Advances in Complex Systems

We consider a market economy where two rational agents are able to learn the distribution of future events. In this context, we study whether moving away from the standard Bayesian belief updating, in the sense of under-reaction to some degree to new information, may be strategically convenient for traders. We show that, in equilibrium, strong under-reaction occurs, thus rational agents may strategically want to bias their learning process. Our analysis points out that the underlying mechanism driving ex-ante strategical decisions is diversity seeking. Finally, we show that, even if robust with respect to strategy selection, strong under-reaction can generate low realized welfare levels because of a long transient phase in which the agent makes poor predictions.

In a globalized world, the distribution of value-added across firms depends on a number of factors that vary across space. A key factor is related to the different types of competition on the multilayer structure of production, which are characterized by different types of (market) power. In this paper, we first argue that PageRank centrality is able to capture sectoral market power within the complex structure of global production. We then study the empirical properties of this market power measure and demonstrate a power-law relationship between sectoral PageRank centrality and relative sectoral profits. This power-law relationship has (international) political economy implications as it demonstrates the high incentives of sectors to become more central to increase their relative profits.

We use a data-driven agent-based model to study the core–periphery structure of two collaboration networks, R&D alliances between firms and co-authorship relations between scientists. To characterize the network embeddedness of agents, we introduce a coreness value obtained from a weighted $k$-core decomposition. We study the change of these coreness values when collaborations with newcomers or established agents are formed. Our agent-based model is able to reproduce the empirical coreness differences of collaboration partners and to explain why we observe a change in partner selection for agents with high network embeddedness.

This paper proposes a macroeconometric analysis to depict and measure possible financial cycles that emerge due to the dynamic interaction between heterogeneous market participants. We consider two-type heterogeneous speculative agents: Trend followers tend to follow the price trend while contrarians go against the wind. As agents’ beliefs are unobserved variables, we construct a state-space model where heuristics are considered as unobserved state components and from which the conditions for endogenous cycles can be mathematically derived and empirically tested. Further, we specifically measure the length of endogenous financial cycles. The model is estimated using the equity price index for the 1960–2020 period for the UK, France, Germany, Italy, Ireland, and the USA. We find empirical evidence of endogenous financial cycles for all countries, with the highest frequencies in the USA and the UK.

This paper examines the impact of countercyclical capital buffers (CCyBs) on financial stability and contributes to the discussion of CCyBs in an agent-based framework. The main focus of this work lies upon the question whether the implementation of CCyBs according to the Basel III framework improves financial stability unconditionally, or at the expense of unintended side effects. For this purpose, we extend the agent-based model of [Riccetti, L., Russo, A. and Gallegati, M., Firm–bank credit network, business cycle and macroprudential policy, J. Econ. Interact. Coord. (2021)] to investigate the effect of credit-to-GDP gap-based CCyBs in general as well as the effects of varying the smoothing parameter lambda $\lambda$ of the Hodrick–Prescott (HP) filter within the method of calculating CCyBs. To the best of our knowledge, this study is the first one that investigates systematically how the method of calculating credit-to-GDP gap-based CCyBs may affect macrofinancial dynamics and stability in such an agent-based framework.