The Human Network

I’ve been thinking about social capital recently, so was eager to read Matthew Jackson’s The Human Network: How We’re Connected and Why it Matters. This is the version of his terrific work on networks and social capital (for example Social and Economic Networks (2010)) aimed at a general readership. Although the book starts with some of the concepts of network theory, it uses diagrams rather than equations to explain. (Anyone wanting a slightly more technical introduction to network theory needs to go elsewhere. Perhaps Barabasi’s Linked, as a still reasonably accessible read.)

Above all, The Human Network motivates the use of the network lens on economic and social questions, from epidemics to the diffusion of technology to financial crises to social immobility. Why did one long-discredited individual who made up his results for a 1998 article manage to trigger an anti-vaccination movement which is still leading to epidemics of infectious disease? What is the difference between a financial system that diversifies risk and one that concentrates it? Why are social media influencers a thing?

The Human Network is a very engaging and worthwhile read. I was for the most part familiar with the material it covers, but nevertheless enjoyed reading it, and also gained some insights about the different ways information can cascade through a network, either amplifying a single (possibly incorrect) piece of information, or pooling different sources of information for a more accurate picture. Given that our societies are highly interconnected in vast networks, and saturated with sources of information through online media, understanding the way networks function seems essential. One would hope at least public health authorities (to deal with epidemics) and financial regulators (to monitor the risk of systemic crisis) have their network diagrams at the ready. One of the messages I came away with is how easy it is for epidemics, real or metaphorical, to spread in the modern world of six degrees (or fewer) of separation.

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Global value chains

I’m very excited, as perhaps only an economist could be, by a new (and free) VoxEU e-book, The Age of Global Value Chains: Maps and Policy Issues. As the first sentence in the foreword states: “The study of global value chains is the only way to fully understand the nature of today’s geographically dispersed production and trade.” This understanding is being extended by new sources and uses of data, the World Input-Output Database in particular – the e-book has an appendix describing this.

GCVs front cover

The book divides into a descriptive first part (including a look at network structures) and a second part looking at the impacts of the increased specialisation in production across national borders. These impacts in turn are divided between the macro level (including productivity, wages and jobs) and the effects at the level of firm organisation. If I have one complaint (without having read the book yet) it is that there is no essay looking at global value chains from the perspective of urban economics, and the sub-national clustering of specialised supply chains.

Still, it’s a mild complaint about a book to say there should be more of it. I’ll be reading this one eagerly, all the more so as there are troubling signs that world trade growth is slowing. And, as I argued in my post on the FT’s The Exchange, that could be related to the global productivity puzzle.

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Putting people in economic theory

Some books are hard to judge. I can’t decide whether An Economic Theory of Greed, Love, Groups and Networks by Paul Frijters with Gigi Foster is brilliant or barking. It looks appealing, an attempt to combine the good aspects of the theoretical rigour of choice theory based on self-interest with the realities of human emotions. Of course love and group identity shape our choices! The book has endorsements on the back from economists I greatly respect. Andrew Oswald calls it, “The most remarkable book I have read in the last decade…. a book that is intellectually taxing but unforgettable.” Jeffrey Williamson and Bruno Frey love it too. So embarking on reading this, I thought it was going to be in the rich tradition of the Adam Smith of Moral Sentiments.

An Economic Theory of Greed, Love, Groups, and Networks

Instead, it’s a more difficult and theoretical read. It’s best explained in a blog post by Paul Fritjers, who says:

“[W]e take the stance of aliens looking at humans as just another species, with love merely one behavioural strategy available to that species. Blasphemous as this may sound, our goal is to apply the scientific method to the realm of the heart.

At the most basic level, we contend that love is a submission strategy aimed at producing an implicit exchange. Someone who starts to love begins by desiring something from some outside entity. This entity can be a potential sexual partner, a parent, “society”, a god, or any other person or abstract notion.From a position of relative weakness, the loving person tries to gain control over this entity.”

In fact, there are four core concepts, including the fundamental one of self-interested choice (‘greed’), in this alternative decision theory. They are love, groups (and power relations) and networks. These concepts are selected from all the other possibilities social scientists have suggested as important in shaping economic choices, such as social norms, freedom, identity, institutions and so on. How they are selected is not fully explained; the author says it follows much work on the explanatory power of each as a potential core concept but I am puzzled about the selection and the mix of categories – emotions, social structures, descriptors of status. Nor did I ever really understand how ‘explanatory power’ was tested. One could say that any of these concepts is self-evidently important in some way in individual choices and social outcomes.

A large chunk of the book sets out this rather odd idea that love is a generalised ‘Stockholm syndrome’ (as Andrew Oswald describes it on the back), a means of getting something from a more powerful person or entity. Apparently, neuroscience says love is not an emotion and nobody is pre-programmed to love anything: “A child needs to be stimulated to develop the ability to love… Unlike many animals, humans do not necessarily love forever what  they bonded with in childhood.” So the book goes on to explain the ‘evolutionary advantage of the love program’, and fits love into the mould of power relations. This takes the book onto a discussion of groups and power, and from groups to networks and markets. These sections touch on other, familiar areas of sociology and network theory.

Somewhere in the necessarily quite dense chapters on this wide-ranging material, I lost track of how the four core concepts lead us to a new choice theory. The final section of the book does look at how the new theory applies in familiar economic contexts. I focused on competition policy, and was disappointed to find that the consequence is to add not much to mainstream economic theory: “The view at which this book arrives regarding competition regulation is thus very close to the standard mainstream view in terms of the merits of any individual case. What is added is an understanding of who the regulator actually are and why they are there, what keeps them honest, where their power comes from, and what language affected parties will use in their appeals to regulators.” But how weird to add an understanding of the regulator and yet not an understanding of how big companies accumulate power and lobby regulators and politicians.

I think the book wants to rescue the fundamental assumption in economics of self-interested choice and make it relevant given all that we’ve learned about evolution, neuroscience and psychology in recent times. I thoroughly applaud this aim, because it is consistent with the evidence from evolutionary biology. Finding out how all this material across the disciplines can be married in a theory of decision making, on which economic models can build, is an important research agenda. This book is an ambitious effort to do so. It didn’t work for me, but now I’d like a lot of other people to read it and say what they think.

 

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Risk-related rambling

Not a new extreme sport, but some thoughts prompted by John Naughton’s column today on the vulnerability of important economic networks, such as just-in-time manufacturing or supermarket supply chains. It seems to me there’s an important gap between businesses making rational individual decisions about what they outsource and where, and how this aggregates up. For one manufacturer to outsource a vital component because there are lots of potential suppliers may be entirely sensible, but what if all the potential suppliers are clustered in one place, as is so often the case in global manufacturing chains? I doubt this question has made it to many businesses’ risk matrices. There’s an issue about diversity here – just as the border between the wisdom of crowds and the madness of crowds turns out to be all the individual members of the crowd having distinct ideas, not influenced by each other. For a supply chain that’s both efficient and resilient, you’d want the individual downstream components not to be linked to each other.

Network mathematics are tricky – I just looked in Barabasi’s 2002 Linked: The New Science of Networks, my reference on the subject, and can’t find anything there on this issue. I’ve read Six Degrees by Duncan Watts and Connected by Nicholas Christakis and can’t remember if the discussion of vulnerability and resilience in those touched on this diversity question. But somebody must have looked at it.

Linked: The New Science of Networks

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Big data 2.0

As I read a long Foreign Affairs article about Big Data and its ramifications this morning, it struck a real chord with a passage I’d just read in James Gleick’s interesting (although rambling) book The Information.

The Information: A History, A Theory, A Flood

He describes the use of the newfangled telegraph to send for the first time almost instantaneous news about the weather in different, distant parts of the country – fine in York, raining in Manchester. “The telegraph enabled people to think of the weather as a widespread and interconnected affair, rather than an assortment of local surprises.” Gleick quotes a commentator of 1848: “The telegraph may be made a vast national barometer.” (Tom Standage’s The Victorian Internet is a brilliant book about this particular communication medium.)

The possibility of weather reports led to the 1854 etablishment of the Meteorlogical Office by the Government, headed by Admiral FitzRoy, famously captain of The Beagle. In 1860 he began issuing the first weather forecasts. The science of meteorology, and understanding of a global interconnected system, was built on the foundation of the local weather information conveyed by telegraph.

The new book, Big Data, by Cukier and Mayer-Schoenberger appreciates the transformative scope of today’s Big Data 2.0 – in the article they write: “Big data is different: it marks a transformation in how society processes information. In time, big data might change our way of thinking about the world.” What the change will be is impossible to predict.

Big Data: A Revolution That Will Transform How We Live, Work and Think

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