Social Psychology and the Narrative Economy

Self Cite

Between 2011 and 2014 the European Non-Equilibrium Social Science Project (NESS) investigated the place of equilibrium in the social sciences and policy. Orthodox economics is based on an equilibrium view of how the economy functions and does not offer a complete description of how the world operates. However, mainstream economics is not an empty box. Its fundamental insight, that people respond to incentives, may be the only universal law of behaviour in the social sciences. Only economics has used equilibrium as a primary driver of system behaviour, but economics has become much more empirical at the microlevel over the past two decades. This is due to two factors: advances in statistical theory enabling better estimates of policy consequences at the microlevel, and the rise of behavioural economics which looks at how people, firms and governments really do behave in practice. In this context, this chapter briefly reviews the contributions of this book across the social sciences and ends with a discussion of the research themes that act as a roadmap for further research. These include: realistic models of agent behaviour; multilevel systems; policy informatics; narratives and decision making under uncertainty; and validation of agent-based complex systems models.

Section: Social Psychology and The Narrative Economymentioning

confidence: 99%

Non-Equilibrium Social Science and Policy

Johnson

Ormerod

Rosewell

et al. 2017

Self Cite

“…Actors in financial markets are driven by narratives and by collective behaviour (e.g. herding behaviour as the origin of financial crashes) [31]. The behaviour of actors in financial systems is influenced as much by networks as it is with them acting as individuals trying to make rational decisions [33].…”

Section: Financementioning

confidence: 99%

“…. the power to edit and control narratives is an important source of control in social processes' [31].…”

Section: Narratives In Global Systems Science and Policymentioning

confidence: 99%

“…Traditional science often assumes that it studies objective phenomena, but social reality is constructed in interactions between individuals, and these social interactions are necessary to sustain the social reality. Social constructs are the results of human decisions rather than objective reality, and narratives are a way to navigate and construct reality [2,31]. Human behaviour is reflexive and people can respond to predictions by making them self-fulfilling prophesies or deliberately falsifying them, e.g.…”

Section: Visualisation and Visual Analyticsmentioning

confidence: 99%

See 1 more Smart Citation

Global Systems Science and Policy

Dum

Johnson

2017

The vision of Global Systems Science (GSS) is to provide scientific evidence and means to engage into a reflective dialogue to support policy-making and public action and to enable civil society to collectively engage in societal action in response to global challenges like climate change, urbanisation, or social inclusion. GSS has four elements: policy and its implementation, the science of complex systems, policy informatics, and citizen engagement. It aims to give policy makers and citizens a better understanding of the possible behaviours of complex social systems. Policy informatics helps generate and evaluate policy options with computer-based tools and the abundance of data available today. The results they generate are made accessible to everybody-policy makers, citizens-through intuitive user interfaces, animations, visual analytics, gaming, social media, and so on. Examples of Global Systems include epidemics, finance, cities, the Internet, trade systems and more. GSS addresses the question of policies having desirable outcomes, not necessarily optimal outcomes. The underpinning idea of GSS is not to precisely predict but to establish possible and desirable futures and their likelihood. Solving policy problems is a process, often needing the requirements, constraints, and lines of action to be revisited and modified, until the problem is 'satisficed', i.e. an acceptable compromise is found between competing objectives and constraints. Thus policy problems and their solutions coevolve much as in a design process. Policy and societal action is as much about attempts to understand objective facts as it is about the narratives that guide our actions. GSS tries to reconcile these apparently contradictory modes of operations. GSS thus provides policy makers and society guidance on their course of action rather than proposing (illusionary) optimal solutions.

“…Economics needs to work with other disciplines, especially psychology, in order to understand how agents are able to make decisions under conditions of model uncertainty see, for example, [13]. In essence, agents are motivated by a mixture of excitement and anxiety, excitement about potential gain and anxiety about potential loss.…”

Section: Sentiment Narratives and Uncertaintymentioning

confidence: 99%

Economics

Ormerod¹

2017

Economics is by no means an empty box. For example, it offers what is possibly the only general law of behaviour in the social sciences, namely that agents react to incentives. Over the past two decades or so, at the micro level, the level of individual agent decision making, the discipline has made progress. Developments in the econometric theory of the analysis of large longitudinal data bases and the rise of behavioural and experimental economics have made the discipline much more empirical. However, at the macro level, economics has, if anything, gone backwards. The main intellectual effort since the 1980s has been to import the concept of equilibrium into macroeconomics. It is no surprise that policymakers during the financial crisis of the late 2000s found the mainstream economic models to be of little or no help at all. In the 1950s, there was an active debate about the computational limits which agents faced when making decisions. The polymath Nobel Laureate Herbert Simon was prominent in arguing that the rational model of choice, the core model of economic theory, was not realistic in many situations because of these limits. Even after the event, it may not be possible to determine what the optimal decision would have been at any given time. The world is in general too complex. Mainstream economics gradually lost sight of this fundamental challenge to one of its key assumptions. The rise of cyber society and Big Data mean that Simon's challenge is more relevant than ever. Looking to the future, new models of 'rational' agent behaviour are required which are better suited to the cyber society of the twenty-first century. Key areas of research include: agent decision making rules; heuristics to identify decision types in any given context; network percolation of imitation, incentives, ideas, beliefs, influence and sentiments; networks evolution; the policy implications of different modes of behaviour; fundamental theory and tools to operationalise narrative dynamics; computational theories of narratives, including Big Data; tools for processing narratives and sentiment; and predicting the emergence of narratives. P. Ormerod ( )