We study a stochastic model of anonymous influence with conformist and anti-conformist individuals. Each agent with a ‘yes’ or ‘no’ initial opinion on a certain issue can change his opinion due to social influence. We consider anonymous influence, which depends on the number of agents having a certain opinion, but not on their identity. An individual is conformist/anti-conformist if his probability of saying ‘yes’ increases/decreases with the number of ‘yes’-agents. We focus on three classes of aggregation rules (pure conformism, pure anti-conformism, and mixed aggregation rules) and examine two types of society (without, and with mixed agents). For both types we provide a complete qualitative analysis of convergence, i.e., identify all absorbing classes and conditions for their occurrence. Also the pure case with infinitely many individuals is studied. We show that, as expected, the presence of anti-conformists in a society brings polarization and instability: polarization in two groups, fuzzy polarization (i.e., with blurred frontiers), cycles, periodic classes, as well as more or less chaotic situations where at any time step the set of ‘yes’-agents can be any subset of the society. Surprisingly, the presence of anti-conformists may also lead to opinion reversal: a majority group of conformists with a stable opinion can evolve by a cascade phenomenon towards the opposite opinion, and remains in this state.
We study a model where agents face a continuum of two-player games and categorize them into a finite number of situations to make sense of their complex environment. Agents need not share the same categorization. Each agent can cooperate or defect, conditional on the perceived category. The games are fully ordered by the strength of the temptation to defect and break joint cooperation. In equilibrium agents share the same categorization, but achieve less cooperation than if they could perfectly discriminate games. All the equilibria are evolutionarily stable, but stochastic stability selects against cooperation. We model agents’ learning when they imitate successful players over similar games, but lack any information about the opponents’ categorizations. We show that imitation conditional on reaching an intermediate aspiration level leads to a shared categorization that achieves higher cooperation than under perfect discrimination.
2018 / Dawid, H., P. Harting and M. Neugart
Cohesion Policy and Inequality Dynamics: Insights from a Heterogeneous Agents Macroeconomic Model
Journal of Economic Behavior and Organization, 150, 220-255
Regions within the European Union differ substantially not only with respect to per capita GDP, but also with respect to income inequality within the regions. This paper studies the effects of different types of technology-oriented cohesion policies, aiming at the reduction of regional differences, on the convergence of regions and the dynamics of income inequality within regions. In particular, policies are analyzed using a two-region agent-based macroeconomic model – the Eurace@Unibi model – where firms in the lagging region receive subsidies for investment in physical capital. It is demonstrated that the short-, medium- and long-term effects of the policies on per-capita output and between- as well as within-regional inequality differ substantially. Effects depend on how successful the policy is in incentivizing firms to choose best available capital vintages and on how flexible labor markets are in the targeted region.
2018 / Quax R., G. Chliamovitch, A. Dupuis, J.-L. Falcone , B. Chopard, A.G. Hoekstra and P. M. A. Sloot
Information processing features can detect behavioral regimes of dynamical systems
In dynamical systems, local interactions between dynamical units generate correlations which are stored and transmitted throughout the system, generating the macroscopic behavior. However a framework to quantify exactly how these correlations are stored, transmitted, and combined at the microscopic scale is missing. Here we propose to characterize the notion of “information processing” based on all possible Shannon mutual information quantities between a future state and all possible sets of initial states. We apply it to the 256 elementary cellular automata (ECA), which are the simplest possible dynamical systems exhibiting behaviors ranging from simple to complex. Our main finding is that only a few information features are needed for full predictability of the systemic behavior and that the “information synergy” feature is always most predictive. Finally we apply the idea to foreign exchange (FX) and interest-rate swap (IRS) time-series data. We find an effective “slowing down” leading indicator in all three markets for the 2008 financial crisis when applied to the information features, as opposed to using the data itself directly. Our work suggests that the proposed characterization of the local information processing of units may be a promising direction for predicting emergent systemic behaviors.
2018 / Halleck-Vega, S., A. Mandel and K. Millock
Accelerating diffusion of climate-friendly technologies: A network perspective
We introduce a methodology to estimate the determinants of the formation of technology diffusion networks from the patterns of technology adoption. We apply this methodology to wind energy, which is one of the key technologies in climate change mitigation. Our results emphasize that, in particular, long-term relationships as measured by economic integration are key determinants of technological diffusion. Specific support measures are less relevant, at least to explain the extensive margin of diffusion. Our results also highlight that the scope of technological diffusion is much broader than what is suggested by the consideration of CDM projects alone, which are particularly focused on China and India. Finally, the network of technological diffusion inferred from our approach highlights the central role of European countries in the diffusion process and the absence of large hubs among developing countries.
2018 / Conti C., M.L. Mancusi, R. Sestini, F. Sanna Randaccio and E. Verdolini
Transition Towards a Green Economy in Europe: Innovation and Knowledge Integration in the Renewable Energy Sector
This paper investigates the fragmentation of the EU innovation system in the field of renewable energy sources (RES) by estimating the intensity and direction of knowledge spillovers over the years 1985–2010. We modify the original double exponential knowledge diffusion model proposed by Caballero and Jaffe (1993) to provide information on the degree of integration of EU countries’ RES knowledge bases and to assess how citation patterns changed over time. We show that EU RES inventors have increasingly built “on the shoulders of the other EU giants”, intensifying their citations to other member countries and decreasing those to domestic inventors. Furthermore, the EU strengthened its position as source of RES knowledge for the US. Finally, we show that this pattern is peculiar to RES, with other traditional (i.e. fossil-based) energy technologies and other radically new technologies behaving differently. Our results provide suggestive, but convincing evidence that the reduction in fragmentation emerged as a result of the EU support for RES taking mainly the form of demand-pull policies.
2018 / Moro, A. and P. Pellizzari
A computational model of labor market participation with health shocks and bounded rationality
This paper presents a computational agent-based model of labor market participation, in which a population of agents, affected by adverse health shocks that impact the costs associated with working efforts, decides whether to leave the labor market and retire. This decision is simply taken by looking at the working behaviors of the other agents, comparing the respective levels of well-being and imitating the more advantageous decision of others. The analysis reveals that such mechanism of social learning and imitation suffices to replicate the existing empirical evidence regarding the decline in labor market participation of older people. As a consequence, the paper demonstrates that it is not necessary to assume perfect and unrealistic rationality at the individual level to reproduce a rational behavior in the aggregate.
2018 / Dawid, H. and D. Delli Gatti
in C. Hommes and B. LeBaron (Eds.) "Handbook of Computational Economics Vol. 4: Heterogeneous Agent Modeling", North-Holland, pp. 63-156
This chapter surveys work dedicated to macroeconomic analysis using an agent- based modeling approach. After a short review of the origins and general characteristics of this approach a systemic comparison of the structure and modeling assumptions of a set of important (families of) agent-based macroeconomic models is provided. The comparison highlights substantial similarities between the different models, thereby identifying what could be considered an emerging common core of macroeconomic agent-based modeling. In the second part of the chapter agent-based macroeconomic research in different domains of economic policy is reviewed.
2018 / Assenza, T., P. Colzani, D. Delli Gatti and J Grazzini
Does fiscal policy matter? Tax, transfer, and spend in a macro ABM with capital and credit
Industrial and Corporate Change, 27 (6), 1069–1090
We investigate, compare, and contrast the emerging properties of a macroeconomic agent-based model along the lines of Assenza et al., (2015, Journal of Economic Dynamics and Control, 50, 5–28) when the government experiments with different policy configurations: (i) tax and transfer; (ii) tax, transfer, and spend; and (iii) the implementation of a fiscal rule, such as a stylized Stability and Growth Pact. In some of the scenarios considered, a remarkable property can be detected, which we label the balanced budget emerging property: The scale of activity in the aggregate (GDP, employment, and unemployment rate) is such that a balanced budget emerges spontaneously. The strong implication of this property is that the fiscal authority is able to target GDP and the unemployment rate, a result reminiscent of the Blinder–Solow framework. It is worth noting, however, that there are many departures from the rule, which we have detected by carrying out the sensitivity analysis.
2018 / van Beest, F.M. S. Mews, S. Elkenkamp, P. Schuhmann, D. Tsolak, T. Wobbe, V. Bartolino, F. Bastardie, R. Dietz, C. von Dorrien, A. Galatius, O. Karlsson, B. McConnell, J. Nabe-Nielsen, M.T. Olsen, J. Teilmann and R. Langrock
Classifying grey seal behaviour in relation to environmental variability and commercial fishing activity-a multivariate hidden Markov model
Classifying movement behaviour of marine predators in relation to anthropogenic activity and environmental conditions is important to guide marine conservation. We studied the relationship between grey seal (Halichoerus grypus) behaviour and environmental variability in the southwestern Baltic Sea where seal-fishery conflicts are increasing. We used multiple environmental covariates and proximity to active fishing nets within a multivariate hidden Markov model (HMM) to quantify changes in movement behaviour of grey seals while at sea. Dive depth, dive duration, surface duration, horizontal displacement, and turning angle were used to identify travelling, resting and foraging states. The likelihood of seals foraging increased in deeper, colder, more saline waters, which are sites with increased primary productivity and possibly prey densities. Proximity to active fishing net also had a pronounced effect on state …
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