Agent-Based Modelling in Population Studies
In: Canadian Studies in Population
Edited by André Grow and Jan Van BavelSpringer International Publishing 2017 ISBN: 978-3-319-32281-0Hardcover, $159.99 US, eBook, $119 US, 513 pp.
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In: Canadian Studies in Population
Edited by André Grow and Jan Van BavelSpringer International Publishing 2017 ISBN: 978-3-319-32281-0Hardcover, $159.99 US, eBook, $119 US, 513 pp.
In: Perspectives on politics: a political science public sphere, Band 10, Heft 4, S. 1026-1028
ISSN: 1537-5927
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.
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This paper is about the theoretical implications of agent-based modeling exercises. Construction of an agent-based model challenges a social scientist to formalize many concepts and relationships that would have remained implicit or unrecognized. While formalizing these "unimportant" assumptions can be a nuisance, it can also have substantial theoretical payoffs. In order to fill the gaps of the model, the researcher is forced to confront the gaps in the theory that motivated the model in the first place. Using examples drawn from several large political science simulation models, the paper argues that frailty, defined as unpredictability in the behavior of agents, is often required in order to bring closure to the modeling exercise. It is difficult (or impossible) to square the dynamic or aggregate implications of the agent-based model with observations without placing a substantial amount of emphasis on frailty. Hence, the component in behavior that we often treat as "error" in empirical analysis is actually a vital part of the glue that makes the many different moving parts of a social system interact in coherent ways. The example models were developed with the Swarm simulation system (http://www.swarm.org) during the last decade.
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This is the publisher's version, also available electronically from https://sites.google.com/a/fspub.unibuc.ro/european-quarterly-of-political-attitudes-and-mentalities/Home ; This paper is about the theoretical implications of agent-based modeling exercises. Construction of an agent-based model challenges a social scientist to formalize many concepts and relationships that would have remained implicit or unrecognized. While formalizing these "unimportant" assumptions can be a nuisance, it can also have substantial theoretical payoffs. In order to fill the gaps of the model, the researcher is forced to confront the gaps in the theory that motivated the model in the first place. Using examples drawn from several large political science simulation models, the paper argues that frailty, defined as unpredictability in the behavior of agents, is often required in order to bring closure to the modeling exercise. It is difficult (or impossible) to square the dynamic or aggregate implications of the agent-based model with observations without placing a substantial amount of emphasis on frailty. Hence, the component in behavior that we often treat as "error" in empirical analysis is actually a vital part of the glue that makes the many different moving parts of a social system interact in coherent ways. The example models were developed with the Swarm simulation system (http://www.swarm.org) during the last decade.
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SSRN
In: Journal of economic dynamics & control, Band 131, S. 104231
ISSN: 0165-1889
An organization is a collection of agents that interact and produce some form of output. Formal organizations - such as corporations and governments - are typically constructed for an explicit purpose though this purpose needn't be shared by all organizational members. An entrepreneur who creates a firm may do so in order to generate personal wealth but the worker she hires may have very different goals. As opposed to more amorphous collections of agents such as friendship networks and societies at large, organizations have a formal structure to them (though informal structures typically emerge as well) with the prototypical example being a corporation's organizational chart. This structure serves to define lines of communication and the distribution of decision-making. Organizations are also distinguished by their well-defined boundaries as reflected in a clear delineation as to who is and who is not a member. This boundary serves to make organizations a natural unit of selection; for example, corporations are formed and liquidated though they can also morph into something different through activities like mergers.
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In: Small wars & insurgencies, Band 24, Heft 2, S. 306-321
ISSN: 0959-2318
World Affairs Online
In: JCIT-D-22-00396
SSRN
This article uses computer simulations as a means of assessing two different models for the competition between two languages from the interdisciplinary perspective of complex systems. These models allow for the analysis of the role of bilingual speakers and they consider two of the basic factors determining the use of each language: their relative prestige and the language loyalty of their speakers. Here we assess the effect of these parameters in different social networks, with the aim of contributing to the understanding of the role of bilingualism and social networks in processes of language contact. We first present a qualitative analysis based on a simulation tool that we have designed, in order to visualize the dynamics of the models. Secondly, we consider a qualitative analysis of the role of complex networks, identifying mechanisms for the rapid extinction of a language and for situations of language segregation. Finally, we present a quantitative analysis which shows, counter-intuitively, a transition from a final scenario of language maintenance to one of language shift as language loyalty increases. Other findings are: (i) that the scenario of language coexistence is reduced in the presence of bilingual agents; and (ii) that networks which allow for local effects reduce further the situations for which language maintenance is possible. ; In addition, for generous financial support, Xavier Castelló and Maxi San Miguel thank the Spanish Ministry for Science and Innovation and the European Regional Development Fund (grant FIS2007-60327, FISICOS), and Lucía Loureiro-Porto thanks the Autonomous Government of Galicia (INCITE grant 08PXIB204016PR) and the Spanish Ministry for Science and Innovation and the European Regional Development Fund (grants HUM2007–60706 and FFI2011-26693-C02-02). ; Peer reviewed
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In: Synthese: an international journal for epistemology, methodology and philosophy of science, Band 165, Heft 2, S. 159-177
ISSN: 1573-0964
SSRN
Working paper
In: Agent-based social systems, v. 9
Decision makers in large scale interconnected network systems require simulation models for decision support. The behaviour of these systems is determined by many actors, situated in a dynamic, multi-actor, multi-objective and multi-level environment. How can such systems be modelled and how can the socio-technical complexity be captured? Agent-based modelling is a proven approach to handle this challenge. This book provides a practical introduction to agent-based modelling of socio-technical systems, based on a methodology that has been developed at Delft University of Technology and which has been deployed in a large number of case studies. The book consists of two parts: the first presents the background, theory and methodology as well as practical guidelines and procedures for building models. In the second part this theory is applied to a number of case studies, where for each model the development steps are presented extensively, preparing the reader for creating own models.