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The trade-investment-service-intellectual property nexus

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I’ve managed to resist reviewing Richard Baldwin’s new book The Great Convergence: information technology, trade and the new globalization until now, and it has taken serious self-restraint as the book is so relevant to (among other things) the Brexit debate. I would for one thing force every Cabinet member to read it and not allow them to keep their jobs unless they could pass an exam based on it. Anyway, the book’s published on 14th November and now it’s November my self-denying ordinance can end.

The Great Convergence offers a compelling framework for thinking about how trade is organized and why and how it benefits whom. The first part is a historical overview of trade leading up to the first, the Old Globalization or the 19th century. This phenomenon, due to steam power reducing trading costs, industrialization and a context of relative global peace led to the Great Divergence: the major economies of Asia, which had been richer than the West, fell behind, dramatically so over the course of two centuries. The New Globalization, since the 1980s, driven by the new information and communication technologies, has taken the rich countries’ share of global output back to its 1914 level in little over two decades. China is the standout story, going from uncompetitive in 1970 to 2nd biggest in the world by 2010, but other rapidly industrializing nations in the New Globalization are Korea, India, Poland, Indonesia and Thailand (ie. a different group from the notorious BRICs).

However, as the book goes on to document, the New Globalization is a completely different kind. Trade over distance has three costs: the costs of moving goods, ideas and people. When moving goods got cheap, the first explosion of trade occurred, but ideas were costly to move so the innovations of the industrial revolution were not easily exported. The Old Globalization was the result of low shipping costs and high communication costs. ICTs have reduced the latter significantly, so industrial competitiveness is defined in terms of production networks, interlinked supply chains, that cross national borders. Knowledge has been offshored, and the rapid growth in a few previously poorer countries has come about because of their geographical location, close enough to G7 industrial centres that managers can travel there, sharing knowledge within the confines of the production network.

This means the New Globalization happens at the level of stages of production and occupations. This makes it harder to predict who will be affected – which jobs will be offshored, which areas most affected. “Nations are no longer the only natural unit of analysis”. Much of the book describes a new data set making it possible for economists to begin to explore the ‘value added’ pattern of trade created by the switch from trading finished goods toward trading components in global production chains. The picture is going to be utterly different – the famous example being the iPhone which is sourced conventionally as a Chinese export to the US but where the value added is concentrated in the American business and the Chinese import a lot of the components they assemble and re-export with not much value added at that stage.

This is one insight the Brexiteers need to appreciate, although the Nissan letter suggests at least some members of the government realise the signficance. British businesses are woven into supply chains with our near neighbours: we aren’t importing prosecco and salami so much as gear boxes. Brexit threatens to tear apart these links. If the cost appears to be too high, the multinationals at the head of the supply chains will relocate chunks of their production networks, and won’t care if they’re exporting gear boxes to the Czech Republic rather than Britain.

The book adds: “Twenty-first century supply chains involve the whole trade-investment-service-intellectual property nexus, since bringing high quality, competitively priced goods to customers in a timely manner requires international coordination of production facilities via the continuous two-way flow of goods, people, ideas and investments. Threats to any of these flows become barriers to global value chain participation…” Baldwin adds that the movement of people is still a binding constraint on globalization, and face-to-face communication – and so distance – remain important. He argues that the improving quality of telepresence is changing this, but I think that remains to be seen.

Ultimately, trade policy today is not just about trade nor about nations. It involves deploying the nation’s productive resources through overseas connections. This is why 90% of the economics profession thought, and thinks, Brexit so damaging, and the idea that the UK has more economic self-determination outside the EU a delusion. The Great Convergence is not about Brexit – it ranges far wider. I can’t imagine a better and more accessible analysis of trade and globalization in the digital era.

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(20 November: minor typos corrected)

Still more upcoming books

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It’s always a pleasure to read the new publishers’ catalogues. Apart from the lovely pictures, one always has the frisson of thinking about all the interesting books there isn’t going to be time to read but maybe mental osmosis from looking at the covers and blurbs works a little….

Anyway, the Yale University Press catalogue for Spring and Summer 2017 just landed. The economics/tech books on offer promise a rather gloomy view of the world.

I’m looking forward to (and will definitely read rather than osmose) Stephen King’s Grave New World: the end of globalisation and the return of the economics of conflict. The title says it’s even gloomier than his last book, xxxx. There are two interesting looking titles on environmental economics. One is my Natural Capital Committee colleague Dieter Helm’s Burnout: The endgame for fossile fuels. The other is Benjamin Barber’s Cool Cities: the urban fix for global warming.

The other title here I’m very much looking forward to reading is Zeynep Tufekci’s Twitter and Teargas: the power and fragility of networked protest. Remember the Arab Spring, the hope of social media facilitated liberation movements? It seems an aeon ago. Now we have authoritarian surveillance and Trumpism and the Alt-Right.

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Wanting to change

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Anybody who reads Duncan Green’s excellent blog, From Poverty to Power, won’t be entirely surprised by the approach he takes in his equally excellent new book, How Change Happens. It is based on two pillars. One is Amartya Sen’s capabilities approach to human development (‘the freedoms to do and to be’), and I’ve always thought that when you appreciate its ethical and practical merits, it’s hard to take any other approach. The other is the need for systems thinking when it comes to considering economic policies or other interventions – in any context, really, but certainly in the case of development.

“Change in complex systems occurs in slow steady processes such as demographic shifts, and in sudden, unforseeable jumps,” Green writes. Mostly, change is extremely, painfully slow. It turns out to be impossible to do one thing because another, linked thing gets in the way. Events and crises open the way for the big shifts – being an economist, I think of this in terms of what it takes to move a co-operative game to a new focal point. But even then, the direction of the jump is contingent, messy, unpredictable. It anyway depends on the prevailing climate of ideas and norms – so part of the challenge is to be ready to take advantage of a crisis by having done all the contextual spade work, all the while getting on with the day job of trying to bring about incremental changes in the previous state of affairs.

Needless to say, this does not make for a concise ten-point plan in the final chapter (although it does try to sum up the whole in a ‘power and systems approach’ in the final few pages). The book has some interesting practical ideas, however. I like the principle of looking for ‘positive deviance’ – look for examples of people or activities that succeed against enormous odds, for outliers, and use them as ‘social proof’ so others copy whatever it is. This is exactly the way new technological innovations spread: the ideas are there, a few people try, and others imitate them. There are loads of examples of advocacy and development organisations and initiatives that have been able to implement responsive, adaptable changes (many of these brought Tim Harford’s Adapt to mind). Other suggestions are harder to see how to implement. The book argues that principled leadership matters. I agree. But where is it? How do donors encourage it?

Green concludes that many organisations in the aid world, including his own, need to move away from linear thinking and get wiser to context and the whole complex environment (actual and political) in which they operate. I hope they follow his advice and this book is certainly well worth anyone working in this world reading. The one element missing, though, seems to be the meta-analysis of the development agency ecosystem itself, and the prevailing ideas. For example, how do you get social innovation akin to technological innovation in a world of impact assessment and RCTs? Or indeed combine fleetness of foot with a genuine need to understand ‘what works’? Understanding one’s own cognitive biases or limitations is a tall order. What’s more, the aid world has incentive structures built in that will discourage change. In a variation on the old lightbulb joke (How many psyhologists does it take to change a lightbulb? Only one, but the lightbulb has to really want to change), how change happens is that a lot of people have to want change to happen.

Anyway, there’s no excuse for not reading the book, as it’s also published as an open access pdf. I hope lots of activists read and digest and change their approach, but suspect it will prove difficult for many.

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Not the smartest animals

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The title of Frans de Waal’s latest book is a rhetorical question: Are We Smart Enough to Know How Smart Animals Are? I thoroughly enjoyed reading it. De Waal’s deep knowledge shines through every sentence, as does his delight in all the creatures (especially other primates) he has spent his career studying. The book is about the evolution of cognition and emotion in animals (including humans). It particularly debunks Skinner’s behaviourism – mental processes as a black box, but manipulable using reward and punishment. (This of course the approach behind the present fashion for behavioural economics, a fashion I find troubling because some of its enthusiasts do so clearly see themselves as omniscient scientists ordering society for the better by manipulating the choices of their less intelligent subjects.)

I learned a lot from the book, including that the elephant brain is the one with the most neurons (about 3 times as many as we do). The neural differences between humans and other primates are not sufficient to make us unique in all aspects (although we clearly are in some, notably language). De Waal argues we should assume continuity, a spectrum of cognitive abilities between different animals, rather than sharp and wide distinctions. He notes that psychology is moving to accept this assumption, but the social sciences tend to assume human discontinuity – “But what does it mean to be human?” he reports social scientists asking him. “I usually answer with the iceberg metaphor, according to which there is a vast mass of cognitive, emotional and behavioural similarities between us and our primate kin. But there is also a tip containing a few dozen differences. The natural sciences try to come to grips with the whole iceberg, whereas the rest of academia is happy to stare at the tip.”

The scientific project must therefore be to develop a unitary theory of different cognitions, how cognition operates in general, and then in the case of each particular species. The book emphasises two important contributors: sense perceptions (is vision the most important to the species? or hearing, or smell?); and social relations (is it a species with strict social hierarchies, like chimpanzees, or solitary, like the octopus?) “Cognition and perception cannot be separated… they go hand in hand,” he writes. (Interesting to reflect on what this means for AI. The question is not so much what androids dream of as what they see or hear.)

To crown a wonderful book, it ends with a quotation from David Hume: “Tis from the resemblance of the external actions of animals to those we ourselves perform, that we judget their internal likewise to resemble ours; and the same principle of reasoning, carried one step farther, will make us conclude that since our internal actions resemble each other, the causes, from which they are derived, must also be resembling. When any hypothesis, therefore, is advanced to explain a mental operation, which is common to men and beasts, we must apply the same hypothesis to both.” As Hume summed it up, “No truth appears to me more evident than that beasts are endowed with thought and reason as well as men.”

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Revolt of the data points

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Libération has a very interesting article about the politics and ethics of big data. It cites some excellent books, such as Eden Medina’s brilliant Cybernetic Revolutionaries about Project Cybersyn in Allende’s Chile, and Alain Desrosières’ classic The Politics of Large Numbers. It doesn’t mention Francis Spufford’s Red Plenty, which makes exactly this point (and is a cracking read too): «La planification soviétique et l’ultralibéralisme se rejoignent ainsi pour asservir le droit à ses calculs d’utilité.»

There is huge interest in using big data techniques to construct better economic statistics (including on my part!). Here in the UK, the ONS is launching a data science campus. The Turing Institute has just been funded by HSBC to look at economic data (although the release says nothing about the work or the researchers involved, so this looks like very early stages). There’s particular progress on constructing price indices using big data, as in this VoxEU column or the Billion Prices Project.

But, as the Libération article underlines, the utopianism of ‘datacratie’ can tip into a dystopian extreme. The technology looks like it can make the utilitarian project of measuring the costs and benefits of everthing a reality, extracting information from every click, every move, every choice. But when the data points (aka humans) realise what’s happening, they won’t necessarily like it.

Bring on the philosophers and ethicists.

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