Economics

Abstract

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 ( )

Systems, Networks, and Policy

“…As Ormerod's chapter in this book makes clear, when it comes to making choices, copying is a much more convincing explanation for the decisions made than rational choice with perfect information [29]. This insight is of great potential value to policy makers because it gives new network-based methods of understanding the possible outcome of policy, and can help to shape policy.…”

“…In practice these two subsystems tend to oscillate as 'market sentiment' transforms the belief that prices will increase to the belief that prices will fall, and vice versa. The dynamics of these changes are partly due to the narratives circulating as the system evolves, as discussed in the chapters by Ormerod and Nowak in this volume [27,29]. …”

Non-Equilibrium Social Science and Policy

“…Ormerod's chapter [11] addresses the question of whether the commanding position of orthodox economics in the policy making process is justified by its scientific achievements. Despite the failure of its macro-level Dynamic Stochastic General Equilibrium models to provide useful guidance following the financial crash of 2008, at the microlevel economics provides the general law that individuals react to changes in incentives.…”

“…Economics has become much more empirical at the microlevel over the course of the past two decades. In his chapter Ormerod argues that this is due to two factors [11]. First, substantial advances in statistical theory, which enables better estimates of the effects of policy changes at the microlevel.…”

Global Systems Science and Policy

“…They are neither perfectly informed (as acknowledged now by economic theories of limited information) nor do they act 'rationally' in the strict sense of the word [32]. Actors in financial markets are driven by narratives and by collective behaviour (e.g.…”