Tag Archives: complexity

We’re all doomed – maybe

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I read Peter Turchin’s (2023) End Times: Elites, Counter-Elites and the Path of Political Disintegration on a long flight yesterday (I’m at Stanford for a couple of workshops). I’m not sure what to make of it. It’s well-written and an engaging read. The basic idea that there is a pendulum in the strength and health of polities, of generation-long good times and bad times, seems valid enough. The idea that one can model these computationally, I find a bit weird – speaking as one who spent some years early in her career modelling the UK and other economies computationally. Predicting outcomes from those models a year ahead that was tricky enough. This kind of system-wide modelling involves a great deal of judgement whereas this book claims an implausible degree of automaticity. As a sceptic about macroeconomic-modelling I’m a natural sceptic about – whatever we are going to call this – metaeconomic-modelling?

Turchin’s dynamics are driven by two phenomena: the immiserisation of the working class as the labour share of the economy declines, due to a ‘wealth pump’ as successful elites rig the economy to grab ever more of the value; and the over-production of elites who have to compete to benefit from the wealth pump. After a cycle of growth and integration, these mechanisms give way to a cycle of conflict and chaotic politics, driven by a coalition of the impoverished (Trump voters from the former manufacturing heartlands) and the not successful-enough elites (J.D.Vance).

This is a neat model, and seems to correspond to today’s US reality, but I have questions. For example, if expanding education is ‘over-production of elites’, what are we to make of the role of expanded education in technical progress and growth – is periodic conflict simply a cost of investment in human capital that has to be borne? Where does the role of demand in creating jobs for these productive people fit in? Do we need a war to kill off the excess PhDs and return to a stable, integrative phase? The role of excess labour supply in Turchin’s model seems to involve the lump of labour fallacy. All the (UK) evidence I know on immigration is that the effects on local wages and employment depend on (a) how complementary or not the skills of migrants are to local skills and (b) the state of the business cycle. Additional labour supply does not automatically mean immiserisation of workers.

There’s also a long quotation from Jack Goldstone to the effect that the population had grown substantially for 50 years before every major revolution and rebellion between 1500 and 1900. Does this mean the model will predict no more revolutions outside sub-Saharan Africa as populations are now in decline? It’s also a very US centric book despite using historical examples from many countries. For the instance UK labour share has not fallen like that in the US, although median wages have certainly stagnated.

I suppose in the end how seriously you take this kind of modelling depends on your belief about the extent to which human societies can learn and thus escape from past patterns. For what it’s worth, the book predicts the 2020s in the US will stay tumultuous. Of course, one doesn’t need a model to see this. I visit here once or twice a year but might stay away for a bit after early November 2024.

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Future uncertain

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I’m late to Radical Uncertainty by John Kay and Mervyn King, which was published last year. It took me a while to get into the book but I’ve enjoyed it and found much to agree with. The basic hypothesis is well known: that the kinds of models and methods useful for understanding what the authors call ‘small world’ or well defined problems are not useful for dealing with the contexts of many actual economic challenges. In these cases, from innovation or financial stability to climate change, ‘radical uncertainty’ demands a less narrowly formal approach. The term the book uses is that we should be asking ‘what is going on here?’ By radical uncertainty they go beyond Taleb’s famous black swans, or events in the fat tails of distributions. Rather, they mean there is no stable underlying probability distribution at all. This is the territory of unknowable futures. Is the Earth’s climate going to change irreversibly in the years ahead and if so how? There’s no probability to read off for this.

Some of the analysis is familiar. For instance the idea of reflexivity (from Popper via Soros among others) undermines the stationarity of probability distributions. In other words, one source of radical uncertainty is that we humans respond to events in ways that can be self-fulfilling or self-averting (see Chapter One of my Cogs and Monsters!) Kay and King also emphasise the important role of narratives, increasingly recognised (and btw we have a terrific Bennett Institute event on this coming up). I strongly agree with their scepticism about the scope for replacing humans with machine learning systems to get ‘better’ outcomes – as they put it, justice should be admininstered in an individual, not a statistical, manner. Otherwise we’re in the nightmare world of Minority Report. Human intelligence is accumulated collective intelligence, and co-ordination and institutions are all-important.

The book is full of examples of where policies go wrong by assuming a small world problem in a context of radical uncertainty. The UK pensions regime for example, applying technical valuations of the worth of pensions schemes which assume a stationary distribution of future returns – something belied by the evidence. Future risk can’t be eliminated so what’s needed is a future risk-sharing mechanism, rather than raising contributions now to unaffordable and unnecessary levels. (See for instance this excellent article about the UK’s USS scheme.)

As you would expect given the authors, the book is wide-ranging and beautifully written. There’s a tacit acknowledgement that these two eminent economists have changed their minds about the applicability of much of mainstream economics, for Mervyn King at least held an important role at the heart of mainstream policy. Good for them, though – so have I. As well as reading Radical Uncertainty on its own merits, it offers an interesting insight into the tides of change within economics, about which I’ve also written.

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Complexity across boundaries

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Summer, with its leisurely hours for reading, seems a long time ago. I have managed Barbara Kingsolver’s excellent novel Unsheltered. And also, discovered down one of the by-ways of Twitter or the Internet, Worlds Hidden in Plain Sight, edited by David Krakauer. This is a collection of columns by researchers at the Santa Fe Institute dating back to its establishment in 1984.

SFI is of course the best-known centre for the study of complexity across disciplinary boundaries, and its work on economics is always at least intriguing and often far more. Like any collection of essays this is a mixed bag. One striking feature is how much more focused the later ones become on the social sciences and the humanities, compared to the earlier focus on biology and physics. I don’t know if this is an artefact of the selection or actually reflects the balance of work there, but it’s also obvious I suppose that human activity and society is inherently complex. A few of the essays – although intended for a not-entirely-specialist audience – are utterly incomprehensible to someone who isn’t a disciplinary expert. I suspect one or two were also incomprehensible to their authors. And the most recent batch consist of some disappointingly banal essays for a newspaper.

In between, however, I found much food for thought – particularly on the lessons at disciplinary borders: information science, economics, anthropology, biology…. As one 2011 essay by Krakauer puts it, we have to recognize that “many of our most pressing problems and interesting challenges reside at the boundaries of existing disciplines and require the development of an entirely new kind of sensibility that remains ‘disciplined’ by careful empirical experiment, observation and analysis.”

What else? There’s a brilliant 2009 essay by Ole Peters, entirely justifying the cost of the book, explaining in a few pages with great clarity why ignoring the non-ergodicity of economic and financial variables has led to catastrophic policy errors. A 2012 Robert May essay alerted me to a calculation I’ve not spotted before by Ben Friedman (my thesis adviser) that before the crisis running the US financial system “took one third of all profits earned on investment capital,” up from 10% three decades earlier.

And I’ve been thinking about information – the way ideas and imagination, not mechanical or physical constraints, limit social progress; and puzzling how the role of information in energy use and social complexity, a running thread. One day I’m going to have to get my head properly around information theory.

Like all collections, this book has the merit of being easy to dip into and read in chunks. It’s a great overview of the work of SFI, one of the most interesting research centres anywhere. More power to their elbow.

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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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The world of yesterday

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I’ve ben indulging in a non-econ book again, Stefan Zweig’s The World of Yesterday. Beautifully written, unsurprisingly dark, and – knowing his end – poignant. 51sqimqxfolThis paragraph describes life in post-WW1, chaotic, hyper-inflating Austria:

“The will for life to go on proved stronger than the instability of the currency.  … The baker made bread, the cobbler made boots,the writer wrote books, the farmer cultivated the land, trains ran regularly, the newspaper lay outside your door every morning at the usual time, and the places of entertainment, in particular the bars and the theatre, were full to overflowing. For with the daily loss of the value of money, once the most stable aspect of life, people came to appreciate true values such as work, love, friendship, art and nature all the more, and in the midst of the disaster the nation as a whole live more intensely than before, strung to a higher pitch.”

The other message of the book is how quickly societies can change, how almost overnight one normality vanishes, to be replaced by another. This was also the lesson of one of the most powerful books I’ve read, Richard Overy’s Interrogations, a study of the documents related to the interviews conducted with the accused in the Nuremberg Trials. He concluded that the moral universe in which people live can, similarly, change almost instantaneously, so powerful are the forces of conformity that create and sustain social norms. These norms are very strong – until they’re not. This is the lesson too from Joseph Tainter’s work. So – for those of us who live in stable and prosperous places – the message is: never forget that underlying capacity of social order to crumble very quickly.