Such announcements are far from unusual for Gou, and often, nothing comes of them. In Vietnam in 2007, in Brazil in 2011, in Pennsylvania in 2013, and in Indonesia in 2014, Foxconn announced enormous factories that either fell far short of promises or never appeared. Just this year, the industries minister of Maharashtra, India, which aggressively pursued one of Gou’s multibillion-dollar projects in 2015, finally confirmed the factory isn’t coming, saying the state had learned a lesson about believing businesses promising big investments. In China, where Foxconn employs the vast majority of its million workers, these sorts of announcements are called “state visit projects,” according to Willy Shih, a Harvard business school professor and former display industry consultant. Officials get a ribbon-cutting photo op, the company gets political goodwill, and everyone understands that the details of the contract are just an opening bid by a company that will ultimately do whatever makes economic sense.
I wish I could explain statistics as clearly as this:
Let’s say we have 100 people who have volunteered for the trials. We’ve divided them into two groups of 50 each. One will be administered the experimental drug, the other a placebo — i.e. something that looks identical, but has no medicinal value at all. There are rules for administering a placebo correctly, and I’ll come to those. For now, let’s assume they have been followed. The trial runs its course. The placebo group reports that one person has recovered, whereas the group that got the actual drug reports that five have recovered. What, if anything, can we conclude? Is this just chance? Is there a real difference between the groups? Is this enough to conclude anything about the efficacy of the drug?
As they got older, the chimps developed more mutual friendships and fewer one-sided friendships. They also exhibited a more positive approach to their whole community, continuing grooming of other chimps, including those that weren’t close friends, at the same rate, but with a drop in aggression. Other primates don’t necessarily follow this pattern as they grow older, according to the authors. Some monkeys tend to withdraw from social relationships and their aggression levels stay high.
Krish Ashok writes a passionate (and erudite, but that’s a given, no?) defence of… maida.
Maida is technically more all-purpose than all-purpose flour because, with a little bit of food science, you can turn this unfairly maligned flour into flaky Malabar parottas, crisp luchis, fluffy naans and kulchas, airy bhaturas, pillowy soft loaves of bread, crunchy-yet-chewy pizzas and delectable cakes without having to buy multiple kinds of flours to do it all.
And while on food, this excellent, entertaining article on custard:
Corn flour comes from pounding the kernel into a white powder that forms a non-Newtonian fluid––a liquid that doesn’t change viscosity under stress––when mixed with water. Its greatest virtue is that it contributes to thickness and volume without tasting like anything. Its use as a food product was patented in Britain in 1854 by a man named John Polson Jr., who began manufacturing it in a factory in Paisley, Scotland owned by his father, John Polson, and his partners William Polson and John Brown. Some of their first advertisements declared that the product “was preferred on account of its plainness.”
When I explain GDP to folks unfamiliar with the concept, I often use the analogy of marks.
“Do you”, I intone in the most professorial voice I can muster, “remember how many marks you scored in your math exam when you were in the 4th grade?”
The point behind asking that question is to help the class realize that there were many other things going on in their life in the 4th grade. The measurement of how well you did on the specific questions you were asked in that test on that day do very little to show you how much math you actually learnt that year. Leave alone, of course, the question of how little the math test had to do with all of what you learnt while you were in the 4th grade.
A similar point was made about GDP recently, in the Business Standard:
Take GDP first. In India, we don’t measure the output of 65 per cent of the economy and make only well-informed guesses about the remaining 35 per cent.
That’s exactly right, of course. You shouldn’t obsess over GDP numbers, much like you shouldn’t obsess over grades. But we do obsess over both!
And the analogy between marks and GDP works really well especially now, because when it comes to GDP, we now have a Sharmaji ka beta in the neighbourhood.
About two years ago, India’s Home Minister Amit Shah spoke of “infiltrators” who were hollowing out the country “like termites”. A Minister from Bangladesh retorted that Shah’s statement was “inappropriate”, “unwanted”, and “not based on information”. The IMF’s recent per capita GDP projections for South Asian countries show that the alleged ‘termite factory’ is shining — Bangladesh, which has been doing better than both India and Pakistan on social and human development indicators for several years now, is also beginning to march ahead on the economic front.
In much the same way that you shouldn’t compare marks obtained by students, you really shouldn’t compare GDP per capita between nations.
But (and you knew there was a but coming along, didn’t you), as I also say in my classes – what else you got, eh? It’s all well and good to say we shouldn’t, but it’s not like we have readymade alternatives. And if you take the GDP factory away from us economists, how do we fill our days?
TCA Srinavasa-Raghavan, in the same column cited above, has three answers:
Only three things: Food inflation, because it has a direct bearing on welfare; foreign exchange reserves, because they serve as a powerful signalling device to foreign investors and sellers of goods; and the revenue deficit. These are the only things the Centre has total control over. In determining all other indicators, the states play a big role.
Read the whole article (which, I’m sorry, may well be behind a paywall). I don’t necessarily agree with all of it, about which more below, but the point that GDP is overrated as a useful barometer for the state of the economy is a point I agree with wholeheartedly.
TCA’s suggestions about what is to be used instead (food inflation, the revenue deficit and forex reserves) are worth considering, but there is a long list of alternatives that have been suggested. Here is just one example:
Provincial officials have long been suspected of overstating growth. Adding their figures together suggests that China’s economy was $364 billion bigger in 2009 than the total in the national accounts. Mr Li preferred to track Liaoning’s economy by looking at other indicators: the cargo volume on the province’s railways, electricity consumption and loans disbursed by banks.
Other folks may come up with other things to use as a proxy for measuring the state of the economy, but really, it is the old story of the six blind men and the elephant all over again. Whatever you use will give you only a limited picture. That’s just the nature of the beast.
Worse! Whatever you agree to measure instead of GDP immediately becomes susceptible to Goodhart’s Law:
In a paper published in 1997, Anthropologist Marilyn Strathern generalized Goodhart’s law beyond statistics and control to evaluation more broadly. The phrase commonly referred to as Goodhart’s law comes from Strathern’s paper, not from any of Goodhart’s writings:
When a measure becomes a target, it ceases to be a good measure.
So sure, you could ask that food inflation, revenue deficits and forex reserves be the target. But it’ll just be cobras or rat tails all over again.
So GDP, whether you like it or not, whether its measurement is favorable or not, is not going to go away anytime soon, whether in India or elsewhere.
Consider the concluding paragraph from a column in the Livemint yesterday by R Jagannathan:
This does not make GDP calculations worthless, but the real focus should be on sectors. More than macroeconomics, sectoral understanding and microeconomics ought to be central to policy-making. Future GDP will best be estimated as a sum of its parts, and not as a whole extrapolated from numbers in the more visible parts of the economy.
The key point made in the book is that entrepreneurship is not – and should not – the responsibility of the private sector. Indeed, it cannot be the responsibility of the private sector.
Early on in the book, she makes the strongest case there is to be made for her thesis, by arguing that the United States of America has known this, and practiced this, for years on end. The rest of the world, she says, would do well to emulate the USA:
If the rest of the world wants to emulate the US model they should do as the United States actually did, not as it says it did: more State not less.
LOCATION: 372 (Note that the location refers throughout to the Kindle version)
I want to focus on three key points in this essay: horizons, incentives and spillovers. Let’s tackle each in turn.
Moonshots is a word that has become increasingly popular over the last two decades, and it refers to projects or even ideas that have a relatively low chance of succeeding. The payoff, if these ideas succeed, is so large that that it may compensate for the relatively low probability of this actually happening. That, of course, is exactly what expectations are all about.
But for a firm, particularly one that may not have the luxury of time and money on its side, placing bets on projects that may not work out – and indeed most of them will not – is a rather risky thing to do. Money is an obvious constraint, but a less obvious one is time.
Firms just do not have the luxury of waiting while a project turns out to be successful… eventually. These kind of moonshots, then, are perhaps best handled, for this specific reason, by the state.
In fact, the point is even more nuanced, because a firm is much more likely to (if at all) invest in a moonshot project based on a specifically desired outcome. The word project itself is an indication of this fact – this is not “blue sky research” that we are talking about.
But blue sky research is important!
A core difference between the US and Europe is the degree to which public R&D spending is for ‘general advancement’ rather than mission-oriented. Market failure theories of R&D are more useful to understand general ‘advancement of knowledge’–type R&D than that which is ‘mission oriented’ (Mazzucato 2015). Mission-oriented R&D investment targets a government agency programme or goal that may be found, for example, in defence, space, agriculture, health, energy or industrial-technology programmes (Mazzucato and Penna 2015).
Governments need to focus, for the sake of their own economies, their domestic firms and their long term growth, on focusing on moonshot projects, precisely because firms are reluctant to do so. The state needs, in other words, to take risks that private firms will not.
Saying this is easy, but how to go about doing this?
That is, if governments need to tackle long-term low-probability-of-success and uncertain-outcome initiatives that are important, but unlikely to be taken up by the private sector, the question that then arises is: how?
Mazzucato offers two points in this regard that I found interesting:
Block (2008, 188) identifies the four key characteristics of the DARPA model:
1. A series of relatively small offices, often staffed with leading scientists and engineers, are given considerable budget autonomy to support promising ideas. These offices are proactive rather than reactive and work to set an agenda for researchers in the field. The goal is to create a scientific community with a presence in universities, the public sector and corporations that focuses on specific technological challenges that have to be overcome.
2. Funding is provided to a mix of university-based researchers, start-up firms, established firms and industry consortia.
3. There is no dividing line between ‘basic research’ and ‘applied research’, since the two are deeply intertwined. Moreover, the DARPA personnel are encouraged to cut off funding to groups that are not making progress and reallocate resources to other groups that have more promise.
4. Since the goal is to produce usable technological advances, the agency’s mandate extends to helping firms get products to the stage of commercial viability. The agency can provide firms with assistance that goes well beyond research funding. Part of the agency’s task is to use its oversight role to link ideas, resources and people in constructive ways across the different research and development sites.
In effect, she is suggesting that government alone cannot do this, it needs to be a “scientific community” that is decentralized, has autonomy, sets the agenda, and applies Darwinian principles (see point 3). Hmm, sounds familiar. Different context, but a similar lesson!
And elsewhere in the book, her example of how Japan did this in the 1970’s is instructive:
The general point can be illustrated by contrasting the experience of Japan in the 1970s and 1980s with that of the Soviet Union (Freeman 1995). The rise of Japan is explained as new knowledge flowing through a more horizontal economic structure consisting of the Ministry of International Trade and Industry (MITI), academia and business R&D. In the 1970s Japan was spending 2.5 percent of its GDP on R&D while the Soviet Union was spending more than 4 per cent. Yet Japan eventually grew much faster than the Soviet Union because R&D funding was spread across a wider variety of economic sectors, not just those focused on the military and space as was the case in the Soviet Union. In Japan, there was a strong integration between R&D, production and technology import activities at the enterprise level, whereas in the Soviet Union there was separation.
Equally important were the lessons learned by Japanese people that went abroad to study Western technologies for their companies, and relationships between those companies and US firms. These companies benefited from the lessons of the US (hidden) ‘Developmental State’, and then transferred that knowledge to Japanese companies which developed internal routines that could produce Western technologies and eventually surpass them.
So, bottom-line: the state has to get in this business, but it can’t “go” it alone. There needs to be a community of academicians, researchers, firms, scholars – and as the example of Japan shows, this community needs fostering, and horizontal collaboration.
Or, if you prefer to put it simply, this is going to be hard.
Academia suffers from the same problem that government bureaucracy does in India: the incentives are all wrong. Both are about risk minimization.
A professor in a college has no incentive to try and do something new, something risky, something innovative. Why, if you think about it, should she? Your best case scenario is that it works, but you get no upside for it: remember, wages aren’t a function of what you do, they are a function of how long you have been in the system. Your worst case scenario is that what you tried to do blows up in your face. So why take the risk?
And it is the same, of course, with a government bureaucrat. And that makes the conclusion of the previous section even more problematic, for where, exactly, are you going to unearth government bureaucrats willing and able to make this happen?
I’m all for the state being more entrepreneurial. I buy into the idea. But I worry, especially in a country like India, about the feasibility of it, for hey, incentives matter!
In a blogpost I had written earlier this year about the budget, I had touched upon this point:
Here is Ninan’s solution:
“Is there a solution? Yes, railway engineers of old like the metro builder E Sreedharan, builders of government companies like D V Kapur and V Krishnamurthy, and agricultural scientists like M S Swaminathan have shown how they made a difference when given a free hand. Vineet Nayyar as head of Gas Authority of India was able to build a massive gas pipeline within cost and deadline in the 1980s. The officers who are in charge of Swachh Bharat and Ayushman Bharat, and the one who has cleaned up Indore, are others who, while they may not match China’s speed, can deliver. Perhaps all we have to do is to spot more like them and give them a free hand.”
But as any experienced HR professional will tell you, spotting them is very difficult, even in the corporate world. And as any corporate CEO will tell you, giving these talented folks a free hand is even more difficult. And as any student of government bureaucracy will tell you, achieving the intersection set of these two things in a governmental setup is all but impossible.
And so what we need to study and copy from China is not so much anything else, but lessons in achieving, and sustaining, excellence in government bureaucracy. Or, if you prefer, how to improve state capacity.
In short, quality of government, not size of government, is what matters for freedom and prosperity.
That point resonates even more in this context: fostering an ecosystem led by the government is dead in the water without either the proper incentives, or at least bureaucrats who are able to work through poorly designed incentives. It is a hard problem, state led entrepreneurship, and made harder by the problem of incentives.
Or externalities, if you prefer. It doesn’t matter how hard the problem is, the payoffs are worth it!
Ruttan (2006) argues that large-scale and long-term government investment has been the engine behind almost every GPT (general purpose technology) in the last century. He analysed the development of six different technology complexes (the US ‘mass production’ system, aviation technologies, space technologies, information technology, Internet technologies and nuclear power) and concluded that government investments have been important in bringing these new technologies into being.
(Note: emphasis added)
If those GPT’s are the outcome of general, as opposed to specific, R&D, sign me up. They are magnificent positive externalities. Indeed, elsewhere in the book, Mazzucato points to how almost everything produced by Apple today simply could not have been produced without an entrepreneurial state:
The final point that I’ll make relates to how Mazzucato proposes “capturing” some of these externalities:
Where an applied technological breakthrough is directly financed by the government , the government should in return be able to extract a royalty from its application . Returns from the royalties , earned across sectors and technologies , should be paid into a national ‘ innovation fund ’ which the government can use to fund future innovations . Granting a return to the State should not prohibit the dissemination of new technology throughout the economy , or disincentivize innovators from taking on their share of the risk . Instead it makes the policy of spending taxpayers ’ money to catalyse radical innovations more sustainable , by enabling part of the financial gains from so doing to be recycled directly back into the programme over time .
Mazzucato does present alternative schemes to the one shown above, but this is the one that strikes me as being the one with the most promise, if administered well, with appropriate risk-mitigation built in. But again, saying that is much easier than actually getting it done.
But all the being said, one simple fact is inescapable: India needs to be thinking about how to get something like this off the ground, and ASAP.
For that reason alone, more of us should be reading this book.
First, what is Palantir Technologies? Here’s Wikipedia – note that I have combined sentences across different paragraphs in this excerpt:
Palantir Technologies is a public American software company that specializes in big data analytics. Headquartered in Denver, Colorado, it was founded by Peter Thiel, Nathan Gettings, Joe Lonsdale, Stephen Cohen, and Alex Karp.
The company is known for three projects in particular: Palantir Gotham, Palantir Metropolis and Palantir Foundry. Palantir Gotham is used by counter-terrorism analysts at offices in the United States Intelligence Community (USIC) and United States Department of Defense…
…Palantir Metropolis is used by hedge funds, banks, and financial services firms…
…Palantir Foundry is used by corporate clients such as Morgan Stanley, Merck KGaA, Airbus, and Fiat Chrysler Automobiles NV
Its two primary software programs, Gotham and Foundry, gather and process vast quantities of data in order to identify connections, patterns and trends that might elude human analysts. The stated goal of all this “data integration” is to help organizations make better decisions, and many of Palantir’s customers consider its technology to be transformative.
But the story gets more interesting in the very next line in the article…
Karp claims a loftier ambition, however. “We built our company to support the West,” he says. To that end, Palantir says it does not do business in countries that it considers adversarial to the U.S. and its allies, namely China and Russia. In the company’s early days, Palantir employees, invoking Tolkien, described their mission as “saving the shire.”
There’s two questions at play here, really. First, what does Palantir Technologies do (that’s the first excerpt from the NYT story)? And second, why does it do what it does (and that’s the excerpt right above)?
Now, the reason I find this so interesting is that the instinctive argument that you might want to make against Palantir Technologies is “but privacy!”. And the second excerpt above is, in a sense, Palantir’s response.
Although Palantir claims it does not store or sell client data and has incorporated into its software what it insists are robust privacy controls, those who worry about the sanctity of personal information see Palantir as a particularly malignant avatar of the Big Data revolution. Karp himself doesn’t deny the risk. “Every technology is dangerous,” he says, “including ours.”
Technology is technology – what you do with it is what matters is a rather old argument, but that’s the argument that is being used here. There’s more though – if we don’t, somebody else will. Better the known devil, etc.
Once the data has been integrated, it can be presented in the form of tables, graphs, timelines, heat maps, artificial-intelligence models, histograms, spider diagrams and geospatial analysis. It is a digital panopticon, and having sat through several Palantir demos, I can report that the interface is impressive — the search results are strikingly elegant and easy to understand.
Elsewhere in the article, the author speaks about how the work isn’t glamorous, and is really just glorified plumbing. Well, maybe – but as anybody who has lived in a house will tell you, it is plenty important. Good plumbing is plumbing you don’t notice, but reap the benefits of – and that seems to be Palantir’s USP.
While Thiel provided most of the early money, the start-up secured an estimated $2 million from In-Q-Tel, a venture-capital firm that finances the development of technologies that can help the C.I.A. Karp says the real value of the In-Q-Tel investment was that it gave Palantir access to the C.I.A. analysts who were its intended clients.
Did In-Q-Tel pay to help start Palantir, or did it hire consultants for 2 million dollars? Did Palantir agree to work for only 2 million dollars to get access to the CIA?
Bottom-line: the world is a non-zero sum game.
According to Thiel, their conversations generally took place late at night in the law-school dorm. “It sounds too self-aggrandizing, but I think we were both genuinely interested in ideas,” he says. “He was more the socialist, I was more the capitalist. He was always talking about Marxist theories of alienated labor and how this was true of all the people around us.”
This excerpt is from a section which is about Karp figuring out his education and career, and we learn about his Jewish, rebellious background as well. I found this clip interesting because from Peter Thiel’s viewpoint, succeeding in selling the idea behind Palantir to Karp is one of the biggest validations there could possibly be. If he bought into the story, well, there must be something to it. Second, what better way to maintain checks and balances than to have somebody like Karp running the show?
In fact, Thiel hiring Karp for this job becomes more and more interesting the more you learn about Karp. Thiel has a quote in the article about needing someone who was smart and scrappy, but left unsaid, perhaps, is someone who was very unlike Thiel. And not just unlike Thiel, also unlike the typical CEO. A person who worries about the alienation of labor, likes solitary pursuits, and dreams of being an intellectual in Europe isn’t the person you would have in mind as the typical CEO of a firm like Palantir. But that, it would seem, was the whole point. Well, that, and being a bachelor by choice wouldn’t hurt, given the traveling nature of the job.
(Although there is a section in the article in which Karp insists that he being who he is hasn’t helped him or Palantir.)
Karp and Thiel say they had two overarching ambitions for Palantir early on. The first was to make software that could help keep the country safe from terrorism. The second was to prove that there was a technological solution to the challenge of balancing public safety and civil liberties — a “Hegelian” aspiration, as Karp puts it.
Karp and Thiel make for a Hegelian pair themselves!
When I asked Thiel about the risk of abuse with Palantir, he answered by referring to the company’s literary roots. “The Palantir device in the Tolkien books was a very ambiguous device in some ways,” he said. “There were a lot of people who looked into it and saw more than they should see, and things went badly wrong when they did.” But that didn’t mean the Palantir itself was flawed
He continued: “The plot action was driven by the Palantir being used for good, not for evil. This reflected Tolkien’s cosmology that something that was made by the good elves would ultimately be used for good.”
A moment later, he added: “That’s roughly how I see it, that it is ultimately good and still very dangerous. In some ways, I think that was reflected in the choice of the name.”
I found this fascinating, and I also found it useful to think about this from the Wikipedia article about the original Palantir:
A major theme of palantír usage is that while the stones show real objects or events, they are an unreliable guide to action, and it is often unclear whether events are past or future: what is not shown may be more important than what is selectively presented. Further, users with sufficient power can choose what to show and what to conceal
The technology is what it is – and as Karp himself points out, it is susceptible to misuse. More importantly, the technology in combination with the person(s) who are using it is, at least potentially, an even more dangerous tool.
Karp made clear that he was opposed to Trump’s immigration policies: “There are lots of reasons I don’t support the president; this is actually also one of them.” He told me that he was “personally very OK with changing the demographics of our country” but that a secure border was something that progressives should embrace. “I’ve been a progressive my whole life,” he said. “My family’s progressive, and we were never in favor of open borders.” He said borders “ensure that wages increase. It’s a progressive position.” When the left refuses to seriously address border security and immigration, he said, the right inevitably wins. To the extent that Palantir was helping to preserve public order, it was “empirically keeping the West more center-left.”
To understand a big data firm started by one the world’s most successful VC’s, one should end up reading about a German philosopher from the 18th century – for what could possibly more Hegelian than that excerpt?
And finally, the last sentence in the article:
“Palantir,” he said, “is the convergence of software and difficult positions.”
A student messaged last week, asking some questions about inflation and its measurement in India. In particular, they wanted to know about food and its impact on inflation right now.
Well, outsourcing is always and everywhere a good idea, and Vivek Kaul had already answered the question at great length:
What this means is that, despite the end consumers of food paying a higher price, the farmers are largely not benefitting from this rise in food prices, given that they sell their produce at the wholesale level. This difference can be because of a few reasons.
a) A collapse in supply chains has led to what is being sold at the wholesale level not reaching the consumers at the retail level, thus, leading to higher prices for the consumer.
b) This could also mean those running the supply chains hoarding stuff, in order to increase their profit.
Having said that, the former reason makes more sense given that stuff like vegetables, egg, fish and meat, etc., cannot really be hoarded. Also, hoarding stuff like pulses, needs a specialized storage environment which India largely lacks.
The entire article is worth reading (and so is subscribing to Vivek’s blog, so please do so!). And if you think 2020 isn’t depressing enough already, do read this article, also written by him. A short excerpt follows:
To conclude, the Indian economy will contract during the second half of the financial year. There is a slim chance of growth being flat for the period January to March 2021. Inflation, even though it might come down a little, is likely to remain high due to the spread of the covid pandemic. Hence, India will see conflation through 2020-21.
From a reading-the-tea-leaves perspective, it would seem the RBI actually isn’t that worried about inflation right now (and rightly so!). Here’s an excerpt from an excellent newsletter, Anticipating the Unanticipated that makes this point:
But the RBI wants to signal it is willing to live with inflation running above ‘comfortable’ level in the coming days. The MPC report last week claimed almost 80 per cent of the increase in inflation beyond the 4 per cent target can be attributed to supply chain disruptions and increase in fuel prices. This it believes is a short-term phenomenon and inflation will be in the 5 per cent range next year. This is underlined to give comfort to bond investors to buy government securities without the fear of a near-term interest rate hike to contain inflation. Further, the other step announced by RBI in extending the HTM (hold-to-maturity) limits by another year to March 2022 is to protect any bondholder from the volatility of prices and booking losses on account of it. The overall RBI signal is it doesn’t want the worry of rising inflation and a consequent rate increase to come in the way of growth. It’s focus now is on improving the transmission of rate cuts to the borrowers to stimulate growth.
… and here is Anantha Nageswaran making the same point, but by utilizing a different analysis:
This exercise generates the hypothesis that there is little or no intersection of the household inflation expectations formation and the monetary policy regime. Two, high inflation expectations peaked in September 2014. Similarly, the current high inflation expectations should peak as supply disruptions ease. So, in my view, RBI is betting correctly that the rate of inflation would ease and project policy on hold for the next few quarters. Three, inflation generation process should matter only to the extent that it affects medium-term output and employment generation. For now, other indicators suggest that it is not as disruptive as it was in 2011-13. Therefore, there is no need to turn it into a fetish. The new MPC and the central bank have done well and done good. They should be pleased.
And for the data nerds among you, here is the Inflation Expectations Survey of Households by the RBI (do keep in mind the point Ananta Nageswaran makes about trimmed means in his article). Note that currently at least, not too many people seem to be too worried about persistently high food inflation.
Side note: Jason Furman’s podcast with Tyler Cowen contained this interesting snippet:
FURMAN: GDP could be more meaningful if we measured it better. The inflation rate gets harder and harder to measure over time. So I think the one that probably has deteriorated in meaningfulness is the measure of inflation. Number one, we don’t measure it well, and number two, it’s low enough that it’s hard to get that excited about it.
COWEN: Is that a quality-of-goods problem? Or how we do chaining over time? Where are we going wrong in measuring inflation?
FURMAN: Just more and more of the economy is in areas that are harder to measure the quality of, healthcare being the most notorious.
I’m sure I must have linked to this before, and shame on me if I haven’t – but I did just finish teaching game theory in my principles of economics class at the Gokhale Institute – plus, who can resist watching this again, eh?
Human evolution produced gossip. Cultural anthropology sees gossip as an informal way of enforcing group norms. It is effective in small groups. But gossip is not the search for truth. It is a search for approval by attacking the perceived flaws of others.
Arnold Kling writes an excellent essay about gossip and (as he puts it), the ISS. That, to be clear, stands for Internet, Smart Phones and Social Media. Excellent essay, well worth your time.
Low level of CRAR not only hampers bank health but also restricts smooth transmission of monetary policy. Injection of capital by the Government of India in public sector banks is likely to increase the credit flow to the real sector and help in smoother transmission of monetary policy.
How much of this paper is signaling/laying the groundwork, and how much of it is a genuine addition to what we already know about monetary policy? The link comes via Amol Agarwal
This is exactly why I am so pleased to see how narrowly focused the Justice Department’s lawsuit is: instead of trying to argue that Google should not make search results better, the Justice Department is arguing that Google, given its inherent advantages as a monopoly, should have to win on the merits of its product, not the inevitably larger size of its revenue share agreements. In other words, Google can enjoy the natural fruits of being an Aggregator, it just can’t use artificial means — in this case contracts — to extend that inherent advantage.
The concluding paragraph from this blog post by Ben Thompson is even better, and I was tempted to go with it, but this works too! Please read the whole thing – excellent writing, as always.
If you’re looking to get an iPad right now and can afford it, the new $599 iPad Air is the best tablet for most people. Apple has taken the design from the more expensive iPad Pro and brought it down to a more reasonable price point. It’s $100 more than it was last year, but in return this year’s iPad Air has a bigger, better screen and a faster (and very intriguing) processor.
Dieter Bohn’s review of the iPad Air (2020). If I could, I would!
Miniature paintings are among the most beautiful, most technically-advanced and most sophisticated art forms in Indian culture. Though compact (about the same size as a small book), they typically tackle profound themes such as love, power and faith. Using technologies like machine learning, augmented reality and high-definition robotic cameras, Google Arts & Culture has partnered with the National Museum in New Delhi to showcase these special works of art in a magical new way.
It is such a pleasure to begin a blog post on such a happy, warm and fuzzy note in 2020 – and what’s rarer is that the note is courtesy Twitter!
Milgrom and Wilson aren’t exactly household names in India – or at any rate, weren’t household names until yesterday. In fact, even within economics departments, they are unlikely to have been names that absolutely everybody is familiar with. This blog post is as much a celebration of they having won the Nobel Prize for Economics as it is an opportunity for me to learn more about their work.
But let’s begin by allowing Twitter to return to type, as it were:
So what gives? Why such a curmudgeonly response to the highest prize that one can receive as an economist?
Twitter being what it is, Branko Milanovic was eventually goaded into answering this question himself (link here), but his response – to me! – boils down to “Pah! There are other, more important problems to think about.”
Well, maybe. But if you ask me, Milgrom and Wilson’s work is plenty important in its own right.
Let’s find out why!
Every day, auctions distribute astronomical values between buyers and sellers. This year’s Laureates, Paul Milgrom and Robert Wilson, have improved auction theory and invented new auction formats, benefitting sellers, buyers and taxpayers around the world.
How do we decide who gets what? Should this be decided by governments without the use of markets, or should this be completely random? Should bidding wars (that is, auctions) be deployed, and if so, what might be the implications?
It is for their attempts at answering that last question, for the most part, that Milgrom and Wilson have been awarded this year’s Nobel Prize in Economics.
How did they go about answering this question? Here’s Timothy Taylor with one answer:
A useful starting point is to recognize that auctions can have a wide array of formats. Most people are used to the idea of an auction where an auctioneer presides over a room of people who call out bids, until no one is willing to call out a higher bid. But auctions don’t need to work in that way.
An “English auction” is one where the bids are ascending, until a highest bid is reached. A “Dutch auction”–which is commonly used to sell about 20 million fresh flowers per day–starts with a high bid and then declines, so that the first person to speak up wins. In an open-outcry auction, the bid are heard by everyone, but in a sealed-bid auction, the bids are private. Some auctions have only one round of bidding; others may eliminate some bidders after one round but proceed through multiple rounds. In “first-price” auctions, the winner pays what they bid; in “second-price” auctions, the winner instead pays whatever was bi by the runner up.
In some auctions the value of what is being bid on is mostly a “private value” to the bidders (the Nobel committee suggests thinking about bidding on dinner with a Nobel economist as an example, but you may prefer to substitute a celebrity of your choice), but in other cases, like bidding on an offshore oil lease, the value of the object is at least to some extent a “common value,” because any oil that is found will be sold at the global market price. In some auctions, the bidders may have detailed private information about what is being sold (say, in the case where a house is being sold but you are allowed to do your own inspection before bidding), while in other auctions the information about the object being auctioned may be mostly public.
In short, there is no single perfect auction. Instead, thinking about how auctions work means considering for any specific context how auction rules and format in that situation, given what determines the value of the auctioned objects and what what kind of information and uncertainty bidders might have.
The excellent, excellent blog A Fine Theorem ends up responding (unintentionally, to be clear) to Branko Milanovic while speaking about Milgrom and Wilson’s body of work:
When it comes to practical application, Milgrom’s work on auctions is well-known, and formed the basis of his Nobel citation. How did auctions become so “practical”? There is no question that the rise of applied auction theory, with the economist as designer, has its roots in the privatization wave of the 1990s that followed the end of the Cold War. Governments held valuable assets: water rights, resource tracts, spectrum that was proving important for new technologies like the cell phone. Who was to be given these assets, and at what price? Milgrom’s 1995 Churchill lectures formed the basis for a book, “Putting Auction Theory to Work”, which is now essential reading alongside Klemperer’s “Theory and Practice”, for theorists and practitioners alike. Where it is unique is in its focus on the practical details of running auctions.
In other words, applied auction theory helps us, as a society, decide who gets what, and on what basis. Especially with the end of the Cold War, and with the wave of liberalization and privatization that followed in many major economies the world over, applied auction theory became especially important!
Timothy Taylor again:
One useful property of auctions is that in a number of settings they can discipline the public sector to make decisions based on economic values, rather than favoritism. For example, when a city wants to sign a contract with a company that will pick up the garbage from households, companies can submit bids–rather than having a city council choose the company run by someone’s favorite uncle. When the US government wants to give companies the right to drill in certain areas for offshore oil, or wishes to allocate radio spectrum for use by phone companies, it can auction off the rights rather than handing them out to whatever company has the best behind-the-scenes lobbyists. In many countries, auctions are used to privatize selling off a formerly government-owned company.
By the way, this post – or indeed the blog posts that I have referred to so far – aren’t really indicative of just how complex this field has become today! For example, take a look at this video to understand how modern auction design is the combination of cutting edge computer science, operations research and economic theory at the same time (h/t Alex Tabarrok on MR)
MR’s other blogger, Tyler Cowen’s posts on both winners are also worth reading: here is the post on Milgrom, and here is the post on Wilson. Like the post on A Fine Theorem, both posts contain much more information about both authors than just the body of work that won them the Nobel.
For example, the story of Milgrom courting his wife:
And before I forget, also read about the “no-trade” theorem and the bid-ask spread paper – not to mention the “Chain Store” paradox and the “Gang of Four” papers. Tyler Cowen’s post, and A Fine Theorem’s post have fine summaries of all of them.
In line with Tyler Cowen’s post about Milgrom, his post about Wilson contains much more information about Wilson’s work outside of auction theory. The entire post is worth bookmarking for the treasure trove of links contained therein, but in particular, the following are particularly interesting to me:
Speaking of Roth (himself a Nobel Prize winner, of course), here is his blogpost about the prize – as he says, 2024’s Nobel Prize is something we should keep an eye out for!
Joshua Gans, another student of Paul Milgrom, also has a blog post on the winners, with a rather neat explanation of why Milgrom’s Wikipedia page is so lengthy:
For that conference, the attendees all contributed to complete Paul’s wikipedia page. The idea was to make sure that everything was there specifically for today. I had a goal of making it the longest page of any living economist. We overshot and it is the longest page of any economist! His contributions were so voluminous, it wasn’t hard to get to that point.
Trillion Dollar Economists, by Robert Litan (h/t Arnold Kling)
And of course, everything else I have linked to already!
And finally, just to round off the whole thing, why not end with a tweet, since we started with one? Explaining stuff as simply as possible is one of my life goals, and I wish my game was half as good as this tweet: