Agent-based Computational Economics: a Methodological Appraisal

This paper is an overview of "Agent-based Computational Economics (ACE)", an emerging approach to the study of decentralized market economies, in methodological perspective. It summarizes similarities and differences with respect to conventional economic models, outlines the unique methodological characteristics of this approach, and discusses its implications for economic methodology as a whole. While ACE rejoins the reflection on the unintended social consequences of purposeful individual action which is constitutive of economics as a discipline, the paper shows that it complements state-of the-art research in experimental and behavioral economics. In particular, the methods and techniques of ACE have reinforced the laboratory finding that fundamental economic results rely less on rational choice theory than is usually assumed, and have provided insight into the importance of market structures and rules in addition to individual choice. In addition, ACE has enlarged the range of inter-individual interactions that are of interest for economists. In this perspective, ACE provides the economist‘s toolbox with valuable supplements to existing economic techniques rather than proposing a radical alternative. Despite some open methodological questions, it has potential for better integration into economics in the future.Agent-based Computational Economics, Economic Methodology, Experimental Economics.

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

The Cost of Rational Agency

The rational agency assumption limits systems to domains of application that have never been observed. Moreover, representing agents as being rational in the sense of maximising utility subject to some well specified constraints renders software systems virtually unscalable. These properties of the rational agency assumption are shown to be unnecessary in representations or analogies of markets. The demonstration starts with an analysis of how the rational agency assumption limits the applicability and scalability of the IBM information filetering economy. An unrestricted specification of the information filtering economy is developed from an analysis of the properties of markets as systems and the implementation of a model based on intelligent agents. This extended information filtering economy modelis used to test the analytical results on the scope for agents to act as intermediaries between human users and information sources

An evolutionary theory of systemic risk and its mitigation for the global financial system

This thesis is the outcome of theory development research into an identified gap in knowledge about systemic risk of the global financial system. It takes a systems-theoretic approach, incorporating a simulation-constructivist orientation towards the meaning of theory and theory development, within a realist constructivism epistemology for knowledge generation about complex social phenomena. The specific purpose of which is to describe systemic risk of failure, and explain how it occurs in the global financial system, in order to diagnose and understand circumstances in which it arises, and offer insights into how that risk may be mitigated. An outline theory is developed, introducing a new operational definition of systemic risk of failure in which notions from evolutionary economics, finance and complexity science are combined with a general interpretation of entropy, to explain how catastrophic phenomena arise in that system. When a conceptual model incorporating the Icelandic financial system failure over the years 2003 – 2008 is constructed from this theory, and the results of simulation experiments using a verified computational representation of the model are validated with empirical data from that event, and corroborated by theoretical triangulation, a null-hypothesis about the theory is refuted. Furthermore, results show that interplay between a lack of diversity in system participation strategies and shared exposure to potential losses may be a key operational mechanism of catastrophic tensions arising in the supply and demand of financial services. These findings suggest new policy guidance for pre-emptive intervention calls for improved operational transparency from system participants, and prompt access to data about their operational behaviour, in order to prevent positive feedback inducing a failure of the system to operate within required parameters. The theory is then revised to reflect new insights exposed by simulation, and finally submitted as a new theory capable of unifying existing knowledge in this problem domain

Open Problems in DAOs

Decentralized autonomous organizations (DAOs) are a new, rapidly-growing class of organizations governed by smart contracts. Here we describe how researchers can contribute to the emerging science of DAOs and other digitally-constituted organizations. From granular privacy primitives to mechanism designs to model laws, we identify high-impact problems in the DAO ecosystem where existing gaps might be tackled through a new data set or by applying tools and ideas from existing research fields such as political science, computer science, economics, law, and organizational science. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the wider research community to join the global effort to invent the next generation of organizations