzo & , 2014. "Identifying the Science and Technology Dimensions of Emerging Public Policy Issues through Horizon Scanning," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-17, May.
    2. Agnieszka Lipieta & Elżbieta Pliś, 2022. "Diversity and mechanisms of economic evolution," Journal of Evolutionary Economics, Springer, vol. 32(4), pages 1265-1286, September.
    3. Yang, Xiuyun & Li, Min & Liang, Shanshan, 2024. "How consumers’ digital engagement affects regional innovation capacity in China?," Economic Modelling, Elsevier, vol. 139(C).
    4. Badarinza, Cristian & Gross, Marco, 2011. "Macroeconomic vulnerability and disagreement in expectations," Working Paper Series 1407, European Central Bank.
    5. Aalbers, Rob & Shestalova, Victoria & Kocsis, Viktória, 2013. "Innovation policy for directing technical change in the power sector," Energy Policy, Elsevier, vol. 63(C), pages 1240-1250.
    6. Wang, Jinxiu & Deng, Kun, 2022. "Impact and mechanism analysis of smart city policy on urban innovation: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 574-587.
    7. Elżbieta Pliś, 2020. "Diversity and Innovation in Economic Evolution," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(4), pages 347-367, December.
    8. Guo, Qingbin & Zhong, Jinrong, 2022. "The effect of urban innovation performance of smart city construction policies: Evaluate by using a multiple period difference-in-differences model," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    9. Bryan, Kevin A. & Lemus, Jorge, 2017. "The direction of innovation," Journal of Economic Theory, Elsevier, vol. 172(C), pages 247-272.
    10. Gans, Joshua S., 2025. "Regulating the direction of innovation," Journal of Public Economics, Elsevier, vol. 246(C).
    11. Marcin Woźniak, 2015. "Can the Stochastic Equilibrium Job Search Models Fit Transition Economies?," Acta Oeconomica, Akadémiai Kiadó, Hungary, vol. 65(4), pages 567-591, December.
    12. Lu, Danning & Hui, Eddie Chi Man & Shen, Jianfu & Shi, Jianxun, 2024. "Digital industry agglomeration and urban innovation: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 1998-2025.

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    More about this item

    JEL classification:

    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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