When Michael Lewis came to dinner

That Michael Lewis came to dinner at our house once. This was about 30 years ago, when he was dating a friend of mine for a while, and before Liar’s Poker made him famous. He was charming – working in finance – but if only I’d known who he’d turn into, I’d have quizzed him closely about his stellar writing technique.

I’ve just devoured The Undoing Project, his much-trailed book about Daniel Kahneman and Amos Tversky, and their launching of the behavioural revolution in economics, over two evenings. It’s a wonderful book. I heartily recommend it as a Christmas gift for the economists in your life, or a treat for yourself over the holiday.

The book weaves together the personal and intellectual biographies of its protagonists. It explains the ideas, including the paradoxes requiring one to think about probabilities, beautifully clearly. It’s also just a terrific human story about an intense creative friendship as it flowed, and ebbed, over the decades and continents. If they’re not always totally likeable, the two characters are always immensely sympathetic.

It will surely send many readers on to Kahneman’s Thinking Fast and Slow, which requires some mental effort but everybody who fancies themselves an intelligent, educated person ought to have read. Although I’ve read loads of behavioural economics books and papers, and so think I know about a lot of the insights the literature has given us about how our decision-making processes function, there were still some new (to me) ones in The Undoing Project. These are two I found. Tversky had a rule that you must wait a day before replying to any invitation, even one you wanted to accept. It becoms much easier to decline the ones you don’t want. This is advice I definitely need to follow.

The other comes from thinking about reversion to the mean. An exceptionally (beyond average) good or bad performance is usually followed by one that is less good or less bad (closer to average).  Yet coaches and teachers and bosses often hold that if you praise someone for doing well, they do less well next time, and if you shout at someone for doing badly, they do better next time.  “Because we tend to reward others when they do well and punish them when they do badly, and because there is regression to the mean, it is part of the human condition that we are statistically punished for rewarding others and rewarded for punishing them,” wrote Kahneman. This strikes me as profound and something one ought to act on.

It was surprising to learn that at the height of his fame, in the years before his death, Tversky was bugged by the criticism of their work by Gerd Gigerenzer. I’ve never seen Gigernenzer’s argument that heuristic rules of thumb were rational because they economized on brain energy as a fundamental attack on Kahneman and Tversky, more an extension. There’s surely loads still to be discovered about decision making (especially under uncertainty), not least when decisions are conventionally ‘rational’ versus when ‘behavioural’ behaviour kicks in.

As economics is all about decision-making in the domain of resource use and allocation, this overlap with psychology and cognitive science is an exciting area – even though I’m deeply uneasy about the eagerness with which some economists and policy makers are leaping to adopt ‘nudges’ as another handy tool for social engineers to get the people to behave as they ought. We certainly ought to be teaching this at A level and in universities. The Undoing Project is a great book to introduce behavioural economics – and a cracking good story, told by a master.

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Another 2017 book to look forward to

This one, from Norton’s Spring catalogue, is the latest from Andrew McAfee and Erik Bryjolfosson, Machine, Platform, Crowd: Harnessing the Digital Revolution.

I’m sure their follow up to The Second Machine Age  and Race Against the Machine will be just as interesting as the others. Here’s the blurb: “We live in strange times. A machine plays the strategy game Go better than any human; upstarts like Apple and Google destroy industry stalwarts such as Nokia; ideas from the crowd are repeatedly more innovative than corporate research labs. MIT’s Andrew McAfee and Erik Brynjolfsson know what it takes to master this digital-powered shift: we must rethink the integration of minds and machines, of products and platforms, and of the core and the crowd. In all three cases, the balance now favors the second element of the pair, with massive implications for how we run our companies and live our lives. In the tradition of agenda-setting classics like Clay Christensen’s The Innovator’s Dilemma, McAfee and Brynjolfsson deliver both a penetrating analysis of a new world and a toolkit for thriving in it. For startups and established businesses, or for anyone interested in what the future holds, Machine, Platform, Crowd is essential reading.”

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Have we run out of innovations?

I’ve been reading old articles about about hedonic adjustment and followed one trail to a 1983 paper by William Nordhaus about the productivity slowdown between the 1960s and 1970s. He wrote: “Is it not likely that we have temporarily exhausted many of the avenues that were leading to rapid technological change?” (1981 working paper version here). Timothy Bresnahan and Robert Gordon pounce on this in their introduction to the 1996 NBER volume they edited on The Economics of New Goods: “The world is running out of new ideas just as Texas has run out of oil. Most new goods now, compared with those of a century ago, are not founding whole new product categories or meeting whole new classes of needs.” (Apropos of Texan oil, see this: Mammoth Texas oil discovery biggest ever in USA, November 2016.)

Gordon has, of course, doubled down on this argument in his magisterial The Rise and Fall of American Growth. (It is btw a great holiday read – curl up under a blanket for a couple of days.)

This reminded me I’d seen this post by Alex Tabarrok at Marginal Revolution:  A Very Depressing Paper on the Great Stagnation.

I haven’t yet read the paper it refers to, nor the earlier Jones one, and will do of course. It’s just that it seems we’ve been running out of ideas for over 30 years. I’ll say nothing about sequencing the genome and the consequent medical advances, new materials such as graphene, advances in photovoltaics, 3G/wifi/smartphones, not to mention current progress in AI, robotics, electric cars, interplanetary exploration. Oh, and chocolate HobNobs, introduced in 1987. Excellent for productivity.

For the time being, I’m going to stick with the hypothesis that we haven’t run out of ideas.

Rescuing macroeconomics?

It’s always with great diffidence that I write about macroeconomics. Although I’m in good company in being sceptical about much of macro (see this roundup from Bruegel and this view from Noah Smith, for instance), I’m all too well aware of the limits of my knowledge. So with that warning, here’s what I made of Roger Farmer’s very interesting new book, Prosperity for All: How To Prevent Financial Crises.

The book starts with his critique of conventional DSGE real business cycle and also New Keynesian models. Farmer rightly dismisses the idea that it’s ok to mangle the data through a Hodrick-Prescott filter and ‘calibrate’ the model, as in the real business cycle approach. But he also has a chapter criticising the (now) more conventional New Keynesian models. He writes, “Macroeconomics has taken the wrong path. The error has nothing to do with classical versus New Keynesian approaches. It is a more fundamental error that pervades both.” This is the idea that there is an ultimate full employment equilibrium. Echoing Paul Romer‘s recent broadside, he describes both as phlogiston theory. Echoing a number of others, he describes New Keynesian models as being like Ptolemaic astronomy, adding more and more complexity in a desperate and degenerate attempt to keep the theory roughly aligned to evidence.

The book demolishes the idea that there is a natural rate of unemployment (and thus also the idea of the output gap). Farmer argues that there are multiple possible outcomes and unemployment in many of these will persist in equilibrium. His alternative model – also a DSGE approach – replaces the New Keynesian Phillips Curve with a ‘belief function’, assuming that beliefs about future expected (nominal) output growth equal current realized growth.

It seems obvious to me that this approach is preferable to the New Keynesian and certainly RBC models, although this obviousness is rooted in my intuition – of course unepmloyment can persist and there can be multiple equilibria, duh! However, some things about it are less appealing. Above all, Farmer’s assumption that consumption is a function of wealth, not income. He replaces the conventional consumption function with one more purely related to the Permanent Income Hypothesis. This troubles me, although not because I disagree  with his view that the conventional Keynesian consumption function and multiplier are inconsistent with macro data. However, I thought the permanent income hypothesis sat badly with the data also, as it implies more consumption smoothing than is observed. It seems incredible too that many people look forward very far in determining their consumption level even if they do note and respond to asset price changes. Besides, most people have low net wealth – indeed, 26% of Britons have negative net financial wealth.

As the book points out, this change of assumption, and the role of the belief function, have strong policy implications. The debate about austerity, which is in effect an argument about the size of the multiplier (which we don’t know), is a distraction: higher government deficits will not shift the economy to a lower unemployment equilibrium. Instead, Farmer advocates a policy using the composition of the central bank balance sheet to manage asset markets and thus the level of output, and beliefs, through wealth effects (rather than including asset price inflation in an inflation target, as some have advocated). Balance sheet policies are effective because financial markets are incomplete: future generations cannot trade now; parents canot leave negative bequests.

This is a policy debate I’ll be leaving to those who are more knowledgeable than me – although of course those who know what they’re talking about will also have their own horses they’re backing in the race. It is striking that these macro debates rage around the same small amount of data, which is insufficient to identify any of the models people are battling over. In his excellent book about forecasting, The Signal and the Noise, Nate Silver pointed out that weather forecasters reacted to weaknesses in their models and forecasts by gathering many more data points – more observatories, more frequent collection. I see macroeconomists downloading the same data over and over again, and also ignoring the kinds of data issues (such as the effects of temporal aggregation) that time series econometricians like David Giles point out. So something like the David Hendry model-free approach, as set out in his recent paper, seems the best we can do for now.

My reservations should not stop anybody from reading Prosperity for All. It is an accessible read – undergraduate and maybe even A level students could cope with this  – and the model is available at www.rogerfarmer.com. I’d like to have seen some discussion of non-US data, and also structural change/non-stationarity. It’s also a short book, and as a macro-ignoramus I’d have liked some sections to be explained more fully. But these are quibbles. This is an important contribution to the debate about macroeconomics, and it’s an important debate because this is what most citizens think economics is all about, and macro policy has a profound effect on their lives.

I’m keen to read other reviews of the book now. I’m sure Roger is more right than the conventional DSGE approach – but also think the how-to-do macro debate is far from settled. How open-minded are more conventional macroeconomists?

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More 2017 books

The seasonal flurry of catalogues has continued with the latest from MIT Press. I’ll gather all these recent posts up towards the end of the month. But meanwhile, here are the highlights from this one.

Top of these is Peter Temin’s The Vanishing Middle Class, which I blogged about after seeing him present on it in September; and alongside that Vaclav Smil’s latest, Energy and Civilisation: A History. Other titles of interest include Tap: Unlocking the Mobile Economy by Anindya Ghose; Paid: Tales of Dongles, Checks, and Other Money Stuff, edited by Bill Maurer and Lana Swart; Information and Society by Michael Buckland; The Death of Public Knowledge edited by Aaron Davis; and Programmed Inequality: How Britain Discarded Women Technologists and Lost Its Edge in Computing by Marie Hicks.

There’s also what looks like a lovely book, Mary Shelley’s Frankenstein, “Annotated for Scientists, Engineers, and Creators of All Kinds.” The blurb says, “In our era of synthetic biology, artificial intelligence, robotics, and climate engineering, this edition of Frankenstein
will resonate forcefully for readers with a background or interest in science and engineering, and anyone intrigued by the fundamental questions of creativity and responsibility. This edition of Frankenstein pairs the original 1818 version of the manuscript—meticulously line-edited and amended by Charles E. Robinson, one of the world’s preeminent authorities on the text—with annotations and essays by leading scholars exploring the social and ethical aspects of scientific creativity raised by this remarkable story.”

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