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AbstractWe are entering the third decade of the twenty-first century with profound uncertainties and crucial challenges for the world economy. Phenomena like climate change, digital transformation, migration, demographic changes, and the ongoing COVID pandemic need to be understood and promptly addressed. We argue that the agent-based approach in economics is well suited to tackle these topics, because of its capacity to integrate the "micro" and "macro" dimensions by modelling the network of interactions among heterogeneous economic agents and their aggregate outcomes. This paper explains why the agent-based methodology is needed to overcome the limitations of the neoclassical approach in economics, which has not been able to properly address those challenges. To do so, the paper retraces the main stages of the scientific evolution in a general historical and epistemological perspective, showing how the paradigm of reductionism, which led to extraordinary advances after the scientific revolution of the seventeenth century, is less effective when addressing the main challenges ahead. On the other hand, the sciences of chaos theory and complex systems can provide the economic discipline with more suitable instruments to face those challenges. Finally, the paper briefly presents the contributions of the special issue, which use applications of agent-based models to study the main problems of our times.

AbstractFor the last 30 years, the economy has been undergoing a massive digital transformation. Intangible digital assets, like software solutions, Web services, and more recently deep learning algorithms, artificial intelligence, and digital platforms, have been increasingly adopted thanks to the diffusion and advancements of information and communication technologies. Various observers argue that we could rapidly approach a technological singularity leading to explosive economic growth. The contribution of this paper is on the empirical and the modelling sides. On the empirical side, we present a cross-country empirical analysis assessing the correlation between the growth rate of both tangible and intangible investments and different measures of productivity growth. Results show a significant correlation between intangible investments and both labor and total factor productivity in the period after the 2008 financial crisis. Similarly, both measures of productivity growth are correlated with a combination of both tangible and intangible investments which include information and communication technologies and software and database. These results are used to inform the enrichment of the agent-based macro-model Eurace that we employ to assess the long-term impact on unemployment of digital investments. Computational experiments show the emergence of technological unemployment in the long run with a high pace of intangible digital investments.

Basel III is a recently-agreed regulatory standard for bank capital adequacy with focus on the macroprudential dimension of banking regulation, i.e., the system- wide implications of banks' lending and risk. An important Basel III provision is to reduce procyclicality of present banking regulation and promote countercyclical capital buffers for banks. The Eurace agent-based macroeconomic model and sim- ulator has been recently showed to be able to reproduce a credit-fueled boom-bust dynamics where excessive bank leverages, while benefitting in the short term, have destabilizing effects in the medium-long term. In this paper we employ the Eu- race model to test regulatory policies providing time varying capital requirements for banks, based on mechanisms that enforce banks to build up or release capital buffers, according to the overall conditions of the economy. As conditioning variables for these dynamic policies, both the unemployment rate and the aggregate credit growth have been considered. Results show that the dynamic regulation of capital requirements is generally more successful than fixed tight capital requirements in stabilizing the economy and improving the macroeconomic performance.