Coffee table economics

I’ve been enjoying paging through Steven Medema’s The Economics Book: from Xenophon to Cryptocurrency, 250 Milestones in the History of Economics, not least because it has lots of lovely pictures. It’s a history of economic concepts –  that starts in 700 BCE with Hesiod to cryptocurrencies in 2009. Each entry has a beautiful illustration, no mean feat when it comes to illustrating Dynamic Stochastic General Equilibrium (a photo of the ECB), National Income Accounting (women washing dishes at home and hence not contributing to GDP), or Utilitarianism (Jeremy Bentham’s catalogue of the different sources of pleasure and pain). The pictures make it exactly the kind of book you’d be happy to have on the coffee table but it’s more than that: the selection of concepts and the capsule explanations do make it a useful starting point for people who’ve maybe read the terms or think they ought to know something about economics but have no idea where to start. They can start here without embarrassment (Hicks-Allen consumer theory, the School of Salamanca, the Shapley value….) and follow up elsewhere. It’s also a bargain – get the hardback, not the Kindle version.

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The wreck of welfare economics

I just re-read Will Baumol’s Welfare Economics and the Theory of the State, first published in 1952, based on his doctoral dissertation, with a 2nd edition in 1965. I started mulling over welfare economics while writing my latest book, Markets, State and People: Economics for Public Policy (OUT THIS WEEK – TA-DAH!).

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This is the area of economics concerned with the question of what it means for society to be better off. As a branch of theory, welfare economics is highly abstract and mathematical, covering the existence of a general equilibrium, its optimality properties (and the extent to which these are delivered by the market economy), and the various impossibility theorems about aggregating individual utlities into social welfare. As a matter of practice, some hazy sense of all of this theory lies behind policies such as the use of cost-benefit analysis. In writing the book, I became increasingly and uncomfortably aware of the theory-practice gap.

Better economists than me were on to this earlier. In 2001 the late, great Tony Atkinson wrote a powerful article noting the ‘strange disappearance of welfare economics’, largely ignored since the 1970s – it was published in a journal (Kyklos) unknown to many economists unfortunately. As it turns out, Baumol skewered the basic problem in this book. “Mathematical manipulation can yield no more than is contained in the premises which are being examined. Walras [in his work on general equilibrium], by assuming that every indivudal independently sought his own ends, obtained mathematical statements which amounted to the not excessively surprising assertion that every individual did as well for himself as possible under the circumstances.”

In other words, if you assume individuals are wholly independent, you conclude that the optimal economic organisation simply requires individual decision-making. But as Baumol points out in the final chapter, titled The Wreck of Welfare Economics, any brush with empirical reality underlines the interdependence of both production and consumption decisions. His conclusion: if economics is to say anything of practical use about economic progress, we need to start filling – with both theory and empirics – the currently empty boxes with labels like ‘externalities’ and ‘increasing returns’.

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Automation, the future of work and giraffes

Daniel Susskind’s A World Without Work: Technology, Automation and How We Should Respond is a very nice overview of the issues related to technological unemployment – will it happen, how will it affect people, and what policy responses might make sense. As the book notes, it is impossible to predict the number/proportion of jobs that might be affected, or how quickly, with detailed studies coming up with numbers ranging from about a tenth to about a half. But that there will be disruption, and that past policies have not dealt well with the consequences, is far less uncertain. Even if you believe that the economy will in time adjust the types and amount of work available – and so in that sense this time is *not* different from the past – the transition could be painful.

The book has three sections. The first looks at the history of technological unemployment and why we might expect AI to lead to a new wave. The second sets out the task-based analysis introduced by David Autor and others to sketch how the character of people’s work can change significantly. While dismissing the lump of labour fallacy, it argues that one of the main symptoms will be increased inequality. It predicts, gloomily, that this will get worse and that some people will be left with no capital and redundant human capital,, “leaving them with nothing at all.” I’m not sure that will be politically viable, judging from current events, but the logic is straightforward.

The final section turns to potential policy responses: improved education – heaven knows, we need that; ‘Big State’ – “a new institution to take the labour market’s place” – in effect more tax and a UBI; and tackling Big Tech through competition policy – yep, I’m definitely up for that. Finally, Susskind argues that part of the role for the Big State is to ensure we all have meaning in our working lives, replacing the job as the source of people’s identity, though I wasn’t sure how this should happen.

It’s a clearly-written book, covering concisely ground that will be familiar to economists working on this territory, and providing a useful overview for those not familiar with the debate. Although I’m not a fan of UBI, the other policy prescriptions seem perfectly sensible – perhaps too sensible to be inspiring.

41mVd8pmXCL._SX324_BO1,204,203,200_I must say that my other recent read has made me even more sceptical about the scope for AI to take over from humans. Recently I noted there has been a wave of terrific books on AI. Add to the list Janelle Shane’s You Look Like A Thing and I Love You. You’d be absolutely mad not to read this bok. It had me in hysterics, while making it super-clear what’s hype and what’s realistic about current and near-future AI. And explaining why image recognition AI is so prone to seeing giraffes – many giraffes – where there are none. An absolute must-read.

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Calculating the economy

One of the books I’ve read on this trip to the AEA/ASSA meetings in San Diego is The People’s Republic of Walmart by Leigh Phillips and Michael Rosworski. This is a very entertaining projection of the socialist calculation debate onto modern capitalism.

41JGcj2r26L._SX329_BO1,204,203,200_The starting point is the Simon/Coase realisation that big firms are internally planned economies – if it works for Walmart, why wouldn’t it work at larger scale? The authors’ hypothesis is that economic planning might work better now that we have so much more powerful computers and better data.

I’d recommend the book as an introduction to the socialist calculation debate for those unfamiliar with it (ideal for students). It cites some of my favourite books including Francis Spufford’s Red Plenty and Eden Medina’s Cybernetic Revolutionaries. Some chilling lines – about Stalin’s purges, for instance: “Anyone with any expertise was placed under suspicion.” It’s a great read.

Am I persuaded? Not entirely. Technology clearly will change organisational configurations, but it has just as much been decentralisation of firms and extended supply chains as it has been giant Walmart-type firms. I’m also sceptical that the data available is actually the information needed to plan an economy, or that it’s easy to access and join up. Still, it’s the right question, and a reminder that the boundary between market, state and other forms of organistaion is not set in stone but needs constant negotiation – in fact, I know a great book about this about to be published: Markets, State and People.

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Venture capital is social capital

Happy New Year, blog readers! Soon I’ll do my usual look ahead to 2020 books.

Meanwhile, this is from Trick Mirror, essays by Jia Tolentino, which I just finished. It’s an excellent, thought-provoking series of extended reflections on what life online is doing to us, and particularly how it interacts with the social constraints on women. As she says here, venture capital is social capital. In fact, capital is social capital.

This is why our Wealth Economy project started with what some people thought was the quixotic aim of measurement of social capital. But if economists think it’s so important – and we do, we just call it ‘goodwill’ or ‘institutions’ or some other term – we’d better be able to give it empirical life. So far, so good, in our work – the UK’s Industrial Strategy Council has taken up the social capital metrics produced by my Bennett Institute colleagues Matthew Agarwala and Marco Felici. But much left to be understood.

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