Learning to grow

I recently re-read Joseph Stiglitz and Bruce Greenwald’s (2014) Creating a Learning Society: A New Approach to Growth, Development and Social Progress (slightly amazed at how many years ago it was published, as I remember hearing Joe Stiglitz give a talk about it in Toulouse when it was just out. Seems much more recent in memory.)

It’s a masterly reframing of how to think about economic development and importantly appropriate policies in terms of quite simple models that are completely compatible with mainstream economics. The policy mix runs counter to what one could describe as conventional (mainstream) wisdom. The book advocates strategic industrial policy – because the models all involve hysteresis, so history matters and policymakers need to think about the path from here to the future; less extreme (albeit enfroced) IP rights because creating the incentive to innovate from a given pool of knowledge has to be traded off against a smaller pool of knowledge; trade/infant industry protection because learning by doing and learning from experience make production important to grow the pool of knowledge. The message about market structure – competition/concentration and static vs dynamic efficiency – is that it’s complicated. There’s no simple relationship.

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Above all, when technology is endogenous there can be no presumption that market outcomes are efficient, and policies need to think about how firms and society learn, and not just about allocative efficiency. It’s a great book for students because it demonstrates how to use models to think about complex policy options, and also that it is not bad economics to challenge market first-ism. Although pitched at developing economies, I went back to it to think about the levelling up challenge within the UK economy. Knowledge sticks to people, who stick in places, and as it accumulates places can diverge a lot over time. Given that innovation also requires adequate scale and some means of mitigating the uninsurable risks associated with it, the need for significant policy interventions seems clear to me.

 

 

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Humanomics – yes please

After a 700+ page tome, excellent as it was, I went next for Deirdre McCloskey’s 100 page Bettering Humanomics: A New, and Old, Approach to Economic Science. Her style is something of an acquired taste – I like it, but know some don’t. In any case, there is no doubting the extraordinary breadth and depth of her knowledge (which was on full display in her Bourgeois Virtues trilogy).

This essay is an update on a constant theme through McCloskey’s work, which is the need for a broader methodological approach to economics by economists. The discipline is hobbled by a narrow range of methods, an obsession with one particular style of showy reasoning (often powerful, but often tipping over into ‘mathiness‘ or the cult of statistical significance. Nick Crafts refers to the ‘identification police’, a character everybody who has had a paper rejected by Reviewer 2 because he doesn’t think causality has been demonstrated in the approved way will recognise. The methodological constraints are reinforced by the tyranny of the Top 5 and the insider process for selection that characterises them.

Anyway, I was predisposed to agree with McCloskey in Bettering Humanomics. Her main theme is that ideas and language shape the economy, and economics needs to listen. As she points out, rhetoric has often changed things on the ground in dramatic and sudden ways – we are not deterministic products of centuries of culture. Economies can turn around in short periods – think post-war Germany, Ireland and Portugal, or Thailand and South Korea. Such changes – and many other examples from the impact of advertising to same-sex marriage – torpedo a “notion of preknown preferences derived from utilitarian theory of decision without rhetorical reflection.” The implication is that the kind of arguments about economic development popular among economists based on game theory or some other theoretical structure explain too much: they are too universalist, and ignore the way our actions at any moment are shaped by the expectations of others and the contextual specifics. I cover similar ground in my next book, Cogs and Monsters (out October 12th!).

So, I liked Bettering Humanomics. It’s critical of economics but a critique by someone who knows what she’s talking about and loves the analytical and empirical power of the subject. I think economics is changing, re-embracing the work of economists such as Hirschman and Baumol and Veblen – I hope so. 51jI00dx7mL._SX331_BO1,204,203,200_

 

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The unknown pioneer

Many people – including economists, I suspect – won’t recognise the name Colin Clark. Yet he has at least as much claim as Simon Kuznets to be known as one of the pioneers of national income accounting. I came across Clark’s work when researching my book on GDP, and was pleasantly surprised to know that he had been a Fellow (and much earlier a student) at my Oxford college, Brasenose. Eventually I put two and two together and realised that the very nice chap I had spoken to at various events was Colin Clark’s youngest son David, another Brasenose student.

Anyway, this is all by way of preamble to saying how much I’ve enjoyed reading Alex Millmow’s biography, The Gypsy Economist: The Life and Times of Colin Clark. This is the first biography of somebody who worked as a young man with Keynes, taught Richard Stone, and produced some of the first modern statistics on national income; and later corresponded with Kuznets and Lewis, creating the field of development economics alongside them. In 1984 the World Bank honoured him as one of the 10 pioneers of development economics, along with Hirschman, Myrdal, Rostow, Bauer and others. Clark was influential in the Labour Party, being particularly close to Hugh Dalton, before spending many years in Australia, as a government economist in Queensland. Later he returned to England for some years, where he was involved in the founding of the Institute for Economic Affairs.

It is natural to ask why, given his scholarly work, Clark is so unknown now. After all, Stone, Lewis and Kuznets all went on to win the Nobel. The answer probably lies in that career history, and political trajectory. Actually, Clark not only left academia for years to take up a policy role, he also seems to have torpedoed his chances in two other ways. One – emerging clearly from between the lines of the book – is that he was a maverick character, possibly even cantankerous. The other is that he converted to Catholicism and became an ardent advocate of ‘distributivism’, which seems to have been a romantic philosophy advocating small rural communities and the virtue of farming. The biography quotes throughout many comments to the effect that Clark was brilliant but his books and papers were disorganised – lacked an organising analytical framework – and were sloppy in many regards. One typical comment described him as, “Brilliant, original, provocative, eccentric and sometimes just plain wrong.”

Having said this, there are many fascinating aspects of Clark’s thinking that emerge here, including some themes that have re-emerged in economics more recently. One is an early and lasting interest in increasing returns to scale, stimulated by working with Allyn Young. The second is simply the opening up of development economics through the empirics of long-run trends: Clark, like Kuznets, did not focus on (what became) GDP but – in his case – on statistics including income distribution, leisure, macroeconomic stability, and natural resource use and depletion. His Catholicism made him interested in non-state, non-business economic institutions such as churches but also friendly societies and unions – an openness to the economic role of a variety of community institutions only just returning in today’s mainstream economics. It also meant he was pro-population growth (he & his wife had 9 children themselves), considering it essential for per capita growth as modern endogenous growth theories imply, and a fierce critic of the Ehrlich ‘population time bomb’ argument.

This very informative biography made me rather ashamed not to have known anything about Colin Clark until a few years ago, even when his papers were sitting in my college library. I learned a lot more from reading it. The book fills a gap in the history of economic thought, and about the history of policy economics in Australia. (Alas, it’s priced for libraries.)

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Endogenising economists

I’m afraid I was underwhelmed by The Power of Creative Destruction by Philippe Aghion & his co-authores Céline Antonin and Simon Bunel. The book falls between the two stools of textbook for econ courses and overview for the general reader. It is based on course notes and has that tone (and charts/tables/referencing of the literature), but all the technical apparatus students would need has been removed. Professor Aghion is of course a terrific economist who has published lots of excellent papers on growth and innovation. However, that too is a downside here, as the book is the Aghion view of the world rather than a broader survey of the economics of innovation and growth.

The oddest aspect of this is his contrast between the Solow neoclassical growth model and the ‘new paradigm’ of Aghion-style Schumpeterian growth. Set aside this claim to novelty, which might cause many other Schumpeterian economists to raise an eyebrow; there is nothing here about the competing workhorse approach of endogenous growth models. Paul Romer makes it to the footnotes, Paul Krugman’s increasing returns models not that far, Ken Arrow too isn’t mentioned. Joseph Stiglitz fares best out of the prominent thinkers about markets, growth and development in the context of increasing returns. The book is more or less an account of Prof Aghion’s own research, and his own papers (excellent as they are) are the most-often cited. So while accepting the importance of creative destruction and new ideas, the absence of much about information and ideas is pretty glaring. There is a chapter about R&D but little about the economic models endogenizing it.

I could quibble about other features too, such as relying on patents to measure innovation, but it’s this missing aspect of the dynamics – the scope for endogenous, self-fulfilling or -averting phenomena – that seems a particularly big gap. The discussion of intellectual property lacks any nuance: it is simply asserted that patent protection is essential. Of course it is, but that isn’t the point of the present policy debate, which is exactly about whether the right balance between patent-protected monopoly and broad access to new ideas has been struck.

41eUnCMDnVL._SX329_BO1,204,203,200_On the other hand, I also read Carlo Rovelli’s Helgoland and warmly recommend it. It sets out his view about quantum phenomena as manifestations of the fact that reality is relational: nothing is experienced, perceived, measured, or understood except in relation to everything else. “Every vision is partial. There is no way of seeing reality that is not dependent on a perspective. …. The actor of this process is not a subject distinct from phenomenal reality, outside it, nor any transcendent point of view; it is a portion of that reality itself.. …. Relations make up our ‘I’, as our society, our cultural, spiritual and political life.”

This appeals strongly to my intuition and echoes the argument of my forthcoming book, Cogs and Monsters, one of whose key threads is the point that economists can not stand outside the society they seek to analyse. Even the economists are endogenous.

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Are humans or computers more reasonable?

This essay, The Long History of Algorithmic Fairness, sent me to some of the new-to-me references, among them How Reason Almost Lost its Mind by Paul Erickson and five other authors. The book is the collective output of a six-week stint in 2010 at the Max Planck Institute for the History of Science in Berlin. That alone endeared it to me  – just imagine being able to spend six weeks Abroad. And in Berlin, which was indeed my last trip Abroad in the brief period in September 2020 when travel was possible again. I started the book with some trepidation as collectives of academics aren’t known for crisp writing, but it’s actually very well written. I suspect this is a positive side-effect of interdisciplinarity: the way to learn each other’s disciplinary language is to be as clear as possible.

The book is very interesting, tracing the status of ‘rationality’ in the sense of logical or algorithmic reasoning, from the low status of human ‘computers’ (generally poorly-paid women) in the early part of the 20th century, to the high status of Cold War experts devising game theory and building ‘computers’, to the contestation about the meaning of rationality in more recent times: is it logical calculation, or is it what Herbert Simon called ‘procedural rationality’? This is a debate most recently manifested in the debate between the Kahneman/Tversky representation of human decision-making as ‘biased’ (as compared with the logical ideal) and the Gerd Gigerenzer argument that heuristics are a rational use of constrained mental resources.

How Reason… concludes, “The contemporary equivalents of Life and Business Week no longer feature admiring portraits of ‘action intellectuals’ or ‘Pentagon planners’, although these types are alive and well.” The arc of status is bending down again, although arguably it’s machine learning and AI – ur-rational calculators – rather than other types of humans gaining the top dog slot nowadays. As I’ve written in the economic methodology context, it’s odd that computers and also creatures from rats to pigeons to fungi are seen as rational calculators whereas humans are irrational.

Anyway, the book is mainly about the Cold War and how the technocrats reasoned about the existentially lethal game in which they were participants, and has lots of fascinating detail (and photos) about the period. From Schelling and Simon to the influence of operations research (my first micro textbook was Will Baumol’s Economic Theory and Operations Analysis) and shadow prices in economic allocation, the impact on economics was immense. (Philip Mirowski’s Machine Dreams covers some of that territory too, although I found it rather tendentious when I read it a while ago.) I’m interested in thinking about the implications of the use of AI for policy and in policy, and as it embeds a specific kind of calculating reason, thought How Reason Almost Lost its Mind was a very useful read.

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