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Global Dynamics: Approaches from Complexity Science (Wiley Series in Computational and Quantitative Social Science)

Wilson, Alan (ed.)
WileyBlackwell: Hoboken, NJ, 2016
ISBN 9781118922286 (hb)

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Reviewed by Nicholas M. Gotts
Independent researcher

Cover of book I approached this book with keen anticipation, there is much work of considerable interest reported in it, and it is, on the whole, well-written. Yet I came away with a distinct feeling of disappointment, a sense that it had not lived up to the promise of the title. I will try to explain this, but will first give an overview of the book’s structure, and a summary of its contents.

Most of the contributors are from University College London (UCL), many of these, including the editor, from the Centre for Advanced Spatial Analysis (CASA). Alan Wilson, the editor, is also co-author of seven of the seventeen chapters. One would therefore expect to find a considerable degree of coordination and common perspective in the book, and this is indeed the case. Almost all the models discussed are equation-based, often requiring many numerical parameters, and many are essentially static, attempting to account for some dependent variable (such as trade or aid flows, piracy, or ethnic conflict) in terms of a set of independent variables; multilinear regression, and the resulting R2 statistic, are frequently used. Spatial themes are prominent. Agent-based models are conspicuously absent. I note that there is a companion volume, Approaches to Geo-Mathematical Modelling: New Tools for Complexity Science, also edited by Alan Wilson and published by Wiley, which is apparently more technical, and which I have not read.

The book consists of six parts, with between one and six chapters.

Part I, “Global Dynamics and the Tools of Complexity Science”, consists of a single chapter with the same title, of which Alan Wilson is the sole author. It begins as follows (p.3): The populations and economies of the 220 countries of the world make up a complex global system. The elements of this system are continually interacting through, for example, trade, migration, the deployment of military forces (mostly in the name of defence and security) and development aid. It is a major challenge to social science to seek to understand this global system and to show how this understanding can be used in policy development. In this book, we deploy the tools of complexity science – and in particular, mathematical and computer modelling – to explore various aspects of change and the associated policy and planning uses: in short, global dynamics.

Of course, no one book, or group of researchers, could be expected to meet this challenge alone, to offer a “detailed and convincing ‘model of the world’ in all its aspects”, to quote Wilson himself later in the chapter. But the book must surely be judged by the progress it makes toward this stated goal.

Part Two, “Trade and Economic Development”, consists of three chapters, of which the first (chapter 2) is a short historical review followed by a standard suggestion that a complex adaptive system perspective would be useful in economics. Chapters 3 and 4 present models focused on international trade (and inter-sector trade within countries in the case of chapter 4), although both are presented as multi-level, incorporating other aspects of the global system. Both models consist of systems of equations, requiring scores of numerical parameters; and although both are dynamic in the sense that quantities traded change from year to year, neither gives the impression of being able to generate endogenous changes of system regime, such as occurred in the financial crisis of 2007-8, and which are generally considered a key feature of complex systems.

Part Three, Migration, consists of two chapters, the first reviewing “key policy needs and research centres” related to migration from the point of view of countries of in-migration, the second describing statistical techniques that can be used to generate estimates of missing migration data within Europe.

Part Four, Security, includes six chapters, covering a proposed general analysis of conflict in terms of “a spatial measure of threat between two adversaries who are distributed over some area or geographic region”, and a range of specific issues: The London riots of 2011, the Naxal rebellion in India, piracy off the coast of north-east Africa, insurgency and counter-insurgency in Iraq following the American-led invasion, and mass media effects on ethnic conflict and governmental repression. This was the section where I felt the models presented gave rise to the most significant insights into the systems modelled – but these systems were all local, or at most national, in scale. In all cases, I felt that an agent-based approach could have produced insights that the mathematical and statistical models described did not, although this could of course be due to my own bias that if your model cannot produce the behaviour it purports to describe, that behaviour has not really been explained.

Part V, “Aid and Development”, consists of three chapters, all of which announce their intention to adopt a complex systems perspective, but only one of which includes a model with a significant dynamic element, exploring three scenarios of change in aid allocation – but including only three donors and three recipients.

Finally, Part VI, “Global Dynamics: An Integrated Model and Policy Challenges”, consists of a single chapter, “An Integrated Model”, by Robert G. Levy. It falls considerably short of the ambitious title of Part VI. The model described is the international economic and trade model of chapter 4, modified in minor ways by adding some possible effects of migration, aid, and military spending on national and international economics.

The disappointment I referred to earlier arises chiefly from the lack of any real attempt to describe global dynamics, the supposed subject of the book, or to make systematic connections with complexity science, as the subtitle promises. The global political-economic-military system is indeed highly dynamic, in ways which are scarcely even hinted at in the course of the book. It is also highly structured, with states, large corporations and international bodies competing and cooperating to maintain or change that structure; its dynamics depend on the interplay of structure and agency at multiple levels, in ways which theories of political science, international relations, and historical sociology (all absent from the book) attempt to describe. Moreover, it is rooted in the larger global social-environmental system which includes demographic change, increasing climate disruption, loss of biodiversity, soil erosion, depletion of aquifers, over-fishing and ocean pollution. Of this larger context, the book says nothing at all, with the sole exception of its limited treatment of migration. As far as complexity science is concerned, there are numerous references to it, but little attempt to show that the models presented show features such as path dependency, resilience, multiple basins of attraction, and adaptive behaviour – although there is some use of network analysis. One may in any case question whether complexity science as usually interpreted is sufficient to deal with global dynamics: it tends to focus on the emergence of system complexity from multiple local interactions, but this is only one aspect of modern global dynamics: multiple competing, strategising actors able to assess, criticise and attempt to change the global system are key to its operations – although none of these actors comprehend its workings as a whole.

It is worth noting that agent-based modelling cannot claim to have made significantly more progress in modelling global dynamics than the approach taken in this book. The most serious attempts to do so in fact come from the systems dynamics tradition exemplified by the Club of Rome’s Limits to Growth (1974) and similar models. Let us see what both equation-based and agent-based modelling, separately and in combination, can do to advance understanding of global dynamics in the full sense, as available computational power and “big data” continue to grow – and let all modellers strive to ensure that such models are used for the general good, not to advance the interests of selfish elites.


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