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awesome autodidacts!

'How do you stay focused, motivated and maintain enthusiasm when things don't go the way you had hoped?

I think my drive to get it done is somewhat disconnected from hope, enthusiasm or anything else. I just don't care about hope, enthusiasm, motivation I just give it everything I've got irrespective of what the circumstances may be. You just keep going and get it done.'

'You are a rocket scientist but how did you actually learn to build rockets?

'This may sound silly, but I read books and talked to people, I mean that's kind of how you learn anything. There's lots of great books out there and there's lots of smart people... If you just talk to people you can learn a tremendous amount. And then as you iterate through problems you can learn a tremendous amount. It's kinda like almost anything, when you struggle with a problem that's when you understand it. So when you've done that for 11 years in the case of Space X and 10 years in the case of Tesla then you have a pretty good grasp of it. In fact that's one of the ways when you interview someone when they want to work at the company, to ask them tell me about the problems that you worked on. And how they solved them. And if the person that's answering is really the person that solved it they'll be able to answer at multiple levels and be able to go down to the brass tacks. And if they weren't they'll get stuck. And then you can say oh this person was not really the person that solved it because anyone who struggled hard with a problem never forgets it.'

u/aerovistae - tl;dr: How do you learn so much so fast? Lots of people read books and talk to smart people, but you've taken it to a whole new level. It seems like you have an extremely proficient understanding of aerospace engineering, mechanical engineering, electrical engineering, software engineering, all various subdisciplines (avionics, power electronics, structural engineering, propulsion, energy storage, AI) ETC ETC nearly all things technical. I know you've read a lot of books and you hire a lot of smart people and soak up what they know but you have to acknowledge you seem to have found a way to pack more knowledge into your head than nearly anyone else alive. Do you have any advice on learning? How are you so good at it?

u/ElonMuskOfficial - I do kinda feel like my head is full!! My context switching penalty is high and my process isolation is not what it used to be. Frankly, though, I think most people can learn a lot more than they think they can. They sell themselves short without trying. One bit of advice: it is important to view knowledge as sort of a semantic tree -- make sure you understand the fundamental principles ie the trunk and big branches, before you get into the leaves/details or there is nothing for them to hang on to.

Jim Cantrell on Elon 'Once he has a goal, his next step is to learn as much about the topic at hand as possible from as many sources as possible. He is by far the single smartest person that I have ever worked with... period. I can't estimate his IQ but he is very very intelligent. And not the typical egg head kind of smart. He has a real applied mind. He literally sucks the knowledge and experience out of people that he is around. He borrowed all my college texts on rocket propulsion when we first started working together in 2001. 

"I'd never seen anything like it," an employee said. "He was the quickest learner I've ever come across. You had this guy who knew everything from a business point of view, but who was also clearly capable of knowing everything from a technical point of view – and the place he was creating was a blank sheet of paper."

At SpaceX, he had to pick things up on the job. Musk initially relied on textbooks to form the bulk of his rocketry knowledge. But as SpaceX hired one brilliant person after another, Musk realized he could tap into their stores of knowledge. He would trap an engineer in the SpaceX factory and set to work grilling him about a type of valve or specialized material. “I thought at first that he was challenging me to see if I knew my stuff,” said Kevin Brogan, one of the early engineers. “Then I realized he was trying to learn things. He would quiz you until he learned ninety percent of what you know.”

"Work like hell. I mean you just have to put in 80 to 100 hour weeks every week. [This] improves the odds of success. If other people are putting in 40 hour work weeks and you’re putting in 100 hour work weeks, then even if you’re doing the same thing you know that… you will achieve in 4 months what it takes them a year to achieve"

"Constantly seek criticism. A well thought out critique of whatever you are doing is as valuable as gold, and you should seek that from everyone you can, but particularly your friends. Usually your friends know what is wrong but they don't want to tell you because they don't want to hurt you. Yeah I want to encourage my friend so I don't want to tell him what I think is wrong with his product. It doesn't mean your friends are right, but very often they are right. And you at least what to listen very carefully to what they say and to everyone. You should take the approach that you are wrong. That you the entrepreneur are wrong. Your goal is to be less 

'But you know if you read books and talk to experts, you can pick it up pretty quickly. In fact, I think people self-limit their ability to learn. It's really pretty straightforward. Just read books and talk to people. Particularly books. The data rate of reading is much greater than when somebody's talking. I mean, what's the output rate of speech? It's like a couple hundred bits per second, maybe a few thousand bits per second, if you're really going full tilt. You can do several times that reading. The main reason I didn't go to lectures in college was because the data rate was too slow. Why are they reading the textbook to me? This is like a bedtime story or something? Ridiculous.

Sergeev: He always picked books to read himself. He looked through and read a huge amount of literature. I never counted exactly how many, but I always seen him reading and writing from dawn to dusk. He would be brought new documents and old ones would be taken away. There was a Commissar of the Artillery Command - Georgi' Savchenko, who even knew Stalins parents, and knew Stalin himself very well. He wrote that Stalin read 500 pages a day. I think that's true.

He always read books with a pencil in his hand, marking something. The majority of his books were philosophical works and our classics. He liked Gogol', Salti'kov-Shedrin, Tolstoy, Leskov, had works of Esenin, Mayakovsky, Pasternak, Bulgakov. In fact Stalin payed special attention to education of Russian language and literature. Knowing who we want to be when we grow up he asked us: "So you will be in the military. And what is the most important subject for a soldier?" We began naming diffrent subjects: mathematics, physics, fitness training. And he told us: "No. Russian Language and Literature. You have to speak so that everyone could understand you and in extreme battle conditions you have to speak brief. And you too have to understand what you are being told. A military must be able to express himself both verbally and in writing. In war you will face such situations, which you have never faced before. You will have to make decisions. And if you read a lot, then in your memory you will find a hint how to act and what to do. Literature will help you."

In my whole life, I have known no wise people who didn’t read all the time — none, zero.

You’re hooked to lifetime learning. And without lifetime learning you people are not going to do very well. You are not going to get very far in life based upon what you already know. You are going to advance in life by what you learn after you leave here. If you take Berkshire Hathaway which is one of the most respected corporations in the world and it may have the best, long-term investment record in the entire history of civilization. The skill that got Berkshire through one decade would not have sufficed to get it through the next decade with the achievements made. Without Warren Buffett being a learning machine, a continuous learning machine the record would have been absolutely impossible. The same is true in lower walks of life. I constantly see people rise in life who are not the smartest, sometimes not even the most diligent but they are learning machines. They go to bed a little wiser then when they got up. And boy does that habit help particularly when you have a long run ahead of you.

‘Learning all the big ideas in all the big disciplines so I wouldn't be a perfect damn fool who was trying to think about one aspect of something that couldn't be removed from the totality of the situation in a constructive fashion. And what I noted as the really big ideas carry 95% of the freight it wasn't at all hard for me to pick up all the big ideas in all the disciplines and to make them a standard part of my mental routines. Once you have the ideas of course they're no good if you don't practice, if you don't practice you lose it. So I went through life constantly practicing this multi-disciplinary approach. Well I can't tell you what that's done for me. It's made life more fun, it's made me more constructive, it's made me more helpful to others, it's made me more enormously rich. You name it that attitude really helps... And by the way when I talk about this multi-disciplinary attitude I'm really following a very key idea of the greatest lawyer of antiquity, Marcus Tullus Cicero. And Cicero is famous for saying 'a man who doesn't know what happened before he was born goes through life like a child.' Well that is a very correct idea of Cicero's and he's right to ridicule somebody so foolish as to not know what happened before he was born. But if you generalise Cicero as I think one should there are all these other things that I think you should know in addition to history. And those other things are all the big ideas in all the other disciplines. And it doesn't help you just to know them enough just so you can prattle them in an exam and get an A. You have to learn these things in such a way that they're in a mental lattice work and you automatically use them for the rest of your life.

When I want to read something I tune everything else down. I don’t know a wise person who doesn’t read a lot. I think that people who multitask pay a huge price –they can’t think of anything deeply, giving the world an advantage, which they shouldn’t give. I wouldn’t succeed doing it. I did not succeed in life by intelligence –I succeeded because I have a long attention span.

'You gotta remember that it's not real brilliance. In other words, you talk about prodigy, what it takes to extend the boundaries of physics, neither of has that. We have learned how to out perform people who are a lot smarter. (Buffett: 'Yeah we can't play top notch chess') 'No we can't. But the other great secret, is we're good at life long learning. Warren is so much better in his 70s and 80s than when he was younger that it is almost awesome. If you keep learning all the time you have a huge advantage. And we both just like it.' (Buffett: 'And we have a wonderful group of friends'.) 'From whom we can l

Nothing has served me better in my long life than continuous learning. And if you take Warren Buffett, if you watched him with a time clock I would say half of all the time that he spends is just sitting on his ass and reading. And a big chunk of the rest of the time is spent talking one on one, either on the telephone or personally with highly gifted people who he trusts and they trust him

“I insist on a lot of time being spent, almost every day, to just sit and think. That is very uncommon in American business. I read and think. So I do more reading and thinking, and make less impulse decisions than most people in business. I do it because I like this kind of life.”

'Read 500 pages like this every day. That's how knowledge works. It builds up, like compound interest. All of you can do it, but I guarantee that not many of you will do it.'

'I should mention one thing about reading. It was the library here at Columbia, where I probably spent more time than any other student. I lived there practically. But I pulled a book out there, it happened to be Who's Who in America and it told me something about my Professor Benjamin Graham. And then I went to the library, and I said I want to learn more about this because I learned this over here. That changed my whole life. We own Geico now because of that librarian directing me to some other book, and following through on that. I read about one fifth the path that Bill does, but I still spend five or six hours a day reading. You can learn so much. I particularly love biographies. To be able to live the lives of this people who are so extraordinary, and the lessons, the discouragements they faced, just everything about it.  You can't get enough of reading.'

In the winter of 1896 as he approached his 22nd birthday he resolved to read history, philosophy, economics and things like that and I wrote to my mother for such books as I had heard of on such topics. He began with Gibbons eight volume Decline and Fall of the Roman Empire... All through the glistening middle hours of the Indian day when we had quitted stables until the evening shadows proclaimed the hour of polo I devoured Gibbon. I rode triumphantly through it and enjoyed it all. I scribbled all my opinions on the margins of the pages. On January 14th 1897 we find him writing Jenny. 'The eight volume of Gibbon is still unread because I've been lured by Winwood Reed's the Martyrdom of Man and a fine translation of the Republic of Plato. Both of which are fascinating. Then remembering Womb's brother-in-law by the fire at Bentnoor he tackled 12 volumes of Macaulay. On March the 17th he wrote I've completed Macaulay's history and very nearly finished his essays... He was covering 50 pages of Macaulay and 25 of Gibbon everyday, there are only a 100 of the latter's 4000-odd left now. The scope of his explorations was broadening. I read 3 or 4 books at a time to avoid tedium and he was pouring over Schopenhauer, Malthus, Darwin, Aristotle (on politics only), Henry Faucett's Political Economy, William Lecky's European Morals and Rise of Influence of Rationalisim, Pascal's Provincial Letters, Adam Smith's Wealth of Nations, Bartylett's 'Familiar quotations', Lang's Modern Science and Modern Thought, Victor Henry Rocheford's Memoirs, The Memoirs of the Duc de San Simon and Henry Hallam's Constitutional History. Incredibly he asked his mother to send him all 100 volumes of the annual register, the record of British Public events founded by Birk. He explained that he wanted to know the detailed parliamentary history: debates, divisions, parties, cliques and caves of the last 100 years... In using them he first set down his opinion an issue and then studied the debate. By this practice he hoped to build up a scaffolding of logical and consistent views which will perhaps tend to the creation of a logical and consistent mind. Of course the Annual Register is valuable only in its facts. A good knowledge of this will arm me with a sharp sword. Macaulay, Gibbon, Plato etc must train the muscles to wield that sword to the greatest effect. 

“Some advise exercise, and others, repose. Some counsel travel, and others, retreat. Some praise solitude, and others, gaiety. No doubt all these may play their part according to the individual temperament. But the element which is constant and common in all of them is Change. Change is the master key. A man can wear out a particular part of his mind by continually using it and tiring it, just in the same way he can wear out the elbows of his coat. There is, however, this difference between the living cells of the brain and inanimate articles:… the tired parts of the mind can be rested and strengthened, not merely by rest, but by using other parts. It is not enough merely to switch off the lights which play upon the main and ordinary field of interest; a new field of interest must be illuminated. It is no use saying to the tired ‘mental muscles’… ‘I will lie down and think of nothing.’ The mind keeps busy just the same. If it has been weighing and measuring, it goes on weighing and measuring. If it has been worrying, it goes on worrying. It is only when new cells are called into activity, when new starts become the lord of the ascendant, that relief, repose, refreshment are afforded.'

'Why then did he go? The simplest answer seems the best. He went because of his desire to learn. The visit to western Europe was the final stage of Peter's education. The culmination of all he had learned from foreigners since boyhood. They had taught him all that they could in Russia but there was more and LeForte was constantly urging him to go. Peter's overriding interest was on in ships for his embryo navy and he was well aware that in Holland and England was the greatest shipbuilders in the world. He wanted to go to those countries where dockyards turned out the prominent navies and merchant fleets of the world and to Venice which was supreme in the building of multi-oared galleys used in inland seas. The best authority on his motive is Peter himself. Before his departure he had a seal engraved for himself which bore the inscription 'I am a pupil and need to be taught.'

Michael Specter, a New Yorker writer who profiled Gates for the magazine, has said that the Microsoft founder 'is one of these autodidacts who reads, reads, reads. He reads hundreds of books about immunology and biochemistry and biology, and asks a lot of questions, and because he's Bill gates he can get to talk to whoever he wants.'

'This is one of the things I love about reading. Each book opens up new avenues of knowledge to explore... These days, I also get to visit interesting places, meet with scientists, and watch a lot of lectures online. But reading is still the main way that I both learn new things and test my understanding. For example, this year I enjoyed Richard Dawkin's 'The Magic of Reality', which explains various scientific ideas and is aimed at teenagers. Although I already understood all the concepts, Dawkins helped me think about the topics in new ways. If you can't explain something simply, you don't really understand it. 

'I really had a lot of dreams when I was a kid. And I think a great deal of that grew out of the fact that I had a chance to read a lot.'

'Whether I'm at the office, at home, or on the road, I always have a stack of books I'm looking forward to reading.'

'I try to make time fore reading each night. In addition to the usual newspapers and magazines, I make it a priority to read at least one newsweekly from cover to cover. If I were to read what intrigues me - say the science and business sections - then I would finish the magazine the same person I was when I started. So I read it all.'


By late May 1788 Napoleon was stationed at the School of Artillery at Auxonne in eastern France, not far from Dijon. Here, as when he was stationed with his regiment at Valence, he ate only once a day, at 3pm, thereby saving enough money from his officer's salary to send some home to his mother; the rest he spent on books. he changed his clothes once every eight days. He was determined to continue his exhaustive autodidactic reading programme and his voluminous notebooks from Auxonne are full of the history, geography, religion and customs of all the most prominent peoples of the ancient world, including the Athenians, Spartans, Persians, Egyptians and Carthaginians. They cover modern artillery improvements and regimental discipline, but also mention Plato's Republic, Achilles and (inevitably) Alexander the Great and Julius Caesar.

'Do you know how I managed?'Napoleon later recalled of this period of his life. 'By never entering a cafe or going into society; by eating dry bread, and brushing my own clothes so that they might last the longer. I lived like a bear, in a little room, with books for my only friends... These were the joys and debaucharies of my youth'. He might have been exaggerating slightly, but not much. There was nothing he valued so much as books and a good education.

'In the nine days between receiving the appointment and leaving for his headquarters in Nice on March 11, Napoleon asked for every book, map and atlas on Italy that the war ministry could provide. He read biographies of commanders who had fought there and had the courage to admit his ignorance when he didn't know something. 'I happened to be at the office of the General Staff in the rue Neuve des Capucines when General Bonaparte came in,' recalled a fellow officer years later: '...Flinging his hat on a large table in the middle of the room, he went up to an old general named Krieg, a man with a wonderful knowledge of detail and the author of a very good soldiers' manual. He made him take a seat beside him at the table, and began questioning him, pen in hand about a host of facts connected with the service and discipline. Some of his questions showed such a complete ignorance of the most ordinary things that several of my comrades smiled. I was myself struck by the number of his questions, their order and their rapidity, no less than the way the by which the answers were caught up, and often found to resolve into other questions which he deduced in consequence from them. But what struck me still more was the sight of a commander-in-chief perfectly indifferent about showing his subordinates how completely ignorant he was of various points of business which the youngest of them was supposed to know perfectly, and this raised him a thousand cubits in my opinion.'

'Napoleon also took 125 books of history, geography, philosophy and Greek mythology in a specially constructed library, including Captain Cook's three-volume Voyages, Montesquieu's The Spirit of the Laws, Goethe's Sorrow of Young Werther and books by Livy, Thucydides, Plutarch, Tacitus and, of course, Julius Caesar. He also brought biographies of Turenne, Conde, Saxe, Marlborough, Eugene of Savoy, Charles XII of Sweden and Bertrand du Guesclin, the notable French commander in the Hundred Years War. Poetry and drama had their place too, in the works of Ossian, Tasso, Ariosto, Homer, Virgil, Racine and Moliere. With the Bible guiding him about faith of the Druze and Armenians, the Koran about Muslims, and the Vedas about the Hindus, he would be well supplied with suitable quotations for his proclamations to the local populations virtually wherever this campaign was finally tp take him.'

'Napoleon had collected all available almanacs and charts on the Russian winter which told him sub-zero temperatures weren't to be expected until November. No information was neglected about that subject. No calculation and all probabilities' were reassuring recalled Faenne. 'It is usually only in December and January that the Russian winter is very vigorous during November the thermometer  doesn't go much below 6 degrees. Observations made from the past twenty years confirmed that the Mosckva winter didn't freeze until November and Napoleon believed this gave him plenty of time to return to Smolensk. It has taken his army less than three weeks to get from Smolensk to Moscow including the three days at Borodeno. Voltaire's 'History of Charles XII' which Napoleon read while in Moscow described the Russian winter as so cold that birds froze in mid-air falling from the skies as if shot. The Emperor also read the three volume 'Military History of Charles XII' by the King's chamberlain Gustafus Omblefelt published in 1741 which concludes with the disaster of Poltava. Omblefelt attributed the King of Sweden's defeat to stubborn Russian resistance and the very piercing cold of the winter. ''In one of these marches 2000 men fell down dead with the cold', reads a passage in the third volume. And in other Swedish troopers were reduced to warm themselves with the skins of beasts as well they could. They often wanted even bread and were obliged to sink almost all their cannon in morasses and rivers for want of horses to draw them. This army once so flourishing was ready to die with hunger. Omblefelt wrote of how the nights were extremely cold, many died of the excessive rigour of the cold and a great number lost the use of their limbs and their feet and hands. From this if nothing else Napoleon would have keenly understood the severity of the Russian winter.'

Napoleon after the retreat from Moscow, 'Whereas in my own case it has taken me years to cultivate self-control to prevent my emotions from betraying themselves. Only a short-time ago I was the conqueror of the world commanding the largest and finest army of modern times. That's all gone now. To think I kept all my composure, I might even say preserved my unvarying high spirits. Yet don't think that my heart is less sensitive than those of other men. I'm a very kind men, but since my earliest youth I have devoted myself to silencing that chord within me that never yields a sound now. If anyone told me before a battle that my mistress who I loved to distraction was breathing her last, it would leave me cold. Yet my grief would be just as great as if I had given way to it. And after the battle I would mourn my mistress if I have the time. Without all this self-control do you think I could have done all I've done?

A member of the group, a chemist in a lab, opened a Subway franchise as a means of raising money. “Since Tom was a genius at numbers,” another member of the group told me, “he was invited to help him.” Zhang kept the books. “Sometimes, if it was busy at the store, I helped with the cash register,” Zhang told me recently. “Even I knew how to make the sandwiches, but I didn’t do it so much.” When Zhang wasn’t working, he would go to the library at the University of Kentucky and read journals in algebraic geometry and number theory. “For years, I didn’t really keep up my dream in mathematics,” he said.

As a small boy, he began “trying to know everything in mathematics,” he said. “I became very thirsty for math.” His parents moved to Beijing for work, and Zhang remained in Shanghai with his grandmother. The revolution had closed the schools. He spent most of his time reading math books that he ordered from a bookstore for less than a dollar. He was fond of a series whose title he translates as “A Hundred Thousand Questions Why.” There were volumes for physics, chemistry, biology, and math. When he didn’t understand something, he said, “I tried to solve the problem myself, because no one could help me.”

Zhang moved to Beijing when he was thirteen, and when he was fifteen he was sent with his mother to the countryside, to a farm, where they grew vegetables. His father was sent to a farm in another part of the country. If Zhang was seen reading books on the farm, he was told to stop. “People did not think that math was important to the class struggle,” he said. After a few years, he returned to Beijing, where he got a job in a factory making locks. He began studying to take the entrance exam for Peking University, China’s most respected school: “I spent several months to learn all the high-school physics and chemistry, and several to learn history. It was a little hurried.” He was admitted when he was twenty-three. “The first year, we studied calculus and linear algebra—it was very exciting,”

Is there a talent a mathematician should have?”

“Concentration,” Zhang said. We were walking across the campus in a light rain. “Also, you should never give up in your personality,” he continued. “Maybe something in front of you is very complicated, it’s lengthy, but you should be able to pick up the major points by your intuition.”

When we reached Zhang’s office, I asked how he had found the door into the problem. On a whiteboard, he wrote, “Goldston-Pintz-Yıldırım”and “Bombieri-Friedlander-Iwaniec.” He said, “The first paper is on bound gaps, and the second is on the distribution of primes in arithmetic progressions. I compare these two together, plus my own innovations, based on the years of reading in the library.”


'whenever he got the chance he would pull out a book and do some reading or some studying for his night school.'

'Kissinger had always been scholarly. Now his rather strong suspicion he was a cut above everybody else was reinforced. Even among the brains plucked out of the army he was considered brainy. He was called upon to tutor the other students in a variety of subjects especially calculus and physics. The process of learning began to enthral him, even obsess him. He would skip meals to devour his books staying in his messy room eating crackers, drinking coke and muttering to himself as he read. Often Kissinger would argue with the books according to his roommate Charles Coyle, 'he didn't read books. He ate them with his eyes, his fingers, his squirming in the chair and with his mumbling criticism he'd be slouching in his chair and suddenly explode with his indignant German accented bullshit blasting the author's reasoning. 

'Leonardo da Vinci liked to boast that, because he was not formally educated, he had to learn from his own experiences instead...'Though I have no power to quote from authors as they have', he proclaimed almost proudly, "I shall rely on a far more worthy thing - on experience.' Throughout his life, he would repeat this claim to prefer experience over received scholarsihp. 'He who has access to the fountain does not go to the water-jar' he wrote... The education that Leonardo was soaking up in Milan, however, began to soften his disdain for handed-down wisdom.

'His notebooks are filled with lists of books he acquired and passages he copied. In the late 1480s he itemized five books he owned: the Pliny, a Latin grammar book, a text on minerals and precious stones, an arithmetic text and a humorous epic poem, Luigi Pulci's Morgante, about the adventures of a knight and the giant he converted to Christianity, which was often performed at the Medici court. By 1492 leonardo had close to forty volumes. A testament to his universal interests, they included books on military machinery, agriculture, music, surgery, health, Aristotelian science, Arabian physics, palmistry, and the lives of famous philosophers, as well as the poetry of Ovid and Petrarch, the fables of Aesop, some collections of bawdy doggerels and burlesques, and a fourteenth-century operetta from which he drew part of his bestiary. By 1504 he would be able to list seventy more books, including forty works of science, close to fifty of poetry and literature, ten on art and architecture, eight on religion, three on math. He also recorded at various times the books that he hoped to borrow or find. 'Maestro Stefano Caponi, a physician, lives at the Piscina, and has Euclid,' he noted. 'The heirs of Maestro Giovanni Ghiringallo have the works of Pelacano.' 'Vespucci will give me a book of Geometry.'And on a to-do list: 'An algebra, which the Marliani have, written by their father... A book, treating of Milan and its churches, which is to be had at the last stationers on the way to Corduso.' Once he discovered the University of Pavia, near Milan, he used it as a resource: 'Try to get Vitolone, which is in the library at Pavia and deals with mathematics.' On the same to-do list: 'A grandson of Gian Angelo's, the painter, has a book on water which was his father's... Get the Friar di Brera to show you de Ponderibus.' His appetite for soaking up information from books was voracious and wide-ranging. In addition, he liked to pick people's brains. He was constantly peppering acquaintances with the type of questions we should all learn to pose more often. 'Ask Benedetto Portinari how they walk on ice in Flanders,' reads one memorable and vivid entry on a to-do list. Over the years there were scores of others: 'Ask Maestro Antonio how mortars are positioned on bastions by day or night... Find a master of hydraulics and get him to tell you how to repair a lock, canal and mill in the Lombard manner... Ask Maestro Giovannino how the tower of Ferrara is walled without loopholes.'


I am living on my farm, and since my latest disasters, I have not spent a total of twenty days in Florence... I get up in the morning with the sun and go into one of my woods that I am having cut down; there I spend a couple of hours inspecting the work of the previous day and kill some time with the woodsmen who always have some dispute on their hands either among themselves or with their neighbours... Upon leaving the woods, I go to a spring; from there, to one of the places where I hang my lime-traps for thrushes. I have a book under my arm: Dante, Petrarch, or one of the minor poets like Tibullus, or Ovid. I read about their amorous passions and their loves, I remember my own, and these reflections make me happy for a while. Then I make my way along the road towards the inn, I chat with passers-by, I ask new of their regions, I learn about various matters, I observe mankind: the variety of its thoughts, the diversity of its tastes and dreams. By then it is time to eat; with my household I eat what food this poor farm and my modest patrimony yield. When I have finished eating, I return to the inn, where there usually are the innkeeper, a butcher, a miller and a couple of kilnworkers. I chat with them for the rest of the day, playing cricca and backgammon, and these games lead to a thousand squabbles and endless abuses and vituperations... When evening comes, I return home and enter my study; on the threshold I take off my workday clothes, covered with mud and dirt and put on the garments of court and palace. Now clothed appropriately, I step inside the venerable courts of the ancients, where, graciously received by them, I nourish myself on that food that alone is mine and for which I was born; where I am unashamed to converse with them and to question them about the ends they sought by their actions, and they, out of human kindness, answer me. And for four hours at a time I feel no boredom, I forget all my troubles, I do not dread poverty, and I am not terrified by death. I absorb myself into them completely. And because Dante says that no one understand anything unless he retains what he has understood, I have jotted down what I have profited from in their conversation and composed a short study, De principatibus, in which I delve as deeply as I can into the ideas concerning this topic, discussing the definition of a princedom, the categories of princedoms, how they are acquired, how they are retained, and why they are lost'. 


Nothing bothered Julia more than insinuations that her husband was an illiterate yahoo. To save her eyes, he read aloud to her for hours each evening, and they plowed through hundreds of books. Mary Robinson confirmed that Grant was unusually bookish. “Most of his leisure time he spent in reading. He was one of the greatest readers I ever saw”.

China's rise to the international stage is for domestic audiences only


IMF adds China's yuan to SDR

On the 30th November the International Monetary Fund (IMF) decided to include China's renminbi in its basket of elite global currencies or Special Drawing Rights (SDR). The new weights place the Chinese renminbi (10.92%) behind only the US dollar and the euro in terms of importance, with the newcomer leapfrogging ahead of both the British pound and the Japanese Yen.

China's rising international status

The immediate impact of the decision is likely to be fairly limited with the new weights only coming into play from 1st October next year. Even without the delay, few goods or services are priced in SDRs and China's inclusion in the basket seems to be largely for show. Andrew Walker, the BBC World Service economics correspondent has said 'More than anything this move is a symbol - a powerful one - of China's meteoric rise, from poverty to pillar of the global economy.'

However, all the talk of China's new place on the international stage fails to appreciate the drama playing out at home. Far from the western perception of a well-drilled army of technocrats, marching to the beat of Beijing's drum, China's government suffers from the same entrenched interests that any political system does. 

Real impact is domestic

It is for this reason that Arthur Kroeber, Managing Director of GaveKal Dragonomics, has argued that Beijing's real motivation in pushing to join the SDR was not 'as many media reports inaccurately suggest, a desire to make the renminbi a major global reserve currency. Rather, it was to force the pace of China's own financial deregulation.'

At the weekly State Council meeting on the 4th December Xing Yujing, head of a monetary policy department at the People's Bank of China (PBOC), echoed these sentiments marveling at the remarkable and rapid internationalization of the renminbi 'especially over the last ten months.' This has been no where more prominent than this August when, on Tuesday 11th, China's shock devaluation of the yuan, weakened the currency against the US dollar by almost two basis points. The official explanation given by the PBOC was that the move was a 'one-off' adoption of a market based approach to setting the yuan's value. However, the widespread perception at the time was that this was actually a desperate bid to revive a flagging economy. Timing is everything, however, and despite the weak export data that had come out over the weekend, just the previous Tuesday the IMF had issued a report which stressed that, with regards to its requirement that the renminbi be 'freely usable', 'significant work' was still needed to be done. In fact, at the press conference announcing the yuan's inclusion, IMF Director Christine Lagarde emphasized that, 'the renminbi's inclusion in the SDR is a clear indicator of the reforms that have been implemented and will continue to be implemented'.

Chinese reforms: two speeds.

The significance of the yuan's inclusion in the IMF's SDR then, is not for the symbolism abroad but rather its role in catalyzing aggressive financial reforms at home. As the Paulson Institute's Houze Song has described, reforms in China are at two speeds 'moving fast in banking and finance... but very slowly, if at all, in the real economy.' The hope in central government is that opening up Chinese financial institutions to foreign competition will force them to be more efficient in their capital allocation and in turn raise China's productivity. For a country suffering from bloated SOEs and debt-laden 'zombie' companies, reforming the real economy remains a monumental challenge but perhaps, with a little international assistance, it can be done.

Going meta


Human knowledge too vast for any one person to master.

Humanity is very good at creating domain experts and our education system is structured to help teach and identify the best in each subject. However, these experts have created a problem which is that accumulated human knowledge, the sum total of all their efforts, has grown to be far beyond the scope of any one individual to keep track of, let alone master. This is a problem because domain experts are increasingly isolated in their fields, ignorant of the wider body of human knowledge.

Long-term solutions

There are several long-term solutions to this problem.

  1. Increase an individual's capacity to learn e.g. genetic engineering, life extension, better teaching.
  2. Create better systems for synthesizing human knowledge. Current examples include how the US President will have teams of experts advising him or how big companies have hierarchies where experts advise senior management to enable them to make decisions. Maybe solutions rely on multiple experts advising one decision maker, maybe with the internet you can replace strict hierarchies with looser, more democratic decision making?
  3. Human-computer partnerships where the human acts as the synthesiser but the computer can provide access to the specialist bodies of human knowledge.

In this essay, however, I want to explore the much easier solution of Charlie Munger's which is to learn all the big ideas.

Learning all the big ideas in all the big disciplines so I wouldn’t be a perfect damn fool who was trying to think about one aspect of something that couldn’t be removed from the totality of the situation in a constructive fashion. And what I noted as the really big ideas carry 95% of the freight it wasn’t at all hard for me to pick up all the big ideas in all the disciplines and to make them a standard part of my mental routines.
— Charlie Munger, billionaire investor at Berkshire Hathaway
Berkshire Hathaway's billionaire investor Charlie Munger


The problem is that traditional teaching is not designed this way. Typically subjects are taught bottom-up with a view to helping those who aim to be experts in a subject rigorously learn it from first principles. Although, this can be valuable, outside your one or two chosen domains of expertise it makes learning even just the core concepts nigh impossible. 


What is needed is:

  1. an easy way to save, find and review the key mental models and concepts.
  2. an easy way to learn the key mental models and concepts.


  • an easy way to save, find and review the key mental models and concepts.

My current solution is fairly good which is when I books, listen to podcasts or watch interviews and someone suggests an interesting mental model I store it in quip, in one of many excel spreadsheets that I have categorized based on topic.


As an example, I recently finished reading 'Poor Charlie's Almanac' which includes his famous essay on 'The Psychology of Human Misjudgement.' Which I have quite simply inputted into an excel spreadsheet. This is very gratifying because it means that I have a systematic way to save all the knowledge and ideas that I come across that otherwise I would quickly forget.

However, as you can see this is likely to very quickly get unwieldy.

The question is in what way would I like to interact with this material? I think there are two ways the first is just general, and perhaps randomized revision. E.g. everyday one mental model from my metadatabase is sent to my phone to review. The second is retrieval, most likely, in the form of checklists I can use to work through a problem, say an investing decision. The question is how to generate this checklist? One way would be to simply create categories based upon which folder the concept/model was saved in but perhaps clever tagging could allow for flexibility on this front.

To consider an example suppose I am thinking through an investment decision and I want to run it against my list of mental models. First I would select the appropriate checklist and then I would be able to run through each item on that list systematically. For example if I was analyzing whether a company is a good investment I would consider checklist item #17 which if relevant I would click yes to and write a brief summary of my thoughts as they relate to the mental model and the specific idea I want to analyse. 

If the brief summary is insufficient to remind the user what the checklist mental model or concept is perhaps there could be a side panel which can come up with a more detailed explanation and link to further notes or even the original source material. 


Obviously to help create this functionality there needs to be a good standardized way to input information. There seem to be a few different types of input structure you may want. But you could have a simple form where if a section is left blank it would not be saved onto the database.

At the end of doing this I could then generate a report of all the checklist points that were relevant to this particular problem alongside my hand written analysis.


  • an easy way to learn the key mental models and concepts.

Of course just like how I read books and write down ideas that interest me I think a lot of the learning will be organic. However, I do think that there should be both an enjoyable and systematic way to learn the core concepts in all the major subjects.

The format my friend and I came up with are five hour videos that would be pitched at medium difficulty in between a more rigorous lecture course on the one hand and layman documentaries and articles on the other hand.

To do this the material needs to be completely reworked and reorganized to allow students to take a top-down, major concepts look at a discipline rather than a more rigorous bottom up approach. 

As an example you may take a five hour course on electric batteries which after an initial hour of foundation work would then over 3 hours explain the 10 major concepts and breakthroughs in the history of battery technology followed by an hour on the future of batteries and the major challenges and potential areas for progress. Having then learnt those 10 major concepts the student could then add those 10 concepts to their library of mental models. 

What we envision is a education company that is focused on content creation rather than platform and tools creation. To make a comparison to the gaming industry, #metalearning would be a game company like Valve or Blizzard rather than a console company like Microsoft's Xbox or Sony's Playstation.


There may even be a role for a different kind of research. Typically a lot of economics research and financial journalism is reactionary, where opinions are given on recent events taken from a largely unchanging and unspoken world view. What if instead, each news story was an opportunity to communicate and compare alternative world views? Each view would be presented with clear references to the underlying mental models and concepts they use back in the database.


    China's financial reform experiments

    Premier Li Keqiang focuses on financial reforms.

    On the 2nd December Premier Li Keqiang meets with Chinese economists to discuss policy reform. [Photo/China News Service]

    On the 2nd December Premier Li Keqiang meets with Chinese economists to discuss policy reform. [Photo/China News Service]

    On the 2nd December, Chinese Premier Li Keqiang hosted a forum of economic experts where he emphasized that supply-side structural reforms, particularly those relating to financial support, were the key to promoting innovation and unlocking sustainable economic development. 

    5 pilot financial reform projects

    Two days later, on the 4th December, the State Council held its weekly policy briefing with several senior members of the People's Bank of China (PBOC) in which they discussed their pilot projects in financial reform. The projects are part of a larger framework of economic policy experimentation aimed at developing the three main types of economic region in China:

    1. Developed eastern and coastal regions.
    2. Central regions undergoing industrial transformation.
    3. Under-developed western and ethnic border regions.
    4th December State Council weekly policy briefing.[Photo/Xinhua]

    4th December State Council weekly policy briefing.[Photo/Xinhua]

    First, in Jilin province, northern China, agricultural reforms include cooperative finance schemes, house property mortgage loans, the development of internet services to promote ecommerce, the introduction of agricultural insurance and perhaps most notably 'land benefit guarantee loans' which involve agriculture-related asset securitization opening the way for financing via capital markets.

    Second in Taizhou, a city in Zhejiang province which lies on the east coast of China just south of Shanghai, PBOC has conducted a pilot project for small/micro businesses. Reforms include improving direct financing channels, promoting a social credit system in local areas, enhancing cross strait financial exchanges, developing insurance schemes and improving financial regulation and risk prevention.

    Finally, free-trade zones (FTZ), like the one successfully introduced in Shanghai, have been proposed in Guangdong (near Hong Kong), Tianjin (near Beijing) and Fujian (near Taiwan). The aim is  to increase cross-border use of RMB by creating the systems and regulatory environment that would allow institutions in these FTZs to take on foreign debt.

    Future possible financial pilot projects include programs around technology finance, inclusive finance and green finance.

    #fromthefrontier: Marc Andreessen on bitcoin



    News used to be about speed. Now it's about understanding.

    Whether it's new technologies, changing policy or quickly developing news stories the modern world is becoming very complex. The problem is journalism hasn't adapted to the fact that it's no longer enough to just churn out the latest headlines, readers need a larger context to help them understand.

    #fromthefrontier is a series of articles that:

    1. CONTEXT : a brief summary of the key ideas, concepts and history of the technology, market, issue etc.
    2. EXPERT: Gives the key views of an expert 
    3. UPDATES: Gives news updates from the expert

    This article is on legendary Silicon Valley entrepreneur (@Netscape, @Opsware) turned venture capitalist (@Andreessen Horowitz) Marc Andreessen's opinions on the cryptocurrency bitcoin.




    Bitcoin is a new and alternative form of digital currency and payment system.

    Historically, digital currencies have suffered from the double-spending problem where John might send the same digital dollar to both Alice and Katy without them knowing and thus 'double-spend'. Of course, physical currencies don't suffer from this problem because the transfer of the store of value involves the physical transfer of a coin or a paper note. Digital currencies solved this problem by having a centralized ledger run by a Visa or Mastercard where they would keep track of all the transactions to make sure there is no fraud or double-spending. In return for running this service Visa would take a cut on all the transactions.

    Unlike other digital currencies bitcoin is decentralized and has a public distributed ledger called a block chain allowing users to transact directly (peer-to-peer) without the need for an intermediary. For this reason bitcoin is often referred to as a cryptocurrency which is a subset of digital currencies where cryptography (rather than a middle-man) is used to secure the transactions and to prevent fraudulent creation of new units. However, it should be noted that the ledger is maintained by third-party miners who are paid in bitcoins which creates a small inflationary effect on the value of the bitcoins.

    Bitcoin was created by Satoshi Nakamoto, the pseudonym for an unknown person or team of people, who in 2008 wrote a paper called 'Bitcoin: A Peer-to-Peer Electronic Cash System' with bitcoin's software itself was released in early 2009.. 

    Since then bitcoin has grown rapidly with the number of transactions in bitcoin rising from a few thousand per month in 2009 to more than a several million in 2015.

    Number of transactions per month of bitcoin (logarithmic scale).

    Number of transactions per month of bitcoin (logarithmic scale).

    Nonetheless, bitcoin has been controversial with software problems, legal issues and perhaps, most significantly for investors, the price has been extremely volatile peaking to as much as $975.45 in Nov 2013 but falling off from that dramatically since.

    Despite his bitcoin has slowly become more mainstream with companies like WordPress in November 2012, Chinese internet giant Baidu in October 2013 and Microsoft in December 2014 accepting the currency. Venture capital investments in bitcoin related companies has been increasing significantly and is on track to be even more in 2015.

    For a good introduction watch this documentary 'The Rise and Rise of Bitcoin'.




    At the heart of Andreessen's argument for bitcoin is the comparison that Bitcoin now looks a lot like personal computers in the 1970s and the internet in the 1990s. They too had lots of legal and regulatory problems, unproven commercial applications and highly uncertain futures but look how they turned out!

    At a deeper level Andreessen's view is rooted in economist Carlota Perez's model of 'Technological Revolutions & Financial Capital' in which technological revolutions occur in two stages: the installation phase and the deployment phase. Crucially, whether it's steam engines, the combustion engine or bitcoin all new technologies in the installation phase are neither accepted or understood by the broader society which is still trapped in the thinking of the previous wave. It's only in the deployment stage that these technologies are adapted to and therefore their true is unlocked. The significance of this model for bitcoin, of course, is that Andreessen, as a venture capitalist and someone who is betting on the future, is looking for technologies that are in the installation phase because by the time they are in the deployment phase it is too late. 

    This section is divided into three parts 1. Andreessen on bitcoin technology 2. Andreessen on criticisms of bitcoin 3. Andreessen on current and future use cases.

    1. Andreessen on bitcoin technology

    Bitcoin, like most widely used stores of value including gold and fiat money, is intrinsically valueless and is only useful if lots of people use and accept it. However, Andreessen argues that bitcoin is more than just a hyped up speculative asset because as the first practical solution to the so-called 'the Byzantine Generals Problem' it is a genuine breakthrough in computer science. The significance of bitcoin is that it provides a way for unrelated parties to trust each other over an untrusted network and transfer (not copy) a digital asset which could be anything from contracts, to passwords and of course money. This in turn means you can have a system of payments without a middle man and therefore no transaction costs.

    2. Andreessen on criticisms of bitcoin.

    There are several criticisms of bitcoin Andreessen disagrees with. 

    1. Bitcoin is too volatile. Andreessen argues that volatility is a function of speculation which has actually helped with adoption of the currency whilst the transaction use case is still weak. He concedes that in the long-run volatilty needs to be lower but as transaction volume increases when compared to speculative volume that should happen naturally. Also with derivative (hedging) and a wider acceptance of the currency should help stabilize things
    2. Black market/illegal activity. Andreessen argues this is over-stated and actually compared to gold, cash or diamonds digital currency is much more trackable because there is a ledger which anyone can see recording all the transactions.

    He does concede though that:

    1. Bitcoin may not be the final form of digital currency and that some future cryptocurrency built on the block chain technology may replace it. 
    2. Bitcoin has a genuine chicken and egg problem that all networks have which is a currency isn't useful to consumers until merchants accept it but merchants won't accept it until consumers use it. Thus in the short-run, less revolutionary but better adapted to the current system systems like Apple Pay may at first win out.

    3. Andreessen on the use cases of bitcoin.

    Current uses case of bitcoin include:

    1. Speculation. As previously argued this may be how bitcoin gets around the chicken and egg problem before its primary use case as a currency emerges.
    2. Lower transaction costs. Without the need for a middle-man managing the ledger there are no need for transaction costs.  
    3. Bitcoin can be used just as a payment system without any exposure to bitcoin price volatility.
    4. Bitcoin can be used to prevent credit card fraud because the information transferred is related to the bitcoins not to the transacting parties.

    Futures use cases of bitcoin include:

    1. Increased access to modern financial services both for unbanked people in the US and people in less developed countries, especially those with corrupt, unstable and undeveloped financial systems.
    2. The low transaction costs are particularly significant for international remittance where transaction costs can be very expensive.
    3. With limited to no transaction costs suddenly micro-transactions, tiny fractions of an american dollar in value are possible and could be used from anything a tiny cost to sending emails to preventing spamming to a way to determine who gets access to that car parking spot.
    4. Finally, the low transaction costs allow for a new way for charities and movements to easily and freely raise money for good causes.



    September 2015

    Andreessen tweet.

    • He teases those who fail to see that the commercial value is in a technology's applications not the technology itself.

    January 2015 

    Andreessen delivers tweetstorm on bitcoin. 

    • Fights against three negative bitcoin arguments 1. bitcoin price fallen a lot 2. bitcoin is too volatile 3. not enough use cases.

    November 2014

    Andreessen's fellow VC at Andreessen Horowitz, Ben Horowitz at Stanford on bitcoin.

    • Explains the problem bitcoin solves and compares it to the internet.

    October 2014

    Andreessen at a Salesforce conference.

    • Admits to chicken and egg problems with bitcoin and long-term and high risk nature of the bet but argues that the reward makes it still worthwhile.
    • Cryptocurrency will definitely happen however.

    March 2014

    Andreessen at Pandomonthly interview. 

    • Admits to lots of legal issues, but argues bitcoin is a response to the over regulation of traditional finance, in the long-run more clamping down might make bitcoin even more compelling. Hasn't made a bet yet because conflict of interest issues mean they can only make one bet. 

    January 2014

    Andreessen writes in the New York Times about 'Why Bitcoin Matters'.

    • Includes how bitcoin works, rebuttals of criticisms, examples of use cases and speculation on the futures of bitcoin.


    Economic Structure & GDP/Capita

    “The first problem for the government in carrying out an industrial policy is that we actually know precious little about identifying, before the fact, a ‘winning’ industrial structure. There is not a set of economic criteria that determine what gives different countries preeminence in particular lines of business. Nor is it at all clear what the substantive criteria would be for deciding which older industries to protect or restructure.” Charles Schultze, chairman of the Council of Economic Advisors under US President Jimmy Carter

    This essay is going to present some research I’ve done recently on industrial structure or what I like to call ‘economic structure.’ A country’s economic structure describes what industries or economic activities it is involved in. We are used to classifying a country’s economic activity as either agricultural, manufacturing or services. Knowing the percentage of economic output that is either agricultural, manufacturing or services we then know the overall economic structure of the country. Of course this is only to a ‘3-industry’ level of detail. You could classify a country’s economic activities much more precisely and in fact in future essays I hope to look at data where a country’s economic activity has been classified to a ’12-industry’ level of detail. The aim of this essay though is to investigate the relationship between a country’s ‘3-industry’ economic structure and its GDP/capita. If there is a strong correlation this would suggest that the path to economic development is largely the same for all countries because for every level of development (i.e. GDP/capita) there is a specific economic structure. If there is a weak correlation this suggests that there are many paths to economic development and that a country’s success is not just a function of what it does but also how well it does it.

    3-industry analysis

    I did a 3-industry analysis of all the countries in the world I could find data on excluding countries that have populations of less than a million people. The reasoning for excluding them was partly because I didn’t have any data for them but also because intuitively I felt like small countries could have bizarre economic structures which might be very misleading. For example a country of just a few hundred thousand people might have an economy that is largely based on tourism which clearly for much larger countries, with tens of millions of people, is not scalable.

    What we find is that the R², a measure of how well the data fits our statistical model, is 0.35 which is not bad but not great. Removing the ‘oil countries’ though we find the R² improves significantly to 0.47.

    One puzzling aspect of the results is why the p-values are so low. Even after removing agriculture, especially as for many of the developed countries agriculture is just a few % of GDP, multicollinearity should be a big problem. This is because lowering manufacturing’s % of GDP should (in some cases almost 1-1) increase services’ % of GDP. However regressing manufacturing on services I find an R² of just 0.09 suggesting that there is no multicollinearity problem.

    However, further investigation suggests that the t-tests are not valid because the errors are not normally distributed. Eyeballing the pnorm and qnorm graphs we can see the errors are clearly not normal.

    Taking a look at a 3-D graph though it becomes clear that it is actually agriculture that does most of the explanatory work. Below you can see a top-down view of the 3-D graph where the red line represents the 1-1 trade-off between services and manufacturing. The closer a data point is to the red line the smaller agriculture contribution to GDP is and the larger the combined contribution of services and manufacturing is.

    Taking a side-on view we can see that when agriculture is a high percentage, more than 10% of GDP, i.e. left of the blue line GDP/capita is very low. If agriculture is less than 10% of GDP suddenly GDP/capita is much higher. In fact if you compare the average GDP/capita of countries with agriculture that is more than 10% of GDP/capita to countries where agriculture is less than 10% of GDP/capita you find a stark difference. The more agricultural economies have an average GDP/capita of just $4294.8 whereas the less agricultural economies have an average GDP/capita of $26261.7. And in fact a regression on just % of GDP that is agriculture has an R² of 0.43 only slightly lower than the manufacturing and services regression R² of 0.47. As you can see below, as GDP/capita rises countries tend to have a larger Services % as compared to Manufacturing % but the effect is not as extreme as one might expect.

    I think the real puzzle to me is why there is this turning point at around 10% agriculture. It cannot just be that the less productive agriculture is being phased out in favour of the more productive manufacturing and services. There must be something more fundamental going on but what exactly I’m not sure. Nonetheless I think you could make a good argument that the countries in the left column which have relatively low GDP/capita given their low % of GDP that is agriculture are perhaps on the verge of a massive economic growth as they race up the curve and join the countries on the right column.

    10% Agriculture

    I want now to try and investigate what is happening when countries agriculture drops below 10% and explain why GDP/capita rockets up so much once this threshold is breached. Unfortunately the Serbian and Argentina websites are not in English and so I was unable to find the data I wanted. Thailand, Macedonia and Malaysia on the other hand have only very limited data sets available. This leaves us with Turkey, Belarus, Tunisia and China.

    Part of the problem is I’m not sure what I’m looking for. I suppose it seems like manufacturing and services suddenly become much more productive when agriculture dips below 10%. So why is this? Is it coincidence? Is that at that point enough labour transfers across? Is it that old industries suddenly become more productive or new industries become less productive?

    Next steps a) Investigate countries around the 10% boundary. Why the sudden increase in GDP/capita b) Investigate whether countries historic development in terms of the turning point around 10% agriculture matches the current distribution. c) Investigate 12-industry data to see whether there is one path to economic development or multiple. Does economic structure determine GDP/capita?

    Investing in the London Housing Market

    This essay is an exploratory look into the housing market, using London as the starting point. Housing is interesting because there is no obvious fundamental to tie the price to. This is in contrast to say stocks where the price of a company should, at least in practice, be tied to the current and discounted future expected profits. Of course like any market I would still expect housing to be internally consistent, where no house sells for much more or less than other similar houses in the same area. This internal consistency however, does not protect you from bubbles and the mass delusion that my house is not mispriced because look at what next door sold for! Clearly having some fundamental to tie house pricing to would be very useful as a way to spot bubbles. Ideally though we would like to be able to go further and use predictions about the fundamental to in turn predict future house pricing.

    Most housing investors tend to have one of two strategies. The first is to buy an old house and renovate it and the second is to predict which areas are ‘on the up,’ which areas are about to be gentrified. This is more of an art than a science but classic clues are improved transport links, better shops and bars and good (but perhaps in need of work) housing stock. I even heard one investor who bought based on wherever a new Starbucks was about to be built. Looking at the data for house prices between 1995 and 2014 we find that there is no obvious relationship between the initial mean house price in 1995 and the amount the index has increased by 2014. Some cheaper areas were gentrified a lot other areas where not.

    All of these strategies though are fundamentally unsatisfying because it still feels a lot like guesswork. My mum manages and invests in property for a living and it is interesting talking to her because she would much rather invest a million pounds on a flat in Chelsea (a comparatively expensive area) than say three houses in Lewisham (a comparatively cheap area). Her argument is that people will always want to live in Chelsea. Initially I thought this argument seemed a little naïve but actually it bears a striking resemblance to Warren Buffett’s approach to investing in stocks. Buffett argues that, just in the same way it is difficult to predict which area will be gentrified next, it is very difficult to predict which companies will succeed. In fact even if you are sure that say, the car or the plane (as they most certainly did) are going to change the world that does not make it any easier to pick the winners from the losers. So Buffett’s approach is to ask what will technology not change? Who is on top now and is likely to remain there? This strategy has led to safe and unsexy investments in companies like Coca Cola and Wrigley’s chewing gum rather than the roulette table of trying to predict the next Facebook or Google.

    Nonetheless it seemed to me that imbedded in my Mum’s preference for Chelsea was the hidden assumption that rich people are going to get richer faster than poor people will. And this gave me the idea that the fundamental that could be used to tie down housing prices should be income and in particular how well different strata of the income distribution are doing and are expected to do in the future. Put simply if you expect there to be more inequality with the rich accelerating away from the poor then you would expect expensive areas like Chelsea to be a better investment. If you expect income inequality to go down with lower income people getting richer faster than higher income people a cheaper area like Lewisham may be a better investment.

    Income and property prices

    The first step was to investigate whether there was a relationship between property prices in an area and the incomes of people in that area. Intuitively it seems like there should be but there are also good reasons to think there may not be. Firstly property markets are not particularly liquid because people buy and sell houses relatively infrequently. Furthermore, housing’s relatively low running costs mean that once you own a property even if your income is relatively low you can continue to live there. Perhaps you bought your house with your low income decades before and then just been fortunate to have the value of the house rise a lot since. Similarly even if your income is much higher than your house suggests you may have already put down roots in an area, with all your friends and family nearby so even though you could afford a more expensive house you do not move. And finally you would expect there to be quite a lot of variation in how much of their income people would want to spend on housing versus other goods. What we find though is actually there is quite a strong relationship between mean house price and mean income across the boroughs of London.

    Above is a regression of mean house prices in the 32 boroughs of London on the mean income of people in those boroughs. The house price data is from the Land Registry’s House Price Index and the income data from HMRC’s Survey of Personal Incomes. The House Price data is released on a monthly basis and so it was averaged out for the tax year to match the HMRC’s data. In this case the data is from 2011. What we find is a very high R² of 0.936 suggesting the model has a lot of explanatory power. The t-statistics are statistically significant with very small p-values. And in fact, this is not surprising because if you eye-ball the graph the data certainly looks fairly linear.

    However it is important to do some robustness checks to make sure the assumptions of linear regression are being met, particularly to check whether the errors look random or not. Which as you can see from the rvf plot the residuals clearly do not.

    I thought the lack of normality and randomness of the errors might be caused by non-normal mean income and mean house price variables. So I tried using ladder, gladder and qladder functions on Stata to suggest possible transformations.

    First I found that mean income can be considerably improved by transforming it to 1/meanincome² where from ladder we can see that we get a χ² of just 0.69 which is pretty good.

    This is also reflected in the gladder plot which shows visually the different transformations and how normal they look. As with ladder 1/square looks the best.

    The 1/square transformation looks especially good in the qladder plot which is sensitive to deviations at the extremes.

    However unfortunately we find that for mean house price no similarly good transformation exists.

    1/square is again the best, but this time only the best of a bad bunch. The qladder plot in particular is not that good.

    And in fact I found that if we regress the new variables 1/meanhouseprice² on 1/meanincome² in addition to losing explanatory power the rvfplot does not improve that much because the errors still do not look very random.

    Use income as predictive variable of property prices?

    Given that there is clearly some sort of relationship between property prices and income I thought it might be interesting to try and use income as a predictive variable for future property prices. In the above example I used income and property data from the same tax year but it would not be that surprising if perhaps there was a lag effect where income increases and then it takes a few years before that is converted into an increase in property prices.

    To investigate this I regressed mean house prices for each year across all the different mean income years that I have in my dataset. Thus we take the mean income data for the tax year 2000 as the explanatory variable for 12 regressions for mean house price from the year 2000 to 2012.

    What we find is roughly what you would expect which is that the mean income data for the year 2000 has more explanatory power for year 2000 mean house prices than the mean income data for the years following that. However, when we consider the other years we find that this pattern is not maintained.

    Instead it seems like some years the mean income data has more explanatory power than other years, or perhaps more intuitively, some years the housing prices are more in sync with income distributions (2005 and 2005) and other years more out of sync with the income data (2000 and 2002).

    Surprisingly housing data is more in sync with income for 2005 and 2006, the years just preceding the financial crisis. It seems a reasonable hypothesis that the housing market should be explained by incomes in that area and so years where there is a larger disconnect such as in 2000 and 2001 might suggest a good time to purchase for a potential investor. Having said, the variations in R² are pretty small and I have not done robustness checks as I would expect similar problems transforming the data as before.

    One thing is clear, it seems unlikely that changes in London’s overall income distributions can be used to predict changes in future house prices. This is especially true as income data is only available two years afterwards (so for the tax year 2014 only 2012 data is currently available).

    Borough by borough income and property price data

    The next step I thought would be to try to see if there were any patterns in the borough by borough housing and income data.

    What I noticed was that more expensive areas seemed to recover much quicker from the recession than cheaper areas. As an example Kensington & Chelsea and Islington seem to be already back to trend. This is in contrast to many cheaper areas where increases in income in recent years has not be converted into higher house prices. This led me to hypothesis that perhaps poorer people were being disproportionally credit constrained.

    As you can see boroughs with mean house prices that were less than £350000 in 2007 by 2012 had suffered decreases in house price value. This is contrast to boroughs with mean house prices in 2007 above about £350000 where their prices increased. And in fact the seemingly linear relationship has a pretty good R² of 0.935. The question then is whether this constraint is a long term phenomena or a short-term one. If it is short-term it would make sense to invest in the cheaper areas whilst the house prices are temporarily lower because of short-term increases in lending standards.

    However when I investigated the amount of leverage for the different housing boroughs I found that the least leveraged areas where the most expensive. Admittedly all the mean income data is pre-tax but given the tax rules vary from person to person I could not think of an intelligent way to estimate the average tax rate for each borough.


    So in conclusion it seems like the best area to invest in is Kensington & Chelsea. There are several reasons for this.

    Firstly in the last twenty years house prices have increased seven times in Kensington & Chelsea compared to just three, four or five times in other areas. Clearly to invest in an area simply because historically it has increased the most is unwise but on the other hand at least it gives a positive trend.

    Secondly the leverage of residents in Kensington & Chelsea is the lowest of all the boroughs suggesting that the increase in prices is not a function of lax lending standards pre-recession. Having said that, I suspect many Kensington & Chelsea residents may own multiple properties so they might actually be more leveraged than I initially imagined. Also as previously mentioned, incomes are pre-tax so it is possible I’m underestimating the amount of leverage.

    Thirdly increasing inequality particularly as the most wealthy’s incomes are increasing at a faster rate than everyone else’s is likely to lead to even greater increases in house prices in Kensington and Chelsea.

    And finally there are very high numbers of foreign buyers, who tend to invest primarily in the prime areas of central London including Kensington and Chelsea. In fact, according to property experts Knight Frank as many as 28% of buyers of properties over £1 million do not live in the UK. Having said that it is possible that foreign demand will slow down with the introduction of a new capital gains tax for foreigners when they sell homes in the UK from April 2015.

    The next step in the research will I think to try and investigate these factors further.

    Politics & Economics: An Initial Framework

    Over the last few months I have been talking to a couple of economics research firms about possible jobs opportunities. One repeated theme in their research is that politics and economics cannot and should not be separated, they are intimately entwined. How then to think of them together? One approach is to think of economics as just one of many political tools to achieve political ends. However in this essay I want to explore thinking about politics through an economics lens. The brutal reality is that the, quite frankly astonishing, appetite for economics research is not borne from concern about the welfare of our fellow human beings but rather from a hunger for investment and financial understanding. In other words, how does politics inform economics? Not the other way around.

    With that in mind the basic framework I came up with is to think of classifying governments within a 2 dimensional grid. One dimension is economic competence (the y axis). The other is governmental freedom of action (the x axis).

    A country’s economic competence is ultimately just a judgment on the economic policies a government pursues and how those policies are carried out. Of course that judgment (at least in the short-run) is subjective and often depends upon which school of economic thought you subscribe too. Other factors matter too though, for example high levels of corruption where government officials pursue private ends over societal ones lowers economic competence whilst having lots of hard working and intelligent people in government increases economic competence. Remember this is politics and government policies judged through a purely economics lens and is not passing judgment on human rights are other societal and political objectives.

    Governmental freedom of action on the other hand is to what extent can government do what it wants, particularly if what it wants is unpopular. Factors that might affect governmental freedom of action include the structure of government (democracy or dictatorship?), the size and economic strength of the country (big, strong economies mean bigger tax revenues and more ability to pursue big investment projects) and the values and beliefs of the society (if the public agree with your policies you can do more).


    To finish, I’d thought I’d explore the framework with a few case studies.

    Mao’s China vs Deng Xiaoping’s China

    Most modern-day economists agree that Deng Xiaoping’s decision to ‘open up’ China was a good one. It certainly coincided with the start of a stunning period of unprecedented economic growth in China that still continues to this day. Mao’s China in contrast was one where 5 Year Plans and the Agricultural Crisis of 59-61 had crippled China’s economy to the extent that economic growth between 1952 and 1971 was just 0.5% a year. Thus even though there was limited change (at least in the short-term) in the Chinese governments freedom of action there was a big change in its economic competency.

    USA 1930’s vs USA WW2

    The USA suffered years of sky high unemployment throughout the Great Depression but was ultimately saved by Keynesian policies that probably would not have been possible without World War 2. World War 2 and the threat from Hitler’s Germany created the political will and therefore gave the government the freedom of action it needed to – in purely economic terms – kick start the American economy.

    Democracy vs Not

    Governmental freedom of action is hugely important I believe in determining economic outcomes. Niall Ferguson argues that American democracy is superior to the Chinese system of government in everyway (particularly human rights) except that the Chinese government can think, plan and invest long term in a way an American government with elections every four years cannot. I have even gone as far to argue (in my piece on Justin Yifu Lin’s Comparative Advantage Following strategy of economic growth) that rather than hurting China’s economic future Mao’s policies laid the foundation for them. Mao though was blessed with a society unique in its ability to endure terrible hardship and human suffering, an ability which gave Mao an unprecedented freedom of action in choosing his economic policies.

    This is a freedom of action that western economies with their large welfare states, bad bank balances and frequent democratic elections are unable to match. Only in wartime is political will (and therefore governments freedom of action) sufficient to have democratic nations really embarked on awesome public investment projects like the Space programme or the Manhattan Project. I think it is worth pointing out that although Western countries would consider themselves democratic there is no such thing as a pure democracy, everything is on a sliding scale. For example the United States if it had biannual Presidential elections would be a more democratic state, but every agrees that this would be crazy and that it is worth sacrificing a little bit of democracy for stability in leadership.

    Although this framework is only concerned with economic outcomes it is important to recognise government freedom of action is usually determined by non-economic considerations. Democracy itself is structured to fight against those in power having too much of it or for too long. After all, as the well-worn phrase goes, power corrupts. In fact, according to Presidential historian David McCullough George Washington, Founding Father and the first President of the United States, greatest act was leaving office when he could have stayed. Like Rome’s Cincinnatus he ‘returned to the farm’ and in doing so not only created a precedent of just two terms in office but also helped protect America’s, at the time, still fragile democracy.

    Going forward therefore, it might be cool to first try and classify all the governments of the world within this framework and second evaluate any changes in government leadership or policy in terms of how it affects a country’s position within the axes of economic competence and freedom of action. This might offer an interesting perspective on which countries you might want to invest in or which countries you think will have strong economic growth.

    Charlie Munger, Warren Buffett’s partner at Berkshire Hathaway

    ‘It’s a very interesting problem, that our founders coped with in just how democratic you wanted the system. My favourite political system in terms of being adapted to its particular circumstances successfully is Singapore. I think Singapore is the single most successful governmental system that exists in the world. They’ve taken a small swamp to a very credible place… I think Singapore’s habit of stepping hard on things that will grow like cancer is the correct way to govern. In America we tend to wait until things are unfixable… And finally you reach a tipping point where the better people leave and then I don’t think you can solve the problem… I don’t think it is a pure democracy. I think our system has worked but… Let me tell you my story… I take a political science course [at university] and everybody teaches the more people that vote the better the systems will work and having a contrarian streak I’m not so damn sure that civilization doesn’t work better when a lot of people don’t vote… If you want to study, take Singapore: terrible malaria problem. It’s a swamp! He [Lee Kuan Yew] drains the swamps, he does not care if some little fish dies. He has a drug problem. He searches the world over for the right solution to the drug problem. He finds it in the United States, imagine someone in Singapore reading books on the United States and thinking the United States is the answer to Singapore’s problems. He copied the military’s drug policy so that anybody in Singapore will pee in a bottle instantly and if they fail they will immediately go to a tough compulsory rehab. Away went the drug problem. Just time after time after time he made these winning decisions. He wanted the place to prosperous. He figured out who he wanted to come in and he made the civilization very user friendly to what he wanted to attract. And it worked! Then it’s 70% Chinese and 30% Malay. And every Chinese thinks that the Chinese are superior to the Malays and he thinks thats terribly counterproductive if anybody should ever say so. So he passes a law. You can’t say if you’re Chinese in Singapore that you think there is any superiority in the Chinese. I think that’s a very sensible law for Singapore to have but of course it has some infringement of free speech! …I mean so this is a very unusually successful man with a very unusually successful history. So while I can’t answer your question if you will make a study of the life and work of Lee Kuan Yew you will find one of the most interesting and instructive political stories in the history of mankind. This is better than Athens. This is an unbelievable history. And you will learn a lot that will be useful in your own life. So my answer to you is don’t ask Charlie Munger. Study the life and work of Lee Kuan Yew. You’re going to be flabbergasted.’

    Thoughts on the Tradeoff between technology growth and employment


    As the developed countries of the world limp out of yet another crippling recession, macroeconomics has been forced to do some soul-searching. Graduating from the London School of Economics with a degree in Economics our departmental commencement speech, in front of friends, family and graduates alike, was a sombre one: impressing the need to manage the public’s expectations about what Economics and Economists are able to do. Put bluntly, despite all the great minds that have applied themselves for decades against the Economics grindstone the holy grail of creating a ‘no recession, no unemployment and steady growth economy’ has remained elusive.

    In this essay I argue that the economies of the future are going to look vastly different from the ones we have today. In particular, I believe there is a trade-off between technology growth and full employment and that if we want the former we shall have to give up on the latter. We shall need to adapt to a society, and a politics, where most people, probably north of 90%, do not work at all in their entire lives. I argue that this is not only not a bad thing, but actually something we should work towards.


    So first of all, let’s start with the assumption that for the foreseeable future, let’s say the next hundred years, we shall have strong technology and productivity growth. This is obviously a strong assumption and so we shall not neglect the alternative, that our future might be one with limited or perhaps even no technology growth, in fact this is something we shall examine in the second half of this essay. For now though, although perhaps optimistic, assuming technology growth is a useful place to start out our discussion.

    My argument, which I have summarised in the table above, is that technology growth will lead to a net decrease in the ‘number of jobs’. The reason for this is simple: technology growth destroys jobs faster than it creates them.

    This was not always the case, for example during the Industrial Revolution advances in farming equipment meant lots of farm workers were put out of jobs but this destruction of farming jobs was offset by the creation of lots of manufacturing jobs in the factories.

    Now it is worth drawing a distinction between developed countries and developing countries. Developing countries in Africa or even countries like China and India could get away with doing nothing innovative for decades to come but still have fantastic ‘technology growth’ because they are simply imitating and executing ideas from the developed countries. This is most certainly worth doing and has resulted in massive improvements in material living standards for billions of people across the planet and hopefully will continue to do so. However, eventually these developing countries will catch up and become developed and then will face the same problem that we in the West are already facing now; which is to have sustained technology growth we need to keep coming up with new things.

    Peter Thiel, co-founder of PayPal and billionaire investor in companies like Facebook, argues that the problem is there has been a failure of imagination. Thiel grew up on the science-fiction of the 50’s and 60’s which imagined a 21st century of underwater cities, colonies on Mars, as well as intergalactic trade and exploration. A world where we could extend lives into the hundreds of years, mind-share ideas and skills instantaneously and dare I say it teleport (‘Beam me up, Scotty!’). As the motto of his venture capital firm ‘Founders Fund’ wittily points out ‘We wanted flying cars, instead we got 140 characters.’

    Although I agree that such projects, if possible, would be both very cool and worthwhile, I do not think they would create a lot of jobs. You only have to look at the most innovative companies of today like Google and Apple which employ workers, admittedly very high-skilled workers, in the 10,000s, not the millions, hardly sufficient to find jobs for the billions of people on the planet.

    This is a problem because I believe there are three types of technology growth.

    1. Build new stuff e.g. iPhone
    2. Automation e.g. car manufacturing
    3. More productive employees e.g. computer

    Both ‘automation’ and ‘more productive employees’ types of technology growth, as we shall see, both lower the number of jobs. Previously these forces were kept in balance by the first type, building new stuff but now when we build new stuff we don’t require lots of workers because most of the job creation is in the innovation of the product not in the manufacture or production of it, and for that you just need a few highly skilled workers. It is obvious why ‘automation,’ at least temporarily, destroys jobs because it involves the direct replacement of human labour with machines and robots. A classic example of this is the manufacture of cars where much of the production now is automated, whereas previously it was very labour intensive.

    Why ‘more productive employees’ type of technology growth destroys jobs is more subtle. In economics, one of the key assumptions is unlimited demand with the only constraint being the budget constraint, i.e. not having enough money. With this assumption, even if people are unemployed new industries and products will develop to take advantage of these unused resources and to meet our insatiable demand. Of course, in the short-run there may be structural unemployment but in the long-run full employment is always possible, as with education and retraining workers are able to find work in the new industries being created. Now of course, for most of human history this is a fairly accurate picture and it is still probably an accurate picture for most people today, consider the Chinese rice farmer or the Brazilian favela housewife, I’m sure, if only they had the money, they would be buying fancy cars and going on luxury holidays. However, we are already seeing the effects of another constraint, a constraint that has usually gone unaccounted for and that is time. Limited time is easiest understood in the creative arts. Only so many people can earn a living as authors, or musicians or artists because you only have so much time to consume these things. And as everything is so scalable now why listen to the average pub singer in your local bar when you can listen to Adele on your iPod? This same principle extends to other areas outside of the creative arts. And as workers become more productive it will be possible to reach our ‘limited demands’ with fewer and fewer workers.

    The question then is, faced with the reality of a world with fewer and fewer jobs, what should we do next? I would argue that rather than try and continue to pretend that economies with both high employment and technology growth are possible we should embrace the change. In fact, those same science-fiction novels that Thiel grew up on also imagined another change: that we would all be working single digit hour work weeks because robots had replaced all the menial tasks and allowed us to live lives of leisure. ‘The Jetsons’ a cartoon tv show in the 60’s that imagined a typical American family 100 years in the future (2062 to be exact) not only had a full-time robotic house-maid called Rosie but also had George Jenson, the patriarch of the family with a workweek, typical of his time, of just one hour a day, two days a week!

    There is a practical aspect to such a society which is that there needs to be transference of ‘income’ from the robots, that are automating all the tasks that are currently being done by humans, to the humans who are now ‘unemployed.’ It is worth pointing out that the robots will not mind being paid nothing, because they are robots! This most likely would be done through a huge welfare state, where perhaps 90%+ of people would spend their entire lives without working. Now obviously, welfare states often get a bad reputation because there are always people who abuse the system and the unfairness of taxing those who work to support those who do not work. In particular, although the production of most things will be done by robots, the machines obviously do not collect a wage and so the actual transference of income will be from the entrepreneurs who made the robots to the masses of unemployed, and with taxes north of 95% I’m sure economists around the globe will be having fits over the lack of incentives.

    There are a few counterarguments to this. To start with I absolutely recognise humanity’s need for inequality, something that is perhaps even greater than its need for equality. First of all in a world where everyone has a high standard of living and does not need to work, money will matter less and there will be other avenues for ‘inequality’ or less cynically ‘a diversity of identity’ to be expressed, like through hobbies and interests. Furthermore, in a world where most people do not work but a few highly skilled entrepreneurs, scientists and artists do, there would be arguably too much inequality rather than too little, so forgetting all the baggage we have about tax rates, there should still be sufficient incentives to motivate great projects, even if taxes are at 95%. It is worth noting that it is not the single mum working 3 jobs who is being taxed 95%, she is now living a life of leisure, but rather the Bill Gates’ and Warren Buffetts of the world. Some may argue that a life of leisure is not fulfilling, work provides meaning and fulfillment which sitting at home and watching TV can never do. This I absolutely agree with but I think it is worth noting that most people do not have jobs anything close to our ideal of fulfilling work. Even in America, the most developed of nations, most people do very menial jobs. As the education reformist John Taylor Gatto in his ‘The Underground History of American Education’ points out the top ten most common jobs in 2020 is predicted to be, according to the US Bureau of Labour Statistics:

    1. Retail salesperson
    2. Registered nurse
    3. Cashier
    4. General office clerk
    5. Truck driver
    6. Managers
    7. Janitors, cleaners, domestic servants
    8. Nurse aids, orderlies, general attendants
    9. Food counter workers
    10. Waiters

    So given that most people do unfulfilling, low-skill work I think the best thing is if we as a society try to automate each of these jobs. Google’s self-driving cars might be a step in the right direction in terms of replacing Truck Drivers, or supermarkets having self-checkouts, a first step in automating Cashier work.

    With time as all these jobs are automated, people, with a guaranteed high standard of living, will then be free to pursue not only lives of leisure but also have the chance to improve themselves and both discover and follow their passions. I know I certainly would take more risks pursuing my entrepreneurial dreams if I was not so scared of, essentially, getting a bad job. Peter Thiel argues that increasingly, higher education is not about learning anymore but rather about insurance, which says that if you have a degree certificate you will not, what he describes as ‘fall through the cracks in society.’ So rather than damage incentives there may be actually more innovation and more production. Just think of the number of Marlon Brandos who never tried to become actors because they were scared of spending their lives as waiters! Now as I argued previously most people will not be world class in anything, that by definition is rare but with the freedom to fail there is nothing wrong with that.


    With the transition to a world where we have less than 2 children per woman population growth is no longer going to be an engine of economic growth anymore. This is a good thing as resource constraints would probably mean anything above this would end in a Malthusian catastrophe. Furthermore changing demographics, notably the boost to our economy that bringing women into the workforce has had has now largely run its course. Thus, in the developed world at least, the buck has officially been passed and further economic growth will require technology growth.

    It could be argued that a world with no technological growth is not such a bad thing. After all material living standards were largely the same from the Roman times all the way through to the beginning of the Industrial Revolution, the last 200 years have been the exception rather than the rule. And furthermore, there is more to life than material things.

    Nonetheless there are I think good reasons for wanting economic growth. Firstly it is nice not only for individual people but for humanity as a whole to progress. Also everything from our politics to our economics works better when we have it. As Peter Thiel points out, if we have no economic growth, i.e. the proverbial pie is not getting any bigger, then suddenly democracy, which is based on a spirit of win-win compromises, turns into a zero-sum world where for one party to do better another has to do worse, a breeding ground for societal division and even political extremism.

    So given that we have established technology growth and the economic growth it brings is worth having the question then is who is going to give it to us? There are a number of candidates.


    With limited technological growth our politics have become increasingly zero-sum. Given our transition to a welfare state as well as the high debt levels it is extremely difficult for governments to have the political capital and financial capital to invest in big technology projects. In the past, this was not the case with the government being instrumental in, for example, both the Manhattan Project and the Space Race. However, both of those programs were possible because there was an outside threat to motivate them (Japan and the Soviet Union respectively). I heard that both China and India are looking to ramp up their own respective Space programmes so it possible this could be a productive rivalry although the obvious downside is the threat of real war.

    There is also the usual argument of creating ‘innovation friendly’ tax codes and laws. Peter Thiel has argued that areas like energy and medicine have suffered because of over regulation where the government has tried to prevent bad outcomes at the cost of eliminating the chance for good ones. There is a trade-off because innovation is messy and requires lots of experimentation, even something as scientific as science, and arguably we have become too risk averse. In contrast, the only two areas that were not regulated were the only two areas that experienced innovation: computers and finance, although with finance we perhaps got the balance too far the other way!


    Universities are unique in that a lot of research that goes on has no immediate payoff. This is good for two reasons 1) there is more to life than creating technology growth and 2) a lot of the most valuable projects are those with no immediate payoff and therefore outside the scope of business. Even though I do not think it is possible for everyone to be employed in high skilled jobs (among other things because of the time constraint) clearly education is very important for future technological progress. I think one measure that would be useful would be to outsource some of the undergraduate lectures because not only might it improve the quality of teaching but more importantly it would also free up more time for professors, to do what they do best, which is to focus on their research (I have written a long article on this topic and I also have a little start-up project on this, contact me for details: hellolao8n@gmail.com).


    I think the fundamental problem with Economics is that is operates at the 2nd order, its’ about fine-tuning but does not have the power to make big changes to economies. Progress towards more and better economic theory will therefore also be of 2nd order importance. At the heart of Economics is the fundamental assumption that if Economists (largely through governments) do good economics, that creates the best possible conditions for growth then growth will happen. I would argue however, that most of the big macro variables we care about are ultimately out of the control of both our Governments and our Economics.


    Start-ups are wonderful because they allow new ideas, products and methods to be tested with limited risk (from a society standpoint). Some of the most famous companies today including Disney, Amazon, Apple and Google were literally founded in garages. And there are several more that were founded at university or by drop-outs such as Facebook, Dell, Microsoft, Virgin, Oracle, McDonalds, Slok Group, Hutchinson Whampoa and General Electric. I certainly believe that much of the technology required to automate many of the ‘menial jobs’ we discussed above may come from start-ups as they are probably primarily robotics and software problems which are not too capital intensive.

    Nonetheless many of the biggest and most important projects, particularly some of the more fanciful science-fiction projects, require investments into the hundreds of millions or even billions well beyond the scope of most start-ups with even the best possible venture funding. As an example, Elon Musk who made more than $300,000 million co-founding PayPal could not find sufficient outside investment to fund his rocket ship company Space X and his electric car company Tesla and instead had to invest all of his personal fortune to save the two companies in the Financial Crisis of 2008. Clearly if we require big projects to be tackled by billionaire entrepreneurs who are willing to risk all their personal fortune then we are greatly limiting our chances for technology growth.

    Big Companies

    So really our best bet should be big companies. Peter Thiel in an event on technology growth with Google’s Eric Schmidt argued that Google’s failure to invest the $50 billion or so it has sitting on its balance sheet proves that Google has insufficient vision to put that money to good work. Schmidt countered that Google has done lots of innovative projects and that there are other limits to innovation than a lack of money.

    The most obvious of which are diseconomies of scale and the well documented failures of big companies to innovate. Robert Lutz of General Motors Company who led the development of Chevrolet’s electric car ‘the Volt’, after seeing the success of Tesla Motor’s electric car, said it was embarrassing that it took Elon Musk’s Tesla, a start-up car company in Silicon Valley to show what was possible before General Motors a company with billions of dollars in revenue to make the same leap. Especially as General Motors, with competition from the Koreans and the Japanese, had presumably very strong incentives to innovate. One problem I think Management as a discipline should look to solve is how to build firms that do not suffer from diseconomies of scale, whether the solution is the right incentives, the structure of the firm etc. Part of the problem I think is that academic research is often impenetrable, if for no other reason that the volume of research, to an ordinary entrepreneur, who with limited time already, is not going to be able to sift through to find relevant papers that could help him run his company better. One alternative firm structure that I think that might work is rather than the top-down approach to resource allocation which you have in most companies, where people play politics to get into positions of power and influence, you could instead have a venture capital model of resource allocation within companies where ‘managers’ would be pitched to by teams of employees who want investment for projects. These ‘start-ups within companies’ could then benefit from all the economies of scale of big companies without the downsides.

    The lack of innovation from big companies may also be due to a lack of high skilled labour. This may be in part because genius is rare; it may also be an education problem. I do think another problem that needs to be solved is the importance of ‘culture’ and teamwork skills within firms. To put it bluntly a lot of ‘creative people’ are not ‘corporate people’ and so that genius is left untapped because unless they found a company themselves (like Steve Jobs) they do not get past the interview stage or climb the management ranks. One answer could be to systematically introduce teaching these soft skills into the education system. Another alternative might be to structure firms so the soft skills matter less.


    If our future is one without technological growth then I think our best bet is to try and transition to an economy with technological growth, where we have big companies, start-ups and universities focusing on automating our list of ‘menial jobs.’

    With this successfully achieved we can then transition to an economy and society where most people do not work, living off the transfers from the welfare state. Even if my proposition is only partially true that still might mean economies with 20 or 30% unemployment, numbers that would be intolerable today. There will still, of course, be scope for big technology projects as well as the more general progress in the arts, science and business although their high-skilled nature and ‘the time constraint’ will mean these will not be particularly labour intensive.

    If Technology Growth does lead to unemployment then what then?

    I wrote an article in which I argued that technology growth will lead to mass unemployment and sent it to my friends asking their opinion on it. Although it was a radical and very contrarian view no one thus far has been able to convince me that it’s obviously wrong (pending further feedback!). Therefore after a couple of months I suddenly thought it might be cool to try and think through what, if on the off-chance my narrative about technology destroying jobs is correct, what that would mean for the world and crucially what the required transition to that new form of society and economy would look like. I think the end equilibrium of a society with mass unemployment is actually quite an attractive one, my Dad even joked that I thought up this essay because I want to live in a world where I don’t have to work! However, the more I think about the transition the more I think it will be fraught with difficulty. Ideally I’d want to be able to outline a blow by blow account of what I expect to happen but the big issue I’m struggling with is the sequencing of events. It would be cool if there was some framework to help think through the issues but I don’t know of any. So, instead in this essay I’ll try and outline a few dimensions that I think are worth considering.


    I think if the Government still maintains the opinion that the country is capable of continuing as a low unemployment economy then there is a real danger of misguided Government Policy. In an interview with Charlie Rose legendary fund manager Jeremy Grantham argues that even now the government is too optimistic:

    Jeremy Grantham: ‘I think Bernanke is whipping this donkey that can only grow at 1%, because he thinks that it’s a race-horse that should be growing at 3. So he’s gonna keep whipping this donkey. Charlie Rose: ‘This donkey can’t run.’ Jeremy Grantham: ‘Until it either drops dead or turns into a racehorse.’ Charlie Rose: ‘And you’re betting on dead.’

    Accordingly if the Government expects low unemployment it may in an effort to stimulate the economy print too much money leading to inflation or go into unmanageable debt trying to stimulate the economy. Perhaps dangerous is the fact that with high unemployment there could be great political instability and perhaps even the potential for extremism to take hold as we saw in 1930’s Germany after the Great Depression. If my assertion is correct it is therefore vital that everyone is educated and persuaded that a low unemployment economy is no longer possible.


    Although I suspect the long-run equilibrium of high unemployment might be fairly stable with those who work only being those who enjoy it and/or earn extremely high returns for their work in the short and medium term there is potential for huge instability.

    I think a central problem is that even if most menial jobs eventually get automated this will be a gradual process. As an example, I heard that efforts are being made to create a gate like the one that you walk through at airport security which as you push your trolley through scans all your items and bills you automatically. So let’s assume this technology works and therefore the cashier job is one of the first to go. Suddenly you have a lot of unemployed people. Can you start giving them the high standards of living that would be possible in a full roboticised society? Well if you did increase the welfare benefits to a comfortable level then suddenly all those people working in the undesirable, low paid jobs that have yet to be automated, let’s say cleaning jobs would choose not to work. Leading to either much higher wages for these undesirable jobs or perhaps those jobs just not getting done. Alternatively if you keep welfare at a low level then I think as unemployment year on year increases you will get more and more unrest potentially leading to the political instability and extremism already cited.

    I think one idea would to help foster a more peaceful transition would be to have education extend later and later into life and retirement to occur earlier and earlier. This gradual erosion of the number of working years might act as a escape valve for all that unemployment pressure.


    However, I think even the long-run equilibrium is fraught with a major problem which is international competition over tax revenues, i.e. the tax paying companies and workers. Countries in a bid to attract the limited number of companies and workers lower taxes because if the tax base is very small then welfare benefits have to be lowered potentially leading to civil unrest from the unemployed. Even if successful in attracting said companies and workers it comes with a cost which how did you get those workers and companies? Well lowered taxes and therefore lower welfare benefits and potentially the same problem as before of civil unrest among the unemployed.

    Even if international cooperation and taxes could be agreed upon there are other factors that lead to the choices of where companies and people choose to locate. As it is impossble to have a completely equal distribution of companies and people across different countries this could lead to conflict. The only solution I can imagine is for a world wide tax and welfare system which would require such radical changes in our government and societies it’s hard to see it happening smoothly, if at all.

    My first exposure to Economics came in the afterglow of 10 years without recession and discussion in the UK that Gordon Brown had finally beaten the boom and bust cycle. However, just at the moment I started studying Economics the greatest Depression since the Great Depression happened so inevitably I, like many of my generation, am on the look out for other assumptions that are perhaps unfounded. Although I’d hate to be pessimistic I think it is an interesting thought experiment to wonder what it would take for two major powers to go to war with each other. I suspect differences in ideology is unlikely to be a sufficient criteria (especially if one of the parties is a democracy) but economic unrest caused by mass unemployment and international migration of the best workers and companies seems unfortunately very plausible.


    Finally, I think there is a question about the nature of identity and a good life in a world where most may never work. I think given the previously mentioned issue this is a relatively minor issue and ideas about how to have a fulfilling life are ones that I’ve explored in my previously cited technology leads to mass unemployment essay.

    Ideal High School

    In this essay I am going to outline my dream school and some of the ideas about why I think it would work well. I admit that the following school would probably be impractically expensive but at least it would give us something to aim for.


    What is the point of education? I think ultimately it’s to create successful people, specifically world-class experts and high-skilled professionals. Of course given the make-up of today’s economy most jobs are neither of the two but hopefully with time our economies will develop such that low-skilled roles are automated. It is possible that the job market is fundamentally demand constrained where even if supply increases quantity does not but for now I am going to assume away in the long run the zero sum nature of the job market. For an analysis of this please see my essay about the ‘trade-off between technology and employment.’

    Given that context, what then is the fundamental problem with education today? In a word generality. and to elaborate, generality at the cost of expertise. Underlying all that follows is an assumption about the marginal benefits of learning, particularly that after an initial upspike when you first learn the basics of a subject and how it can you teach you to think about the world the marginal benefit is very low until you reach a point of expertise. There is no better example of this than languages where after the initial taste of a new culture the language has virtually no value until you can break through to the point where you can have day to day interactions. Then beyond that, the marginal benefit is again relatively small until you approach real fluency.

    Too often in education we get trapped in one of the two valleys. How common is it to hear students say why am I learning this? Or I spent all that time studying and I got good grades but I’ve now forgotten everything I learnt.

    My ideal school is built around avoiding the valleys and aiming for the peaks. Theresa Amabile, Harvard Management Professor did a ground breaking study where she asked the question was is the key to having productive and happy employees? Interestingly, it wasn’t compensation, it wasn’t titles or the status of the firm. It wasn’t having a ping pong table in the office or even doing your dream job. What mattered was the employees felt like they were making a little bit of progress in something that was important everyday. Contrast that with most students experience of school which is not making progress in something that seems really unimportant: when am I ever going to use trigonometry in my lifef? And uniquely as a consumer experience, education is the one place where if as a customer you have a bad result it’s your fault! No wonder so many students leave school never wanting to learn another thing again! So the second problem I think with generality in gaining a well-rounded education you lose the sense of progress.


    First think to note is my ideal class timetable is both long and infringes on the weekend. School on Saturday I think is no problem because I had that since I was eight and I think as a child as long as all your friends are in the same boat it does not really matter. In writing this I imagined a boarding school hence making the late night lessons and private study sessions feasible but even if students went home I see no reason it should be any earlier than 7pm. Not only does it buy more time for the school day it also I think makes it more convenient for the parents as many parents now work. I should emphasise that homework would be fairly minimal with most traditional homework being done in class time with the teacher on hand to help if there are any problems. Lectures would largely be outsourced to education companies that focus on creating compelling learning materials. Salman Khan’s Khan Academy is a good first step in this direction.

    So now time to walk through the class schedule. The first section to notice is the blue blocks which consist of the traditional academic subjects: Maths, History, English and Chinese. I believe these subjects are not only valuable for the fact they can teach you a way to think about things but also because the knowledge is intrinsically valuable.

    With the higher number of hours studying Maths and with better teaching all students would not only learn to an A-Level competency in general Maths but beyond that in Statistics where the focus would be on a practical understanding of statistical programs and manipulation of data. This would give students a valuable job market skill that would be useful in most roles in most industries. Some would argue that it is not possible for all students to attain such a high level in Mathematics and Statistics. I would disagree because I feel that in the ideas discussed below it is possible to teach in a significantly more effective way.

    History would be learnt not only with the view of learning about the past and the opportunity to expose oneself to different influences but also as a way to learn how to write and dare I say it how to think. One downside to learning history I think is that many of the major debates such as the causes of the First World War feel very stale and as a student it can feel like there is a right answer. Wouldn’t it be cool therefore if some time was spent studying conspiracy theories and having vibrant debates about why they are or are not true? This is not only an important life skill but also a valuable asset on the job market.

    Chinese and English would be studied to build competancy in those two languages, although of course Chinese here is only used as an example and could be swapped for a language of the students choosing. I have in my time studied Chinese, French, Russian, Latin and Ancient Greek and despite doing well in exams am unable to speak any of them! A classic case of being trapped in the first valley. I am a firm believer that you cannot improve in anything if you spend less than five hours a week at it especially something cumulative like a language. In addition to throwing more hours at it I also think learning languages could be done more efficiently. Firstly less than that you spend most of your time trying to not to forget what you’ve learnt rather than actually learn new things. Secondly irstly the two highest leverage activities to learn a language are one vocab learning and two have real life conversation practice. More specfically two students would stand in front of the class with one student orally translating English sentences into Chinese with the other translating them back into English. And thirdly I think in language learning there is too much emphasise on correct grammar and pronunciation, as a beginner this is not important. Instead the aim should be for students to be able to speak without inhibitions such that they can understand and be understood, this is very different from speaking accurately. It is amazing how many students I have met at Tsinghua whose exam English is very good but when it comes to having a conversation they are too terrified to say anything. Finally learning another language in addition to your mother tongue is of course another valuable asset in the workplace as well as a window into another culture.


    Our enemy remember is generality and so students would pick one creative discipline, one physical discipline and one wildcard (the red blocks) to spend at least five hours a week working at. Although of course it is possible that the disciplines they choose may evolve into passions or even careers the real focus is on learning how to learn and experiencing the process of setting goals, making progress and becoming more of an individual. Students when they are younger would be free to switch disciplines every six or even three months and sample lots of different activities but as they got older they would be expected to settle down into one or two disciplines for years at a time. Students would with their teachers choose their goals and agree how they will be evaluated against their goals. Students would learn to compete against themselves rather than defining themselves compared to other people. Students will take responsibility of their own learning with the safety net of the core academic subjects would have the freedom to genuinelly choose areas that interest them.

    Teachers and schools would become enablers. Say a student wants to learn how to paint teachers could help arrange visits to art museums or for local artists to come and visit. If a student wanted to learn how to play football teachers could help organise a trip to see a football game or an opportunity to trial at a local football club. I heard a story that #1 chess player in the world Magnus Carlsen when he was 12 or 13 would alongside a few other grandmasters spend hours just talking through various situations. That’s the kind of tailored learning experiences that students want and need. Many people complain that they have no opportunity to contribute so imagine if schools ran mentoring programmes where local people have regular contact with students structured around a discipline they are interested in. How awesome would that be?

    One problem of course would be designing curriculum for all these diverse topics thus having outsource companies that you could buy at the very least teaching materials from would be very useful.

    Too often I think as an educational system we are afraid of specialization too early because what if the child misses out on other opportunities? What we forget is specialization too late also means missing out on the opportunity to really develop one area and know it intimately and be excellent at it. After all, in a specialized economy where excellence often requires starting early and working hard many children are not afforded the opportunity to try and go pro at something because they didn’t put enough hours in at a young enough age. As Confucius said ‘the man who chases two rabbits catches none.’ We should be more afraid of students catching no rabbits then catching one rabbit but not two.


    Despite my criticisms of a general education there is absolutely a lot of value in being open minded and having lots of influences. However, I feel that this process does not have to be an academic one wrapt in the frankly energy sapping process of preparing for and taking exams.

    The short sample lessons would be a chance to gain exposure to lots of different influences. Each one and a half hour lesson would vary from listening to Korean pop music, studying tectonic plate theory to learning about the life of Steve Jobs. The longer sample session would be a chance to delve deeper into one subject; particularly for example big ideas in science like the Big Bang Theory and Evolution. Again to help a tutor with the sheer number of diverse subjects that would have to be prepared schools course outsource teaching materials and lesson plans to education companies. They could also be used to build skills like public-speaking or touch typing. Each semester students might be asked to create presentations or write essays about a few of the topics they learnt or to research topics of their own but again the focus would be not be on exams but rather exposing the students to lots of interesting influences and helping the kids to be curious about the world and open-minded to its possibilities.


    With the sheer number of class hours spent on the core subjects outside of big projects and preparing for exams I think homework should be kept to a minimum. If there was scope for private study though it might be to help students who are struggling. Teachers would tutor one-on-one to help students with problem areas. This would also benefit teachers to help them understand where students are struggling better. Too often teachers are not aware that students are falling behind until the end of year exams. In our ideal school of unlimited resources this is not acceptable.


    The academic year would be long but I think students would be more willing to endure because school would be more enjoyable. Also to achieve excellence at the end of the day takes a lot of hours, 10,000 of them if Malcolm Gladwell is to be believed. Having said, that the academic year can be structured to take advantage of the ebs and flows of motivation and focus. What if each year you had two week Maths camps or two weeks in Washington actually learning American history first hand? The focus on one subject would not only help students break through plateaus but also break the monotony of the academic year. It might also be a good way to add academic variety to the curriculum ,what if after summer examinations you had a month of studying different subjects? Swapping out maths, english, history and chinese for physics, computer science, economics and design. This might also be a good way to introduce an academic taster to students so that they can in the last ¾ years of high school choose additional academic subjects to study on top of their diet of maths and history. Imagine if students studying Italian spent as a 14 year old a year in Italy? Not only would this help them with their language study but would expose them to a new culture at a young age when they are still open minded. Also I think it would be extremely challenging. One downside to our modern culture is we coddle our children too much. We forget that many of our ancient cultures had challenging rituals for children to go through as a passage into adulthood. Much like Sparta’s (extreme!) habit of having their sons spend a night out in the wild with just a spear to protect themselves we should not be afraid of throwing our children into the proverbial deep end lest we be left with thirty year old children!

    Narratives about China and Assumptions About the Nature of Innovation

    It’s commonly accepted that China’s startling economic growth over the last few decades has been built on copying the technology of the West. As a developing country it only makes sense that China would pick the lowest hanging fruit of imitating developed countries technologies first, but nonetheless the consensus is that China is inherently incapable of innovating itself. There are two common narratives as to why this is the case:

    1. Culture
    2. Education system

    China’s culture is too respectful of elders, too caught up in looking to its glorious past for inspiration, too tied down by its Confucian values. This is in contrast to America where the contrarians are the most celebrated and where questioning the status quo has itself become the norm. China’s education system is criticized as too focused on rote learning and not enough on deep understanding. In fact China’s falling behind the West with the dawn of the Industrial Revolution is often blamed on the demanding civil service examinations which wasted China’s best talent, preventing a similar scientific revolution as the one that occurred in Europe, taking place in China.

    The problem with these narratives, though there may be truth in them, is they are difficult to verify or refute. Thus the culture or education system could change but the narrative doesn’t reflect that. In short, what would convince us that these narratives are wrong? This problem is especially dangerous because as place-holders they are intellectually very satisfying, they feel like they make sense and they may match with our day to day, anecdotal experiences. There is little argument that China lacks the innovative companies that America has but why that is not obvious at all. The why matters of course because it affects how China and all developing countries can best hope to develop its innovative capabilities. In fact I believe hidden in our commonly accepted narratives about Chinese culture and its education system are entirely unobvious assumptions about the nature of innovation itself.



    Is Apple’s great products because of Steve Jobs, the talented researchers at Apple or because the American education system is churning out lots of talented programmers. If attention was a guide then you would say that individual genius matters a lot. But it is possible of course that Steve Jobs’ contribution is much less than is commonly accepted, but because he was the leader of the organisation we’ve attributed all the success to him. Another example of this phenomena is in football management where I suspect the manager matters much less than the players but who gets all the blame if things go wrong? The manager. Why? I think part of the answer might be because our cave-man brains have a bias towards overvaluing the contribution of the leader. In particular, our societies are built around competitions that allow marginal skill or ability differences to amplify into huge status differences. A great example of this is good looks. To an alien unaccustomed to human culture, the huge status differences between those considered good looking and not good looking would be completely arbitrary and probably imperceptible. In my own life, growing up in the west the first time I saw Korea’s famous 9 member girl band Girls Generation I could literally see no differences between their faces. But now after a few years I have trained my eyes to see differences that literally where not evident to me before and now I feel that some of the girls in that group are unbelievably beautiful and others not. So therefore my hunch is that our brains have a similar bias towards leaders where we massively overvalue their contribution.

    This of course needs to be verified in data, although anecdotally there was an article which tried to rate the 100 most important inventions in human history in the magazine ‘the Atlantic’ and the interesting conclusion was how few were the results of individual acts of genius but rather tended to be works of (often indirect) collaboration.

    Why this is important of course is the type of society that produces a lot of geniuses probably isn’t the type of society that produces a population of skilled workers. Consider the government targets for numbers of students who are educated to at least a university level. If we really believe that innovation is the product of individual geniuses rather than a generally well educated population wouldn’t it make sense to take the billions of dollars that go into educating those masses and allocating that money to selected geniuses as venture capital. Sure many would fail and our society might be a bit less meritocratic but we might go so much more innovation that its a worthwhile trade-off. Arguably if we are just waiting for geniuses to come along then maybe there is nothing we can do to speed that process along. We can’t turn an average guy into the next Mozart.

    Alternatively maybe what matter is the pool of talent available to companies to hire. Peter Thiel who is skeptical about the level of innovation in America outside computers challenged Google’s Eric Schmidt saying Google isn’t innovative because it has 50 billion dollars that it doesn’t know what to do with. Schmidt’s response was that the other limitations to innovation besides money namely engineering talent. In fact a common narrative in America is we need to increase the number of science and maths graduates but if we find that actually what matters is how many Steve Jobs we have maybe we don’t need any more engineers.

    An example of how these assumptions can be hidden is in Justin Yifu Lin’s book Demystifying the Chinese Economy where he argues that’s China best talent was wasted taking the gruelling and in terms of innovation pointless civil service examination. It is not obvious though that those people would otherwise have been the great innovators.


    The general narrative of breakthroughs tends to be by definition a break from the past. I think if you look at the number of movies and books that are about the underdog triumphing I think there is reason to believe that as human we are drawn to breaks from the current hierachy, they are narratives that are inherently appealing to I guess everyone who isn’t King. But of course, the reality of what’s important to innovation might be different.

    A common narrative about Steve Jobs is that he wasn’t limited to just one discipline and that being able to draw from different areas, broadly both art and science, he was able to create better products. If this really is the key to innovation then shouldn’t we look to evolve our curriculums to encorporate Kirby Ferguson’s idea that creativity is not a case of eureka! but rather just combining two old ideas into a new one – a mashup? Shouldn’t we teach the skill of combining ideas from different disciplines?

    If rather innovation is deeply about breaking from the status quo then shouldn’t we look to intentionally create societies that have individuals and companies that routinely break with the status quo? Perhaps rather than having standardized education testing we should sacrifice some signalling and sorting of talent for a more diverse and non-uniform society?


    Which structure of human organisation best fosters innovation is extremely important because obviously we want more of the ones that work and less of the ones that don’t work. I was listening to a lecture by the Physics Nobel Laureate by Steven Weinberg at a SXSW conference where basically he was hoping to drum up public support for a bigger, better and crucially more expensive version of the Large Hadron Collider. My hunch is that as humanity progresses more and more progress will depend upon riskier and very expensive projects that can not be organised and funded at a individual, startup or university level.

    I’m currently reading Neal Stephenson’s Quicksilver which is a fictional account of the Royal Society with guys like Isaac Newton and Robert Hooke. What is particularly striking is how the only real barrier to entry for these guys is not having to have a normal job and most experiments can be done on the cheap. Now though that is not the case I think (with except perhaps the recent history of internet companies and the early innovations in computers). The proverbial lowest hanging fruit has already been picked.

    It is crazy that as a society electric cars (with Tesla) and space travel (with SpaceX) have relied upon a someone (Elon Musk) not only making hundreds of millions of dollars in internet businesses but then willing to invest all of that money in entirely unrelated and highly risky businesses that he himself admitted ‘most likely outcome was failure’. If the progress of human civilization depends upon that sort of event occurring over and over again progress is going to be very slow if not non-existent.

    Therefore I would argue we need to re-organise our big companies and governments to take large risks. For a long time capitalism has been sufficient but I suspect many projects because of their high likelihood of failure and limited short term prospects of a profit are not possible to achieve in the business sphere and need to be government funded.

    With regards to big companies lack of innovation, if you read much of the creativity literature particularly that which fills your local bookstore you would come to the opinion that the most important factor for innovation is releasing the talents of your workforce. That everyone is capable of innovating and the big problem with big companies is the lack of democratization of creativity. My hunch is that although this narrative feels good it is probably completely wrong and that actually one of the main reasons that big companies don’t innovate is the over democratization of power so that no one person can steer the company into trying one, risky, course of action. Instead companies are built to avoid taking risks by allowing no one person to have so much power they can do anything stupid. However, in doing so it might also mean that they can’t do anything great either. The obvious piece of evidence for this is the success of companies that keep their founders. Perhaps it is because the founders are inherently geniuses or perhaps a factor is that their founding status allows them to hold unnatural monopolies of power over their company, they can get more things done than a typical CEO.


    One of the narratives that is presented by Beida Professor Justin Yifu Lin in his book ‘Demystifying the Chinese Economy’ is the idea that China was initially ahead because before the scientific revolution technology progress relied upon farmers trial and error, experience based experimentation. Therefore because China had a bigger population than Europe it had more technological progress. However, with the scientific revolution suddenly technological progress dependent upon scientific experimentation and so the population advantage became irrelevant. This narrative however is unsatisfying because many of the so called scientific inventions that Europe used to overtake China China had already invented, things like gunpowder, the mechanical clock, the compass and movable type print. My point therefore is to ask maybe the distribution of a technology is more important than its invention? And tied into the distribution is the mass production and lowering of costs in producing the product. Which is more important effects the type of institutions we try to build to create more innovation.


    The main thrust of my essay is that as Economists maybe we are too eager to use Economic tools to solve Economic problems. There is the old joke that to a man with a hammer everything looks like a nail. I think the same is true with Economics. When it comes to innovation, why so much attention is put on the level of tax rates or level of regulation is not obvious to me at all. What evidence is there that the things that economists can easily control are the things that matter most in determining the level of innovation in a society? What I hope my essay does is start to get me thinking about the specifics of how innovation works, rather than thinking about it in generality. Generality is obviously attractive because it means your model is more powerful, more scalable, but maybe it’s not possible to say anything interesting at a general level and that policy should be done on a case by case basis.

    One paradox that I keep butting my head up against is why so many smart people have worked away at Economics all these years and yet we are still unable to manage our economies very well. Maybe the answer lies in the fact that the tools Economics seeks to exploit, primarily that of government policy, is inherently second order and that to some degree economists and governments are simply along for the ride. The principle conclusion of the Solow Model of Growth is that although things like savings and changes in capital can in the short-run increase growth in the long run the only option is technological growth. Given that this conclusion, which was made in the sixties, makes me wonder why Economics is not a study, primarily, of innovation and how to create it? Or alternatively, as a thought experiment, imagine a government that employed all the worst economics policies possible it chose the wrong tax rates, the worst interest rates etc. but despite all that it had year on year massive breakthroughs in technology and innovation. Would that be a successful or a failure of an economy? Or an analogy might be we are currently trying to win football matches by tweaking the rules. Offside rule or no offside rule? Bigger goals or smaller goals? Diving is tolerated or not tolerated? Asking ourselves what conditions allow our football players to succeed. Maybe we should instead spend our time focusing on making sure that our football players are really good and the specific rules under which they play the football games don’t actually matter that much. In short, whether it’s on a small pitch or a big pitch, with a heavy ball or a light ball Barcelona players are always going to beat a pub team.

    My hunch is that societies need to organise themselves to take big and expensive risks. And that the best vehicle for this is for big companies to compete for government contracts. What if rather than our current approach to technology innovation which is very non-specific, i.e. let’s create conditions that entrepreneurs like to innovate in but rather much more hands on. What if the government wrote a list of ten big human problems, or more positively areas for human progress. Maybe solar energy, using computers to personalize education, space travel, curing cancer etc. and then funded multiple research groups in pursuit of those goals. This structure by the way was stolen from exactly how NASA commissioned private companies to service the International Space Station (a contract which was partly rewarded to Elon Musk’s company SpaceX). Maybe that would be much more effective at fostering innovation then fiddling around with interest rates or what regulations we need to manage our economies?

    University Education & The Professor's Problem

    Despite the flurry of attention that education reform has received in recent years, from the scalability of online learning, to the failures of the K-12 system one perspective that is too often left unconsidered is the plight of the university professor. We put the responsibility on professors and universities to not only be the centres of innovation, pushing the frontiers in human knowledge and understanding but also to be the pinnacle and perhaps even heart of our education systems. In no sphere of human endeavour, not in business, in sports or in politics do we ask those who are most excellent to also bear the brunt of the responsibility of teaching the next generation, unless that field of excellence is unfortunate enough to be on a university campus. And yet rather than praise we vilify, rather than reward we complain. I too believe that progress in university education is not only possible but necessary; I’m not denying the problems that exist. On the contrary, I’m arguing for their resolution but a resolution not through a complete rejection of the institutions that have given so much to us over the previous decades as has been proposed but rather through a hybrid model of technology and university that will offer the best of both worlds.


    For decades people have talked about how technology will finally bring change to the seemingly unchangeable. Of course I’m talking about lectures: the process by which one person stands in front of rows and rows of silent and attentive students, talking and occasionally writing on a board, a teaching method that has stood the test of 100s of years, stubborn to innovation, may finally be broken.

    Generally though when we talk about the benefits technology can offer to university education there are two main narratives. One is the extension of education’s reach and power to the poor, for those for whom traditional education isn’t an option. Online learning is cheaper, more scalable and even offers an affordable chance at lifetime learning.

    The second narrative is that of competition, the new replacing the old. The campus university system is broken and we should replace it with the online experience. However, online education for all its cost-efficiency lacks the richness that campus universities can offer: whether it’s face to face interaction between professors and students in seminars and around campus, or networking opportunities, personal growth and life experiences. Not to mention the huge signalling power that incumbents like Harvard in the US, LSE in the UK and Tsinghua in China can offer its students. An online experience taken to its extreme would lose all this richness in favour of 5 year old children in a darkened room, alone, staring at a computer screen for the next 20 years: a learning experience we can all agree is not likely to produce the kind of educated and well rounded citizens we would all want.


    There is a third narrative though, one that is too often left untold. That is one where technology is used to enhance not replace the universities we have. As a thought experiment imagine a new type of university where everything is exactly the same! You would still have seminars with teachers and students interacting face to face, and you’d still have the same physical buildings and campuses, except let’s change one thing. What if lectures were watched on a computer rather than in a lecture hall, this would allow students to pause, rewind and replay in a way you cannot do in a real-time lecture. Taken even further, with adaptive learning technologies the computer experience is more and more able to approximate a 1-1 tuition experience where your learning material is catered to suit your needs. Find topic 3 hard? Here’s another explanation or some more practice problems. Find topic 4 easy? Then whizz on through.

    In fact, not only might this sort of online learning be comparable to traditional lectures they may even be superior. First of all, because students are doing everything on a computer suddenly educators will be awarded a wealth of data, particularly for the more mathematical-type subjects about what topics students find the most difficult, what explanations work best, there may even be insight into the study habits of students. All this data can be used to personalise and improve the learning experience.

    Better technology doesn’t necessarily mean better courses. Great technology has existed for a while, now it’s about writing better courses that take advantage of this technology.

    This personalization has become a buzz-word in entrepreneurship circles but I think often these start-ups are misguided. Too often they focus on general, scalable (and therefore profitable) fixes to teaching and learning problems. But for anyone struggling with matrix multiplication for the first time, these technological fixes will seem largely irrelevant, there is too much focus on the technology and not enough focus on actually using this technology to write better courses, that is where the real value add is. Although only a humble graduate, I have tried writing my own lectures on a few university subjects. A few videos I put online about linear algebra for example have garnered comments such as:

    ‘If you are not in the United States, please come visit and replace 90% of our linear algebra professors. I am confident that these 7 minutes of your lecturing make more sense than an entire semester under their instruction.’

    ‘Agreed. An entire generation of human beings unable to employ mathematics because instead of getting this guy for a teacher, we get Captain Rigorous Mathematical Proof, who never explains his notation and is shocked when someone has a question.’

    ‘You are…AMAZING!’

    ‘Thanks, that really clarifies things!

    ‘Thanks so much for posting these videos!! I finally understand!!!’

    ‘Why don´t we get professors like this?’

    ‘The awkward moment when your learn more from a youtube video in 7 minutes than you did from lectures for a whole semester’

    ‘this is much clearer than the lecture i just had in class. thank you very much! ‘ ‘oh my goodness THANK YOU!’

    ‘all of a sudden, it all makes sense. thank you so much.’

    Now of course, just because a few students found my videos useful doesn’t’ mean they all did, nor does it mean that all university professors are bad at teaching, in fact many are very good. This is not the point I’m trying to make. Rather I hope this shows the extent to which the odds are stacked against the professors in terms of teaching well.


    First off you are lecturing in front of 100+ students who you probably rarely get to interact with, in fact many may not even bother showing up, so you may not even know what some of your students look like, let alone how you might teach them better. And then to add insult to injury your pay, rewards and remuneration are heavily stacked towards your research work, which by the way teaching requires you to do part-time and suddenly people are surprised if your teaching isn’t world-class. Furthermore, the university education system asks some of the smartest people in the world, men and women who – particularly in the mathematical fields – have spent decades trawling through the dense and demanding frontiers of their subjects to relate to an average student who is having trouble with some of the basic definitions and derivations of that same subject. In my own small way, I understand how frustrating that can be: for the teacher. I tutored a boy who got a D in GCSE maths and needed a C and I can tell you trying to explain concepts that are so second-nature and sub-consciously intuitive to me to someone who is completely confused by them is an almost impossible challenge, and I had the good fortune of spending hours after countless hours one-on-one with him.

    One comment I got from someone who saw my linear algebra video was:‘That’s a great analogy, they always help me understand things. Why couldn’t my lecturer do the same??!!!!’

    I think part of the answer is the intuition of the subject is so ingrained for most professors, and for so long that it’s hard to imagine a situation when that wasn’t the case. So of course, in my own little case as a mere graduate I have nowhere near the understanding or knowledge of a professor but paradoxically I may be able to teach a given subject better exactly because I don’t know as much.

    I would like to finish by asking a question: what is the most valuable resource at a university? The answer I think is a professor’s time. The hours they spend lecturing, teaching in seminars and individually in office hours and let’s not forget writing courses is immense, and it’s time not doing research. It’s absurd that with so many people going to universities and the extent to which there is standardisation across universities in what is learnt that more (although not necessarily all) isn’t shared. What if one great teacher in linear algebra wrote and gave the video lectures for everyone studying linear algebra in the UK? Or what if there were a few education companies, driven by profit, writing foundation lectures for courses for universities, their professors and their students to choose from? Would that not lead to better outcomes?

    Right now Professors’ time is wasted because even if the professor is lecturing it’s time spent trawling through algebra or talking about the consensus causes of the Second World War. What possible value add is our world-class professor having there? What if you took that 2 hours of lecture time and asked the professor to go through the harder material or to add their own unique, more nuanced perspectives, or put the basic materials in the context of contemporary debates. If there is anything archaic about university education it’s people ideas about what a Harvard or an LSE education should mean. Just because students might learn the bones of say linear algebra online from the same video course provider that would by no means mean that Harvard and LSE would therefore be offering the same educational experiences. In fact rather than diminishing the differences it would enhance them, you would really be interacting with the professors at each university in a meaningful and valuable way.


    And finally, putting the education question aside let’s remember the other purpose of universities: innovation. In a world where growth in the developing countries may be predicated on copying the developed and where those same developed countries struggle with stagnation and heavy debt the future looks bleak. In the past we have looked to governments to be the leaders in innovation such as with the Manhattan Project or the Space programme, but as, in particular, democracies have evolved into welfare states, trapped in 4 year political cycles and burdened by heavy debt it is unlikely governments will be the crucible of future innovation. Nor perhaps will business, particularly with the short-term focus of even Silicon Valley’s investors. Only at universities can projects be worked on where there is no hope of immediate payoff and yet it may be these very projects that lead to the greatest innovations. Education reform should not be about working against universities and the professors that inhabit them but rather working with them, giving them a fighting chance to do all that we ask of them.

    Alternative and Complementary Approaches to Sovereign Credit Ratings

    ‘It is a feature of many systems of thought, and not only primitive ones, that they possess a self-confirming character. Once their initial premises are accepted, no subsequent discovery will shake the believer’s faith, for he can explain it away in terms of the existing system. Neither will his convictions be weakened by the failure of some accepted ritual to accomplish its desired end, for this too can be accounted for. Such systems of belief possess a resilience which makes them virtually immune to external argument.’
    Keith Thomas, ‘Religion and the Decline of Magic’

    In this essay I am going to outline Standard & Poor’s (S&P) approach to rating sovereign risk and offer my thoughts on potential limitations and weaknesses. I will suggest two alternative and I think complementary approaches to rating sovereign risk that in addition to S&P’s current approach would I believe provide a more comprehensive assessment of sovereign risk.

    The essay is divided into two parts. In part one I will attempt an unadulterated explanation of S&P’s current approach and the rationale for doing it this way. In part two, I will offer my criticisms of their approach and suggestions on how to improve it as well include ideas on what would convince me that I’m wrong.

    Part One: S&P’s approach to Sovereign Credit Ratings

    Sovereign credit ratings are opinions on the future ability and willingness of sovereign governments to service their debt obligations to the market on time and in full. On time and in full is important because no attempt is made to try and predict the exact nature or extent of default. The reasoning is that default is an extreme event (with an average of roughly one a year in the last fifteen years on S&P rated countries – which is pretty much everyone at this point). Default is so extreme that predictions on if it happens, rather than specifically how, are sufficient. Willingness to pay is the crucial quality that separates sovereigns from the usual companies and organizations S&P rates because companies have clear and immediate legal repercussions for not servicing their debt whereas sovereigns face much less clearly defined economic and political costs.

    Although it is not explicitly stated, forward-looking estimates should be at least a year and it was explained to me that non-investment grade have a two-year time line and investment grade has 4-5 years. Technically the ratings are not absolute because they are not tied to any specific underlying metrics. And in fact, pre-1975 the ratings were primarily done through peer comparisons before a more formal framework was put in place. However, it is not correct to say they are purely rankings or that they are fit to a curve because although of course they seek to be, in each time period, internally consistent and offer an accurate measure of relative credit worthiness, they should also be (at least since 1975 when modern ratings methods were put in place) fairly consistent over time and different classes or organizations. Ratings are offered for both local currency and foreign currency debt; the latter is of greater interest because it offers easier international comparison. There is also the more mechanical reason that foreign is calculated first and local is usually just an uptick on the foreign view.

    Because overall creditworthiness is a function of both political and economic risks S&P’s rating approach is necessarily both quantitative and qualitative. Qualitative approaches are particularly necessary when assessing willingness to pay. In all there are five key criteria that are considered when rating sovereign debt:

    Economic structure and growth prospects; Political institutions and considerations; Government budget considerations (fiscal); Monetary flexibility; External liquidity.

    Economic structure and growth concerns the underlying economy and ultimately the tax base that the government of a country can draw from. Stronger underlying economies make for more resilient governments. Political institutions and considerations concerns both stability and transparency issues. Generally the more stable and transparent (which often correlates well with western democracies) the more reliably you can expect countries to pay off their debt. Government budget considerations assess factors relating to the government’s balance sheet. Monetary flexibility assesses the effectiveness and availability of monetary tools whilst external liquidity assesses the impact of balance of payments constraints.

    These five factors are rated on a scale of one to six where one is the strongest six the weakest. These factors are combined into two averages. One is a rating of the overall health of the sovereign which takes an average of the economic structure and growth prospects score with the political institutions and considerations score to make the Institutional and governance effectiveness and overall profile score. The remaining three scores for fiscal, monetary and external are also averaged to create the flexibility and performance profile which represents the country’s ability to react to shocks. By averaging this way the result is slightly lower weights for the external, fiscal and monetary scores. These two profiles are then mapped onto a grid where bands of diagonal equivalence formulaically determine the final credit rating. The specific weights and the boundaries of the bands seem to have been chosen at the current levels primarily for legacy and arithmetical convenience but there is no obvious first-glance reason to suggest the weights are significantly off. Clearly the obvious advantage of having a systematic approach to weighing the different factors is that it makes the ratings comparable across countries even though arguably there may be some country to country variations in the relative importance of each factor. All in all, there are 18 different ratings ranging from the best AAA to the worst CC. In addition to each rating an outlook is published which can be positive, negative or stable. There are also, for very extreme events, credit watch outlooks if there is scope for a rating to turn on an upcoming event such as an appeal to a court. There are no first principle reasons for why the number of different ratings are set at 18 specifically but the main thinking behind the relatively high number is that, often times, organization classes tend to clump around a certain set of ratings. Therefore by providing a relatively high number of ratings there is more scope to offer differentiation within each organization class (whether sovereign, university, company, supranationals etc).

    Part Two: Alternative and Complementary approaches to Sovereign Credit Ratings

    In this section I wanted to fight the temptation of accepting the general approach and just nitpicking within it in favour of trying to ask if there are any fundamentally different approaches that could be made to rating sovereigns. My conclusion was I think there are and that rather than replace they could potentially supplement and complement S&P’s current approach.

    I have been fortunate enough to sit on a large variety of credit committees including sovereigns, banking and even a university. The experience was immensely valuable and really brought the ratings criteria to life and my general impression was that I was very impressed with both the level of knowledge that each of the analysts had about not only the sovereigns they covered themselves but also the highly intelligent and diverse set of questions they asked each other. Of course, all the discussions are strictly confidential and I shall respect that here but nonetheless I will start this section by making generalized impressions about their approach, which I accept are only my perceptions, but nonetheless despite this might still perhaps have some grain of truth to them.

    The problem of using the model that higher general health means a bigger buffer against disease approach

    My overall sense of S&P’s approach to rating sovereigns is that although perhaps the exogenous shock that pushes a country over the edge is largely unpredictable there are long-run build ups of poor fiscal standing, exposure to foreign markets, increased political instability which are completely predictable. In fact it was explained to me that there are no ‘fat tail’ defaults; everything is in the realm of prediction. Therefore the general approach is to try to assess the state of the sovereign with the idea that sovereigns in stronger positions have greater buffers to endure the inevitable shocks that come along. By analogy, if a sovereign was a person and default represented death they try and assess a person’s general health and therefore ability to withstand the inevitable barrage of diseases that the person will come in contact with in the course of a lifetime.

    My primary issue with this approach is that the exogenous shocks are treated as completely unpredictable. Returning to my analogy, S&P’s approach is to keep track of all the factors that might affect a person’s health from cholesterol, to blood pressure, to liver function etc. and then from this develop a generalized view of their health (and therefore the size of their generalized buffer) against a generalized disease. Instead, I think there should be some thinking on specific diseases and each person’s unique exposure to and risk of each disease.. With the human analogy you would take the main causes of death, from cancer, to heart attack and stroke, and try to assess each person’s individual risk of each separate cause of death. This is important I think because I expect there is probably a high degree of heterogeneity among sovereigns in not only causes of default but also therefore exposure to the different types of default. Person A may have no chance of dying from lung cancer but have very risk of dying from a heart attack. To then take an average of the high risk of a heart attack and the low risk of lung cancer and say the person has an average risk of dying I think does not fully communicate the true risk of death. I suspect S&P would argue that causes of default are not independent and you would probably need several to occur simultaneously rather than just one. Nonetheless having sat in the credit committees I cannot help but feel that the ratings, especially with the extreme attention paid to adjusting them up and down the 17 notches, are more an assessment of the general health of the economy rather than a forward looking prediction about actual default. Using the human analogy I feel that a person who eats 5 fruits a day would probably get a better health rating, using the S&P methodology but the actual relationship of the number of fruits you eat a day and whether you are going to die soon is not clearly established and essentially there is an underlying assumption that better health, no matter how marginal, means lower risk of death.

    The problem with short-run trend from equilibrium + shock analysis

    The second problem I think is the short-term nature of the ratings. Long-term ratings on sovereigns are important to investors because sovereign bonds, for example, are often five even ten years in length. I concede that no official position is taken on the actual timeline of the ratings but the general agreement is that should be around the three to five years for investment grade and two to three for non-investment grade and certainly have scope of greater than a year. Having listened to the rating committee discussions though, the feeling is that they are six month or perhaps very generously one year predictions. In the admittedly small number of meetings I have attended rarely did anyone ever try to make predictions beyond six months except to say, for example, that there is political risk and who the hell knows what is going to happen and that that uncertainty should be reflected in a notch down in the ratings as a sort of safety margin. One exception to this would be clear inflection points around elections etc. but in general I heard no attempt to make predictions on worldwide trends and how they make effect a specific sovereign. The obvious rationale for this is that any predictions beyond one year would quickly become highly speculative so instead the approach is to give a, in my opinion, very accurate picture of the country’s position today with buffers for uncertainties. Recently in an attempt to add stability to the system new regulations (although I’m not sure if this is for all countries or just for Europe) were introduced to only allow ratings agencies, outside of exceptional circumstances, to change their ratings every six months and at predictable times so that the market has stable expectations. The resulting approach, I think, is that the ratings end up tracking and describing the risk of default rather than actually predicting it. In fact, in reading the research most trend predictions would take the form of change in A has been caused by B. Perhaps it would be beneficial to firstly establish more concretely (probably through statistics) the B explanation and secondly if it held up to go further with the predictions by predicting changes in A with predictions about changes in B.

    Of course, the question is how can you predict something which inherently, is probably, quite unpredictable. One of the advantages I think of the six month to one year approach is that you can basically use short-run trend from equilibrium + shock analysis. Over short time scales trends have a very high predictive power especially when coupled with expectations of short-run shocks and their likely effects on bumping up or bumping down the trend. The resulting analysis therefore feels much less based on underlying macroeconomic theory or a view on fundamental dynamics but rather just a short-run extrapolation into the future. The problem, of course, is that sovereign risk is not so short-term, especially if you are signed up to a bond say, that is of ten year or longer time scales.

    Now I should caveat all these comments with the reminder that the realm of macroeconomic predictions is a graveyard of great economic thinkers and for that reason I think the short-run trend from equilibrium + shocks approach that S&P takes should actually be the primary ratings method. But rather than implying to the market that these are actually mid to long-run predictions I think it should be more explicitly stated it is a short-run view on the health of the sovereign which in normal circumstances should be very highly correlated with long-run default risk.

    With that short-run approach as the meat and vegetables of the rating I think there could then be scope for longer-run more speculative predictions. These would, as I outlined in my piece (available on my blog) on Frodo Risk, involve trying to categorize default risk into different and distinct narratives. And just like you would separately evaluate the risk of cancer, heart attack etc. rather than try to rate a general risk of death you would, for sovereigns, separately analyze the long-run risk of the different default patterns. You might still want to still have one overall rating because ultimately the market does not really care on how a default comes about just if it does but I think starting with a consideration of the distinct causes and then taking some kind of average is superior to a purely general approach. Thus the research on distinct causes of default could involve speculative predictions about global trends and how these might affect the different sovereign countries. Currently S&P’s approach is to assume these global risks are largely unpredictable, which given that no one in positions of influence in academia, business or politics predicted the Great Recession of 2008 is perhaps a reasonable assumption, and treat them like exogenous shocks. Nonetheless even if the long-run analysis just involved a tree-diagram of different scenarios and how each would one effect risk of default I still think that would be valuable resource for investors.

    I also think there could be scope to try to use macroeconomic (and perhaps econometric) models to make long-term predictions for potential exogenous shocks and how sovereigns will be, in all likelihood differently, affected. Finally, I understand the aversion to econometric modelling and its related tools, particularly when it comes to the actual ratings process, but I think a small team of motivated econometricians could uncover a wealth of relationships and rules of thumb that could help anchor the sovereign analysts’ considerable knowledge and intuition to fundamentals. It might also ensure that there are no biases or false intuitions. This would be particularly valuable in examining assumptions about what matters in terms of actual default risk. I would concede that the relatively small sample size and number of defaults, at least when compared to say company ratings, would somewhat restrict the scope and power of statistical methods but nonetheless I still think it would be immensely valuable. I have no strong feelings about having 17 notches although I suppose if there was some first principles approach that could be used in deciding the classifications that might be valuable also.

    What would convince me that I am wrong?

    On the general health point I suppose that if it was shown that you generally need all the averaged factors S&P uses to go bad to have a default and that there is a very strong relationship between general health (as a buffer) and risk of default I think then perhaps the current approach would be justified and sufficient. Also if defaults either followed completely different patterns every time or the same pattern every time, I think you could argue that there would be limited value in trying to consider, using my analogy, different causes of death separately.

    On the comments I made about S&P’s short-run trend from equilibrium plus shocks approach I suppose the only reason for not supplementing it is that any long-run predictions would be so speculative and in all likelihood wrong that they would have great risk of confusing rather than informing. Another thing that would change my mind is if it were shown that short-run default risk was highly correlated and therefore itself a predictor of medium to long-run default risk. Given the stability of the investment grade ratings and comparative volatility in the non-investment grade ratings this seems to be true for high ratings but perhaps not true for lower ratings. Again the question of can we do better is not clear but I think if we cannot then there might be a case for being more honest about the long-term reliability of the ratings.


    This is only day four of my work experience and just like with my Justin Yifu Lin ‘Comparative Advantage Following’ essay I concede the absurdity of offering my musings but currently it is not obvious to me why I am wrong so I would greatly appreciate any comments that you have. My emotions over the four days have varied immensely. Initially I felt S&P’s approach was completely wrong but after seeing it in action and being immensely impressed with the breadth and depth of the analyst’s knowledge I felt like it was completely right. Having just written the essay though I have, at least for now, settled on the feeling that although S&P’s current approach to rating sovereigns is broadly correct it might be valuably supplemented by both econometric analysis and attempts at predicting the long-run shocks. I would add as my final comment that it is always worth thinking what would the reaction be if something went horribly wrong? How would the press and public react if it was discovered that (quite reasonably I might add) ratings were done in this way. I think there might be a backlash where even though rating agencies can’t be expected to predict all defaults they will nonetheless be blamed for not being able to do so.

    Chinese Language Course

    You’ve got to make sure that whatever you’re doing is a great product or service. It has to be really great and I go back to what I was saying earlier that if you’re a new company… where there’s an existing market place against large entrenched competitors then your product or service needs to be much better than theirs. It can’t be a little bit better because then you put yourself in the shoes of the consumer and you say why would you buy it as the consumer? You’re always going to buy the trusted brand unless there’s a big difference. So a lot of times an entrepreneur will come up with something that is only slightly better. And it’s not, it can’t just be slightly better. It’s got to be a lot better.’ Elon Musk – Paypal, SpaceX, Tesla.


    In my life I have tried and failed to learn Ancient Greek, Latin, Russian, French and Mandarin. Despite the endless hours, very good grades and the fact I was fortunate to be studying at arguably the best high school in the UK (Westminster School) I have never been able to have a basic conversation in any of these languages. I don’t mean just today but even when I was actually learning and passing exams in them. I always attributed this to my own lack of ability to learn languages, I didn’t have the gene for it. Recent events though have forced me to reassess, in particular having just spent the past year at Tsinghua University in China I can now speak Mandarin. Badly admittedly, but speak nonetheless. In fact, several of my best friends in China could not speak English at all.

    However despite this successful outcome even that learning experience I feel was not optimal. For example, going to China to study with a classroom of foreigners defeats the whole point of going to China at all because inevitably you make friends with your classmates and end up speaking to them in English not Chinese. This interestingly was the case even when our Chinese was easily good enough to have the same conversation as we were having in English. Classes were four hours a day stretched out for two epically long seventeen week terms which even the most driven would struggle to maintain a high work ethic for. And furthermore, there was little student teacher interaction, with most classes involving the teacher reading from a textbook. I was fortunate because learning from my friend’s experience I had actively avoided making too many foreign friends instead trying to mix with locals as much as possible. I found it was having natural day to day conversations with my friends, not attending class, that really improved my Chinese. But still, it was hard not mixing with classmates and by the end of the year most of my closest friends were foreigners and in fact I had several classmates who hadn’t made a single Chinese friend all year!

    Despite all these flaws, this is still much better than my previous experiences learning languages where, because I had just two or three hours of classes a week not forgetting what you had learnt the previous was hard enough, let alone actually improving.


    I think the solution is very simple: focus and immersion. The best way to learn a language is to be immersed in an environment where for twenty-four hours a day all communication is in the language you want to learn. The obvious problem is that you first need to learn the basics of a language before you can reap the benefits of immersion.

    The two graphs above I believe describe the typical language learning experience. On the left is the marginal benefit curve, i.e. the benefit of every extra hour’s effort. On the right is the total benefit curve. I argue that after an initial spike in benefit, whether it’s getting exposed to a new culture and language or perhaps being able to say a few words on holiday, very quickly the marginal benefit of every extra hour you spend studying a language drops very low. That is until you reach the level where you can have basic conversations in the language and make friends. At that stage there is an uptick in the marginal benefit signified by the hump in the middle of the marginal benefit curve. Once you can have basic conversations and friends in a language there is another long period of limited marginal benefit to every hour you study because it takes a long time to get to the level of true fluency where you can write and express yourself like a native. For this second long period of limited marginal benefit the best, and really only method, for language learning is immersion.

    For the first valley though immersion is not an option and so I propose intensive language camps. The big advantage of this is that I feel the learning curve is much faster if there is greater focus. Secondly, people can sustain very concentrated work ethic for a week or perhaps even a month but maintaining a proportional work ethic over years, especially when you feel like you’re not making any progress is very difficult.

    Initially I thought it might be possible for someone to jump from complete beginner to basic conversational fluency but I have since been persuaded that this is probably over ambitious. Therefore my current best guess as to the optimal way to learn a language as an adult would be to first have a one or two week intensive beginner course where the focus is getting to sentence construction as quickly as possible. That would be followed by perhaps six months of the more typical three or four hours a week where the primary focus is on maintenance but this would also allow for perhaps a gradual build up in vocabulary as well as general increasing familiarity with the language. This would then be followed by an intense three to five week course which would aim to get the student to complete basic conversational fluency. Ideally, the student would then the day the intensive course finishes get on a flight to the respective country to immerse themselves for at least three months and get real world practice using the language. As I mentioned previously, studying at language schools has the serious disadvantage that you don’t really immerse yourself because all your classmates are foreigners. The provisional best solution my friend and I came up with is that, for example if you are a Japanese language student after the intensive course you would go to Japan to live with Japanese university students, studying at a Japanese university but living in an apartment outside. Perhaps to make it worth their while the language student would pay a disproportionately large share of the rent. In return the language student would be immersed all day every day with Japanese speakers and crucially would have an instant social circle of local friends. Initially I thought that a language learner might try to enroll in a masters course where there is limited need to understand the teacher, a good example might be an art course but this seemed unworkable.

    The big advantage of just living with university students but not actually attending university of course is that with no academic pressures the language learner will have the time to enjoy the local culture. A big problem I think with short-term language programmes is that your motivaton to study is directly diminished because this is your one chance to live in the country and inevitably rather than spending every minute locked up in your room studying you’d rather be about experiencing the country. This is exactly what my British friend found when she spent five weeks studying Korean in Seoul, she didn’t really want to study because there was so many things that she wanted to go and see. By separating the intense language program from the immersion I think you can get the benefit of both. Obviously, the intense language programs as well as the several months living in a foreign country are not easy to manage if you are in a full-time job so our primary target customer base would be university students. Having said that, as it is becoming more and more acceptable to change jobs and change companies it is not entirely inconceivable that a person might have six months off which they want to spend first learning another language and then living in that country.


    As I mentioned, my initial plan was to go straight from beginner to, for Chinese at least, what I felt was the minimum vocab requirement of about 600 words. I should mention that Chinese is unique in its relatively simple grammar (although this is offset by its lack of an alphabet)! But nonetheless I feel that there is too much emphasis in language learning on accuracy, particularly grammatical accuracy. In reality, what matters is that you and your friends both understand what each other is saying most of the time and that you can match normal conversational speed. My initial plan was to learn 600 + words in less than two weeks but after getting feedback from my friends I realized that this was overly ambitious and so I reduced the first intense language program to less than 200 words and just seven days.