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The complexity of the intangible digital economy: an agent-based model

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  • Bertani, Filippo
  • Ponta, Linda
  • Raberto, Marco
  • Teglio, Andrea
  • Cincotti, Silvano

Abstract

During the last decades, we have witnessed a strong development of intangible digital technologies. Software, artificial intelligence and algorithms are increasingly affecting both production systems and our lives; economists have started to figure out the long-run complex economic implications of this new technological wave. In this paper, we address this question through the agent-based modelling approach. In particular, we enrich the macroeconomic model Eurace with the concept of intangible digital technology and investigate its effects both at the micro and macro level. Results show the emergence of the relevant stylized facts observed in the business domain, such as increasing returns, winner-take-most phenomena and market lock-in. At the macro level, our main finding is an increasing unemployment level, since the sizeable decrease of the employment rate in the mass-production system, provided by the higher productivity of digital assets, is usually not counterbalanced by the new jobs created in the digital sector.

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  • Bertani, Filippo & Ponta, Linda & Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2019. "The complexity of the intangible digital economy: an agent-based model," MPRA Paper 97071, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:97071
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    Cited by:

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    2. João Amador & Cátia Silva, 2023. "A view on ICT and digitalization in Portuguese firms," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    3. Shouwu Jing & Feijie Wu & Enyi Shi & Xinhui Wu & Minzhe Du, 2023. "Does the Digital Economy Promote the Reduction of Urban Carbon Emission Intensity?," IJERPH, MDPI, vol. 20(4), pages 1-22, February.
    4. Silvano Cincotti & Marco Raberto & Andrea Teglio, 2022. "Why do we need agent-based macroeconomics?," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 5-29, April.
    5. Domenico Delli Gatti & Roberta Terranova & Enrico Maria Turco, 2023. "Mind the Knowledge Gap! The Origins of Declining Business Dynamism in a Macro Agent-Based Model," CESifo Working Paper Series 10694, CESifo.
    6. Filippo Bertani & Marco Raberto & Andrea Teglio, 2020. "The productivity and unemployment effects of the digital transformation: an empirical and modelling assessment," Review of Evolutionary Political Economy, Springer, vol. 1(3), pages 329-355, November.
    7. Xing, Jack Linzhou & Sharif, Naubahar, 2020. "From creative destruction to creative appropriation: A comprehensive framework," Research Policy, Elsevier, vol. 49(7).
    8. Wei Zhang & Siqi Zhao & Xiaoyu Wan & Yuan Yao, 2021. "Study on the effect of digital economy on high-quality economic development in China," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-27, September.
    9. Samuli Laato & Matti Mäntymäki & A. K.M. Najmul Islam & Sami Hyrynsalmi & Teemu Birkstedt, 2023. "Trends and Trajectories in the Software Industry: implications for the future of work," Information Systems Frontiers, Springer, vol. 25(2), pages 929-944, April.
    10. LIU, Nian & GU, Xinhua & LEI, Chun Kwok, 2022. "The equilibrium effects of digital technology on banking, production, and employment," Finance Research Letters, Elsevier, vol. 49(C).
    11. Ponta, Linda & Puliga, Gloria & Lazzarotti, Valentina & Manzini, Raffaella & Cincotti, Silvano, 2023. "To copatent or not to copatent: An agent-based model for firms facing this dilemma," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1349-1363.
    12. Salvi, Antonio & Vitolla, Filippo & Rubino, Michele & Giakoumelou, Anastasia & Raimo, Nicola, 2021. "Online information on digitalisation processes and its impact on firm value," Journal of Business Research, Elsevier, vol. 124(C), pages 437-444.
    13. Xu, Shengxiang & Chen, Hsinghung & Dong, Shuli & Guo, Zizheng, 2023. "Can upgrading information infrastructure improve the innovation ability of companies? Empirical evidence from China," Telecommunications Policy, Elsevier, vol. 47(6).
    14. Yang Li & An-Chi Liu & Shu-Mei Wang & Yiting Zhan & Jingran Chen & Hsiao-Fen Hsiao, 2022. "A Study of Total-Factor Energy Efficiency for Regional Sustainable Development in China: An Application of Bootstrapped DEA and Clustering Approach," Energies, MDPI, vol. 15(9), pages 1-13, April.
    15. Qinqin Wu & Mengjie Bi & Faiza Siddiqui & Yao Tang, 2023. "Assessing the Impact of Digital Trade on Enterprise Competitiveness: Evidence from Chinese A-Share Listed Companies," Journal of Industry, Competition and Trade, Springer, vol. 23(3), pages 329-362, December.

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    More about this item

    Keywords

    Intangible assets; Digital transformation; Technological unemployment; Agent-based economics;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • 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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