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  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 .

[amazon_image id=”1107678943″ link=”true” target=”_blank” size=”medium” ]An Economic Theory of Greed, Love, Groups, and Networks[/amazon_image]

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 , my reference on the subject, and can’t find anything there on this issue. I’ve read  by Duncan Watts and  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.

[amazon_image id=”0738206679″ link=”true” target=”_blank” size=”medium” ]Linked: The New Science of Networks[/amazon_image]

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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 .

[amazon_image id=”0007225741″ link=”true” target=”_blank” size=”medium” ]The Information: A History, A Theory, A Flood[/amazon_image]

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  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 . 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, , 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.

[amazon_image id=”1848547900″ link=”true” target=”_blank” size=”medium” ]Big Data: A Revolution That Will Transform How We Live, Work and Think[/amazon_image]

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A modest proposal (involving digital market dynamics)

One of the best books about the effect of digital technology on business dates from 1999.  by Carl Shapiro and Hal Varian (now chief economist at Google). Until recently, I’ve thought it didn’t need updating, for although the examples are obviously dated, the principles are not.

[amazon_image id=”087584863X” link=”true” target=”_blank” size=”medium” ]Information Rules: A Strategic Guide to the Network Economy[/amazon_image]

However, a couple of excellent recent books on the telecommunications and media sector have made me start to wish for an update of Information Rules. They are Timothy Wu’s  and Susan Crawford’s new book,  Telecoms is obviously a network industry, with the characteristic kind of increasing returns to scale you get with networks.

[amazon_image id=”1848879865″ link=”true” target=”_blank” size=”medium” ]The Master Switch: The Rise and Fall of Information Empires[/amazon_image]

[amazon_image id=”0300153139″ link=”true” target=”_blank” size=”medium” ]Captive Audience: The Telecom Industry and Monopoly Power in the New Gilded Age[/amazon_image]

Both these newer books are excellent on the sector. What I’d like is an update – beyond the one chapter in the 1999 edition of Shapiro and Varian – on business strategy and market dynamics (including two-sided aspects) in network markets. For digital connectivity is making the network aspect more prominent in other sectors. Finance is obviously one, but there are more sectors where digital technologies are enabling new forms of intermediation as well as disintermediating old forms, where there are information asymmetries or experience goods, and where access to new platforms is becoming vital. Consider publishing, or indeed even retailing – say a new fashion designer facing a declining physical high street.

So here’s a modest proposal: please will somebody write about these new market dynamics (and the competition and distributional implications) where we need two-sided market models, increasing returns and non-linearities, and the experience good/public good characteristics taken into account?!

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