A major concern about the use of simulation models regards their relationship with the empirical data. The identification of a suitable indicator quantifying the distance between the model and the data would help and guide model selection and output validation. This paper proposes the use of a...

Simulated models suffer intrinsically from validation and comparison problems. The choice of a suitable indicator quantifying the distance between the model and the data is pivotal to model selection. However, how to validate and discriminate between alternative models is still an open problem...

Taking agent-based models (ABM) closer to the data is an open challenge. This paper explicitly tackles parameter space exploration and calibration of ABMs combining supervised machine-learning and intelligent sampling to build a surrogate meta-model. The proposed approach provides a fast and...

Since the influential survey by Windrum et al. (2007), research on empirical validation of agent-based models in economics has made substantial advances, thanks to a constant flow of high-quality contributions. This Chapter attempts to take stock of such recent literature to offer an updated...

The Great Recession seems to be a natural experiment for economic analysis, in that it has shown the inadequacy of the predominant theoretical framework - the New Neoclassical Synthesis (NNS) - grounded on the DSGE model. In this paper, we present a critical discussion of the theoretical,...

Wages are an element of cost crucially aecting the competitiveness of individual firms. But the wage bill is also a crucial element of aggregate demand. Hence it could be that more "flexible" and fluid labour markets, while allowing for faster inter-firm reallocation of labour, may also render...

We build an agent-based model to study how the interplay between low- and high- frequency trading affects asset price dynamics. Our main goal is to investigate whether high-frequency trading exacerbates market volatility and generates flash crashes. In the model, low-frequency agents adopt...

We investigate the effects of different regulatory policies directed towards high-frequency trading (HFT) through an agent-based model of a limit order book able to generate flash crashes as the result of the interactions between low- and high-frequency (HF) traders. We analyze the impact of the...

We build an agent-based model populated by households with heterogenous and time-varying financial conditions in order to study how fiscal multipliers can change over the business cycle and are affected by the state of credit markets. We find that deficit-spending fiscal policy dampens the...

The role of the patent system in the pharmaceutical sector is highly debated also due to its strong public health implications. In this paper we develop an evolutionary, agent-based model of the pharmaceutical industry to explore the impact of different configurations of the patent system upon...