Suchergebnisse

Research on loss absorption of financial group (bank network) -- The Mathematics of Human Contact -- Does it still matter in the new world where a refugee comes from? - Social network, Shocks, and Ethnicity - A multi-level analysis -- The Transferability of Human Capital, the Brain Drain, and the Brain Gain -- Evolution in Anonymous Population Games with Multiple Types -- Analysis of search actions on the Internet including the effect of blog and Twitter using Sociophysics approach -- Statistical analysis of a political demonstration using location-based big data -- Different Type of Interaction Plays a Role of Decision Error on Collective Behavior -- A financial network approach to unconventional monetary policy assessment - the case of Quantitative Easing in the euro area -- From Housing Locale Theory to Agent-Based Modeling Approach

Agent-based models (ABMs) provide a methodology to explore systems of interacting, adaptive, diverse, spatially situated actors. Outcomes in ABMs can be equilibrium points, equilibrium distributions, cycles, randomness, or complex patterns; these outcomes are not directly determined by assumptions but instead emerge from the interactions of actors in the model. These behaviors may range from rational and payoff-maximizing strategies to rules that mimic heuristics identified by cognitive science. Agent-based techniques can be applied in isolation to create high-fidelity models and to explore new questions using simple constructions. They can also be used as a complement to deductive techniques. Overall, ABMs offer the potential to advance social sciences and to help us better understand our complex world.

Agent-based models (ABMs) provide a methodology to explore systems of interacting, adaptive, diverse, spatially situated actors. Outcomes in ABMs can be equilibrium points, equilibrium distributions, cycles, randomness, or complex patterns; these outcomes are not directly determined by assumptions but instead emerge from the interactions of actors in the model. These behaviors may range from rational and payoff-maximizing strategies to rules that mimic heuristics identified by cognitive science. Agent-based techniques can be applied in isolation to create high-fidelity models and to explore new questions using simple constructions. They can also be used as a complement to deductive techniques. Overall, ABMs offer the potential to advance social sciences and to help us better understand our complex world. Adapted from the source document.

The aim of this paper is to build a computational model that presents the effects of social dynamics such as evolution on populations applying the theory of Hobbesian Social Contract, social learning and norm diffusion. The phenomenon we are studying is the so-called tragedy of the commons, in which individual agents, having open access to a resource unconstrained by common social structures, act according to their own self-interest, seeking to maximise their own profits. Developing the theoretical framework and agent-based model, we applied to our artificial environment the norm associated with altruism, which modifies agents' behaviour during the simulation, which in turn affects the distribution of wealth. Through the behavioural space, we show that under certain circumstances specified in the parameter, it is possible to obtain a social contract and, as a result, a state of equilibrium. We show that individuals who have obtained the norm are able to enter into a contract, resulting in a rising wealth of the population and a more equilibrium distribution, while if they do not, more inequalities emerge. However, our model is a simplification of Hobbes' theory, admittedly, our agents can spontaneously establish cooperation but there are no complex structures, such as psychological ones, or moral cognition. We believe that this is a skeletal description of the Hobbesian social contract, in which self-interested individuals without obligation to cooperate agree to abide by a norm and its benefits. Depending on how profitable cooperation is (due to the redistribution) and the number of altruistic agents, the community members work for the common good.

Doutoramento em Economia ; A crise financeira de 2007/2008 desencadeou uma onda de críticas à teoria económica. Ataques baseados em quatro críticas principais: os economistas não terem previsto a maior crise desde a Grande Depressão; as autoridades deixarem formar bolhas sem controlo; o falhanço da supervisão bancária; e os modelos usados serem desfasados da realidade. No caso dos modelos, o alvo principal são os modelos DSGE (dinâmicos, estocásticos e de equilíbrio geral) e duas das suas hipóteses simplificadoras: o agente representativo e a racionalidade. As economias são realidades complexas, não-lineares e heterogéneas, e o recurso a métodos computacionais pode ser uma alternativa para ultrapassar as limitações dos modelos tradicionais. O objectivo desta tese é alargar a aplicação dos modelos de agentes em Macroeconomia com três exemplos distintos. O primeiro é um modelo de crescimento endógeno, de gerações sobrepostas, em que a decisão dos agentes sobre estudar é baseada na satisfação e na influência dos seus pares. É usado para testar os efeitos de longo prazo do paradoxo de Easterlin, que sugere que a satisfação e o rendimento não têm uma relação linear. Verifica-se que, no cenário de Easterlin, o crescimento é menor do que no cenário base onde os agentes atribuem igual importância ao rendimento absoluto e relativo. O segundo modelo visa avaliar o contágio dos defaults da dívida pública e a forma como as estratégias dos governos afetam o seu aparecimento e propagação. As simulações mostram que os países mais gastadores e com menor aversão ao risco tendem a entrar mais vezes em default e que políticas monetárias muito expansionistas podem originar fenómenos de risco moral. No terceiro modelo, estudamos o fenómeno da 'fuga de cérebros' e as consequências no crescimento económico. Concluímos que o efeito positivo do brain drain na acumulação de capital humano depende fortemente da probabilidade de emigrar. ; The 2007/2008 financial crisis triggered a wave of criticism of the economic theory. These attacks are based in four main critics: economists had not foreseen the biggest crisis since the Great Depression; authorities let bubbles form without control; weak banking supervision; and the models used in macroeconomic policy being out of touch with reality. In the particular case of the macroeconomic models, the target are the DSGE models (dynamic, stochastic and general equilibrium) and their two simplifying hypotheses: the representative agent and rationality. Economies are complex realities, with nonlinearities and heterogeneities, and computational economics can be an advantageous alternative to overcome the shortcomings of the traditional models. The aim of this thesis is to extend the application of agent-based models to macroeconomic topics in three distinct models. The first one is an endogenous growth model, in an overlapping generations environment, in which the agents' individual decision to study is based on the satisfaction of their peers. It is used to evaluate the long-term effects of the Easterlin paradox, which states that satisfaction and income have a non-linear relation. The second model is used to study sovereign default contagion in order to assess how different government strategies affect default and propagation across countries. Simulations showed that high spending and low risk aversion levels are associated to a high prevalence of default and that monetary stimulus can create moral hazard problems. In the third model, we study the brain drain phenomenon and its economic growth effects. We conclude that beneficial brain hypothesis depend heavily on emigration probability. ; info:eu-repo/semantics/publishedVersion

Agent-based computational economics (ACE) is the computational study of economic processes modeled as dynamic systems of interacting agents. Here agentrefers broadly to a bundle of data and behavioral methods representing an entity constituting part of a computationally constructed world. Examples of possible agents include individuals (e.g. consumers, producers), social groupings (e.g. families, firms, communities, government agencies), institutions (e.g. markets, regulatory systems), biological entities (e.g. crops, livestock, forests), and physical entities (e.g. infrastructure, weather, and geographical regions). Thus, agents can range from active data-gathering decision makers with sophisticated embodied cognitive capabilities to passive world features with no cognitive function.

Aims to give a view of the scientific production in the fields of Agent-based Computational Economics, mainly in Market Finance and Game Theory. Based on communications given at AE'2005 (Lille, USTL, France), this book offers a panorama of advances in ACE, both theoretical and methodological that is of interest academics as well as practitioners

Agent-based models have played a prominent role in recent debates about the merits of democracy. In particular, the formal model of Lu Hong and Scott Page and the associated "diversity trumps ability" result has typically been seen to support the epistemic virtues of democracy over epistocracy (i.e., governance by experts). In this paper we first identify the modeling choices embodied in the original formal model and then critique the application of the Hong-Page results to philosophical debates on the relative merits of democracy. In particular we argue that the "best-performing agents" in the Hong-Page model should not be interpreted as experts. We next explore a closely related model in which best-performing agents are more plausibly seen as experts and show that the diversity trumps ability result fails to hold. However, with changes in other parameters (such as the deliberation dynamic) the diversity trumps ability result is restored. The sensitivity of this result to parameter choices illustrates the complexity of the link between formal modeling and more general philosophical claims; we use this debate as a platform for a more general discussion of when and how agent-based models can contribute to philosophical discussions.