Paul Collier writes a thoughtful obituary in the TLS:
Thankfully, we now know that Economic Man is a travesty. Blueprint: The evolutionary origins of a good society by Nicholas Christakis is the latest study to affirm this. It shows why, through the forces of evolution, Homo sapiens emerged as a uniquely social species. Far from being evolutionarily inevitable, Economic Man was culled almost to extinction, surviving only as the highly deviant behaviour we call psychopathic. In hunter-gatherer societies, hunters do not “eat what they kill”: such behaviour would bring social ostracism, so the hunters share their catch. The theorems derived from Economic Man explain the conditions under which a society of psychopaths would be able to function. In most contexts, those conditions turn out to be fanciful: the efficient paradise depicted in economics textbooks has never existed, and never will. Instead, in well-functioning societies, humans construct and abide by a vast web of kindness and mutual obligations of which Economic Man would be incapable.
Esther Duflo is only the second woman to win the Nobel Prize in economics (she shared this year’s prize with Abhijit Banerjee and Michael Kremer). She’s also the youngest recipient of the prize. This is the TED talk she gave in 2010 explaining some of the work which won the prize.
From John Lanchester, opening a thoughtful and informative LRB essay on the idea of Universal Basic Income. “The broad outline of 21st-century history, its first couple of decades anyway”, he writes,
is starting to become clear. A period of credit-fuelled expansion and runaway financialisation ended with an abrupt crash and an unprecedented bank bailout. The public’s reward for assuming the bankers’ losses was austerity, which crippled the recovery and led to an interminable Great Recession. At the same time, increasing automation and globalisation, and the rise of the internet, kept first-world wages stagnant and led to an increase in precarity. Elites did fine, and in the developing world, especially Asia, economies grew, but the global middle class, mainly located in the developed world, felt increasingly anxious, ignored, resentful and angry. The decades-long decline in union power made these trends worse. The UK had its longest ever peacetime squeeze on earnings.1 In response to this the political right played one of its historically most effective cards – Blame the Immigrants – and achieved a string of successes from Brexit to Trump to Orbán to Bolsonaro to Salvini and the AfD, succeeding in normalising its new prominence to such an extent that a quasi-fascist party scored 34 per cent in the French presidential elections, which were nonetheless hailed as a triumph for the ‘centrist’ winner.
That’s a pretty good summary, IMHO. Characteristically good piece by a terrific explainer. Worth reading in full.
Interesting essay by Dani Rodrik:
Any optimism about the scale of GVCs’ contribution must be tempered by three sobering facts. First, the expansion of GVCs seems to have ground to a halt in recent years. Second, developing-country participation in GVCs – and indeed in world trade in general – has remained quite limited, with the notable exception of certain Asian countries. Third, and perhaps most worrisome, the domestic employment consequences of recent trade and technological trends have been disappointing.
Upon closer inspection, GVCs and new technologies exhibit features that limit the upside to – and may even undermine – developing countries’ economic performance. One such feature is an overall bias in favor of skills and other capabilities. This bias reduces developing countries’ comparative advantage in traditionally labor-intensive manufacturing (and other) activities, and decreases their gains from trade.
Second, GVCs make it harder for low-income countries to use their labor-cost advantage to offset their technological disadvantage, by reducing their ability to substitute unskilled labor for other production inputs. These two features reinforce and compound each other. The evidence to date, on the employment and trade fronts, is that the disadvantages may have more than offset the advantages.
The usual response to these concerns is to stress the importance of building up complementary skills and capabilities. Developing countries must upgrade their educational systems and technical training, improve their business environment, and enhance their logistics and transport networks in order to make fuller use of new technologies, goes the oft-heard refrain.
And here’s the punchline:
But pointing out that developing countries need to advance on all those dimensions is neither news nor helpful development advice. It is akin to saying that development requires development. Trade and technology present an opportunity when they are able to leverage existing capabilities, and thereby provide a more direct and reliable path to development. When they demand complementary and costly investments, they are no longer a shortcut around manufacturing-led development.
“Data is neither a good or service. It’s intangible, like a service, but can easily be stored and delivered far from its original production point, like a good.” Michael Mandel
He goes on to make a useful observation about how our national statistics surveys may be missing something important:
Paradoxically, economic and regulatory policymakers around the world are not getting the data they need to understand the importance of data for the economy. Consider this: The Bureau of Economic Analysis, the U.S. agency which estimates economic growth, will tell you how much Americans increased their consumption of jewelry and watches in 2011, but offers no information about the growing use of mobile apps or online tax preparation programs. Eurostat, the European statistical agency, reports how much European businesses invested in buildings and equipment in 2010, but not how much those same businesses spent on consumer or business databases. And the World Trade Organization publishes figures on the flow of clothing from Asia to the United States, but no official agency tracks the very valuable flow of data back and forth across the Pacific.
The problem is that data-driven economic activities do not fit naturally into the traditional economic categories. Since the modern concept of economic growth was developed in the 1930s, economists have been systematically trained to think of the economy is being divided into two big categories: ‘Goods’ and ‘services’.
Goods are physical commodities, like clothes and steel beams, while services include everything else from healthcare to accounting to haircuts to restaurants. Goods are tangible and can be easily stored for future use, while services are intangible, and cannot be stockpiled for future use. In theory, a statistician could estimate the output of a country by counting the number of cars and the bushels of corns coming out of the country’s factories and farms, and by watching workers in the service sector and counting the number of haircuts performed and the number of meals served.
But data is neither a good or service…