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.


    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.

    The lessons would be everyday from 8am to 10pm with 8 hours of classes a day. The classes would be structured in a very specific way where the first 15-20 minutes would be spent learning six new words. Those who are more ambitious or perhaps already have a familiarity with the language can learn the writing but the priority would be on the pronunciation and the tones. The remaining 40 minutes of each hour long class would then be spent translating aloud English sentences into Chinese sentences. Crucially the English sentences would, in addition, to being written with correct English grammar, would also be written with Chinese grammar. This would indirectly help familiarize students with the structures as well simplify the translation process.

    As an example students would spend twenty minutes learning the following six words in Chinese: today, library, I, go, university, possessive (i.e. ’s)

    They would then, in front of the class, be asked to translate aloud the following: Today I went to my university’s library. [Today] [I] [go] [I] [possessive] [university] [possesive] [library]

    Where the first sentence is the meaning in correct English grammar and the second in correct Chinese grammar. Their partner would then upon hearing the Chinese translation be asked to translate the sentence back into English. In this way students would spend most of their time on the two highest leverage language learning activities: learning vocab and practicing conversations.

    I should add that the other guiding philosophy to my way of teaching is repetition and so a lot of time will be spent revising words that have been learnt. And in fact, in addition to specific hours spent revising old vocab a lot of the vocab will naturally come up in the sentence structure practice. Finally, each day there will be about an hour of optional, it would take place in an extended break between lessons, of culture lessons where students could get exposure to famous Chinese singers or films etc. In practice this would just involve watching videos on YouTube etc. Ultimately the more interested you are in the culture the more motivated you are likely to be to want to study the language. This is especially important if a student is going to spend several months living with locals. The number of my Tsinghua classmateswho had never heard of famous actors like Angelababy or famous singers like Jay Chou was truly astonishing to me.

    Finally in choosing the vocabulary to learn I decided to be very adjective and verb heavy and very noun light. The reasoning being verbs and adjectives are much more important when it comes to constructing sentences, making friends and having daily conversations then nouns.

    Frodo Risk


    I’m a big science fiction and fantasy fan and one of the towering works of the genre is J.R.R. Tolkein’s The Lord of the Rings. At its heart the story is about the battle between good and evil pitching a fragile alliance of men, elves and dwarves against the rising powers of evil led by Sauron and his orcs of Mordor. Sauron does not have a physical body but rather takes the form of a great, all-seeing eye perched on top of a tower in Mordor, the so-called Eye of Sauron.

    He is forced to take this form because he was actually killed many thousands of years before but had managed to survive on by tying his life force to the ‘one ring.’ This ‘one ring’ is paradoxically both the source of his strength but also the eventual tool of his destructive. Frodo Baggins, the most unlikely of heroes being just a hobbit from the Shire, takes the ‘one ring’ and after a terrible journey across Middle Earth manages to destroy the it in Mount Doom and with it Sauron himself.


    The story is instructive I think because it has similarities with the recent recession. Sauron, I’m sure knew that he would die if the ‘one ring’ was destroyed and therefore should have considered all the ways that this might happen, despite the fact it would have seemed very unlikely. In fact, knowing that the ‘one ring’ could only be destroyed in Mount Doom he should have started with the ‘one ring’s’ destruction and worked backwards to consider all the possible scenarios that this highly unlikely event might happen and crucially what the tell-tell signs leading up to the event might be because oftentimes you can only see something if you are actively looking for it. Returning to the recent recession, although of course econometrics, statistical programs and economic modelling are all very powerful tools they do have the very obvious drawback that they fundamentally work by assuming that the future will look like the past therefore all it takes to lead them astray is the historically unprecedented! I believe that econometrics modelling should be complemented with what I like to call ‘Frodo Risk’ analysis.

    Bi-annual report

    My idea then is for a bi-annual report that would be bought by investors to give them a systematic overview of the world economy and possible causes of systemic risk. It would only be bi-annual because a) the report would likely take a long time to prepare and b) investors do not have that much time to be constantly reading updated research. Ultimately the aim is to help highlight possible long-term build-ups of systemic risk and so the limited frequency I think would not be a problem. It is important the report would, at least attempt to, be systematic because I think one problem with a lot of current macroeconomics research is it feels like in-depth journalism. However, much like how the ‘eye of Sauron’ can be distracted from seeing Frodo, I believe sometimes journalism can be distracted from seeing the build-up of systemic risk by the latest hot topic.

    The report would be divided into 100+ mini analyses. These would be structured thus:

    Obvious categories of potential systemic risk to consider would be: ‘asset class bubbles’ ‘war/terrorism’ ‘environmental/weather/global warming’ ‘natural resources, energy crises’ ‘inequality, democratic political unrest’ ‘debt’ ‘bankruptcy of major companies’


    In just writing that small piece on a potential bubble in American University education I already find myself being forced to think hard about issues that otherwise I might not. I think a report of a 100+ or so of these potential causes could realistically hope to, within that hundred, catch any major cause of global economic systemic risk. For the potential investor therefore to, on a bi-annual basis, read a report on all these potential causes would, I think, help very much in first offering alternative perspectives on their portfolio’s risk profile and second possibly inspiring their own research into a specific asset class etc.


    [Michael Burry’s] got Asperger’s syndrome which makes him even more interesting because in fact it ties him back to the other characters. All the characters are in one way or another socially cutoff, isolated either by volition or by syndrome. And as a result they are not hearing the signals, they are not hearing the same music that you and I would, ‘they’re looking at data’ ‘they’re looking at data or they are filtering it through their own peculiar imaginations. But they aren’t part of the Wall Street social world. And in some way or another they are not hearing the propaganda. Asperger’s syndrome is not a bad metaphor for what it was about them, this isolation, this self-isolation’ ‘uncomfortable in social situations’ ‘or didn’t like them.’ Michael Lewis in an interview with Charlie Rose on his book The Big Short and the people who correctly predicted the 2007 sub-prime Financial Crisis.

    This essay is a follow-up to my previous article on ‘Frodo Risk.’ In that essay I argue that the problem with statistical approaches is that they rely upon the assumption that the future, at least in some way, mirrors the past. This assumption leaves them exposed to the historically unprecedented. Much like how Sauron, the evil leader of Mordor from the Lord of the Rings, fails to predict (and prevent) Frodo Baggins from destroying the one ring in Mount Doom I believe that standard macroeconomic modelling approaches fail to predict recessions because recessions usually have some element of the historically unprecedented. It is like the famous quote that ‘generals always fight the last war.’

    It should be emphasized that the failure of macroeconomic modelling is not partial but total. I recently read an article written in 2012 by IMF economist Prakash Loungani in which he points to the astonishingly appalling record that economists have in predicting recessions.

    In 2000, I wrote in the Financial Times that “the record of failure to predict recessions is virtually unblemished.” A dozen years and many recessions later, there is little reason to change my assessment. My initial conclusion was based on my findings that only two of the 60 recessions that occurred around the world during the 1990s were predicted by private sector forecasters a year in advance. About 40 of the 60 recessions remained undetected seven months before they occurred. As even as late as two months before each recession began, about a quarter of the forecasts still predicted positive growth for the country concerned. With my colleagues Jair Rodriguez and Hites Ahir, I’ve since looked at the record of forecasting recessions over the decade of the 2000s and during the Great Recession of 2007-09. Let’s consider the 2000s first and restrict attention to forecasts for twelve [sic] large economies—the G7 plus the ‘E7’ (emerging market economies–Brazil, China, India, Korea, Mexico, Russia and Turkey), which together account for over three-quarters of world GDP. There were a total of 26 recessions in this set of countries. Only two recessions were predicted a year in advance and one of those predictions came toward the turn of the year. Requiring recessions to be predicted a year ahead may seem like an unreasonably high bar to set.

    This should be incredibly surprising. After all, alongside delivering sustained economic growth, the most important contribution macroeconomics could make to society would be the prevention and eradication of recessions from our economies. Failing that, macroeconomics should at least be able to deliver long-term, accurate prediction but as we have just seen from the Loungani article this is not the case. Some would argue that economics is just too complicated, human systems are just too complex, which I concede they just may be. But I still think it is fascinating to note that in no other area of human endeavour have you had so much raw brain power, human expertise and competitive incentive systems (academia and finance) and yet had so much failure.

    My solution to this problem of predicting recessions is to start with imagining all the possible causes of systemic risk, with the guiding principal of: if it is big just imagine what would happen if it would go bad? Then with this list of hundreds of potential ‘Frodo Risks’ you would then try to work backwards and crucially figure out what would be the tell-tell signs that the imagined crisis is slowly developing. Finally you would then track all of these hundreds of potential ‘Frodo risks’ and try to spot potentially systemic threats as they develop. Of course, underpinning this approach is the idea that recessions are long-term predictable which again I concede they may not be. The timing issue is interesting, and my initial idea about how to guess the time of when the market cottons on is to track FT or Economist articles about the issue and correlate an uptick there with a market wide understanding.



    There are four guiding principals to my idealized systemic risk research firm.

    The first is that you cannot see something unless you are actively looking for it. I think this is especially true in economics where any coherent economic model will almost always have plausible explanations for whatever is occurring. In fact, the standard economic modelling approach of current equilbrium + trend + exogenous shocks makes it very easy for long-run build ups (for example in leverage) to be justified because well look it’s only slightly higher than it was six months ago and six months ago it was perfectly fine!

    The second is the value of the outsider, someone who isn’t hearing the music. The problem is how to acquire a detailed understanding of something and yet not become indoctrinated into that way of thinking. One of the advantages that outsiders have is that they can risk asking the stupid beginner questions that an expert cannot because it could potentially reveal an embarrassing lack of basic understanding. I would also add that being an outsider is not just in the sense of a specific industry but also in terms of personality. If you think about most of the examples of people who saw the housing bubble as profiled in Michael Lewis’ ‘The Big Short’ and Gregory Zuckerman’s ‘The Greatest Trade Ever’ many of them had serious social problems. The best example of this is probably Michael Burry who has Asperger’s syndrome and a full suite of personality quirks. In most of working life, particularly in big corporations, eccentricities are punished and it tends to be the socialized and like-able that rise to positions of power and influence. When it comes to something like economics research though the hiring preferences can and should be a little different.

    The third is that creativity, as suggested by Steven Johnson in his book ‘Where Good Ideas Come From’, is largely a function of diverse influences bashing together. Therefore to be more creative you need to proactively expose yourself and your ideas to a diverse range of influences.

    The fourth is the importance of what Robert Greene in his book Mastery calls negative capability. This is the ability to be comfortable with not immediately understanding something. This is the idea of not giving in to the need to have an opinion about everything but instead continuing to wrestle and play with the idea. In my own small way, many of my best and most status quo challenging ideas have come only after months of mulling them over. John Cleese, of Monty Python made the same point when he gave a lecture on creativity

    Well, let me tell you a story. I was always intrigued that one of my Monty Python colleagues who seemed to be (to me) more talented than I was {but} did never produce scripts as original as mine. And I watched for some time and then I began to see why. If he was faced with a problem, and fairly soon saw a solution, he was inclined to take it. Even though (I think) he knew the solution was not very original. Whereas if I was in the same situation, although I was sorely tempted to take the easy way out, and finish by 5 o’clock, I just couldn’t. I’d sit there with the problem for another hour-and-a-quarter, and by sticking at it would, in the end, almost always come up with something more original. It was that simple. My work was more creative than his simply because I was prepared to stick with the problem longer.

    Work practices

    To produce a bi-annual report the working year would be broken into two six month parts. There would be a 5 week break over Christmas and an 7 week break over Summer. This would allow every six months for twenty weeks of working time to produce a report. This would be a sizable increase in holiday time compared to a typical employee which I think would offset the relative inflexibility of when people can take their holidays. One major advantage of such long holidays is that I think it would allow people to spend part of the year living in different countries. I watched a TED talk with the founder of a prestigious design firm who every seven years closed down the firm for a year to allow him and his staff to have a year sabbatical and be exposed to new influences. Clearly an economics research firm cannot just take a year off but I think it could valuably benefit from the long holidays.

    Each 20 week block would be divided into 10 fortnight working weeks where the team would work from Monday of week 1 and through the weekend to Tuesday of week 2 to make 9 straight days of working. This would be finished with five days of weekend. The value in this I think is proper recovery from the working week in a way that I think it is harder to do with just two days of rest every seven. Hopefully by having five days of rest per fortnight as opposed to the normal four people will be more willing to switch. I also think the five days could realistically be used for short holidays around the world which, I know myself in particular, would love to take advantage of to go and visit all the friends I have dotted around. The 9 days of work would be demanding with long twelve hour days starting at 8am and finishing at 8pm. The exception would be the working weekend where finishing at 5pm would allow employees to not completely lose their weekend every other week. You would probably allow for an additional three of four days in each six month period so people can have at least some flexibility with the working year. Of course, a lot of people would not be willing to work like this but I think given that research firms are very small and only need to be about ten people this should not be a problem. Additionally I think being different has the optimal advantage of helping keep people feeling like an outsider and not tied to the system.

    It is really important to have a lot of exposure to diverse influences so every day there would be three hours allocated to reading time, maybe from 11am to 1pm just before lunch and another hour in the afternoon. This would be supplemented by perhaps one afternoon per fortnight where employees could work on essays and develop ideas of their own choosing (much like Google’s 20% time). All this reading would help give employees a regular diet of different influences and the opportunity to develop new insights. Perhaps to create a diverse team of researchers peoples’ reading and interests might be tracked in an effort to maintain diversity and breadth in thinking. Clearly, although there would be a heavy bias away from fiction towards non-fiction and academic literature, you would want to allow the reading to be as varied as possible. Warren Buffett of Berkshire Hathaway said that

    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.”

    Charlie Munger, Buffett’s partner at Berkshire Hathaway said something similar

    In my whole life, I have known no wise people who didn’t read all the time – none, zero. You’d be amazed at how much Warren reads – at how much I read. My children laugh at me. They think I’m a book with a couple of legs sticking out.

    Everyday there would be a team lunch at 1pm for an hour and a half where people can get closer and exchange ideas. In general I think I would probably be against having regular formal meetings because I believe that having to defend ideas that challenge the status quo in their nascent stages is very counter-productive as ideas (especially early on) are inherently very fragile, even to the lightest questioning. Nonetheless eating together and the more informal conversation that would involve would not only bring a family atmosphere but could also be a good way to share ideas and create diverse influences. You might even want to occasionally allow members of the research team to give mini presentations about books they have read or topics that interest them. Afterwards there would be the option of a thirty minute nap which would allow for biphasic sleep patterns which help people recharge for the afternoon and also reduce people’s daily total sleep time.

    The optimal pay structure is interesting I think. My initial gut reaction was to tie pay to the performance of the firm. So have a low minimal wage at say £30,000 a year with additional % of profit to all the employees. I think the problem with this is it incentivizes high sales not good research. So my initial idea would be to keep records of the Frodo risk rating and how well they correlate with actual events and then reward accordingly. This would create very long-term incentives tied to getting the answer right.

    Finally, I think I would ultimately opt in favour of diverse influences over sectoral expertise. Therefore researchers would every six months be, probably randomly, allocated different clusters of potential systemic risks to work with the view that that would keep our thinking fresh and hopefully insightful. You might even offer each researcher, perhaps once or twice a decade, a chance to spend six months just reading, thinking and writing about whatever they want: a sabbatical in the office if you will.


    I think big financial organisations and universities make it harder for people to think creatively because they, through their big impressive buildings, implicitly intimidate their employees into accepting the status quo. This is to me very similar to how banks would try and give confidence to their customers by having big expensive buildings. Therefore I think the office should be in a non-financial district. My current thinking is a cool converted art studio in east London somewhere.

    For the team lunch there would need to be a big open table to eat together and I also think it would be good to have an office library stocked with books and kindles.

    Over time it might be beneficial to develop a suite of internal literature on what major schools of thought. Maybe even Munger-like checklists as a ward against human misjudgement. One of my favourites would be on any analysis a section on ‘what would convince me that I’m wrong?’ as well as internal quotas on criticisms of other peoples work and why they may be wrong.


    I am a big fan of Michael Lewis’ Moneyball which is a book about how the baseball team the Oakland A’s which had one of the lowest wage-bills in the MLB managed to compete with the big expensive teams like the New York Yankees by taking advantage of the mispricing of player value. I similarly believe that these same mispricings occur in the labour market for economics researchers. There are a number of biases I would try and take advantage of in my hiring decisions.

    Firstly, there is a bias in favour of well-rounded, socialized and generally pleasant people. These are all great qualities in friends but not necessarily in out of the box researchers.

    Secondly, I think there is bias discriminating against those who have had unconventional or volatile academic and professional careers. I think it makes more sense to judge a person’s ability to do good research not by their consistency but by their highs. As an example John Paulson who’s hedge fund, as profiled in Gregory Zuckerman’s ‘The Greatest Trade Ever’ made $20 billion dollars in the Great Recession, had an analyst on his team called Paolo Pelligrini. In fact it was Pelligrini who was responsible for making the shorting sub-prime trade recommendation. Pelligrini had an exceptional academic career where he came in the top 5% at Harvard and where one of his Maths professors said he was one of the most gifted students he had ever come across. His professional career, marred by poor client skills and disagreements with bosses, meant that I think he is a classic example of an undervalued asset. In fact, Ben Horowitz of venture capital firm Andreessen Horowitz talks about how Marc Andreessen is very difficult to work with and at times can be, frankly, a bit of a prick. Andreessen it is worth mentioning is a Silicon Valley legend who co-authored the first internet browser and was co-founder of Netscape. Horowitz’s point is that in normal working life you would not put up with these types of people as it would disrupt team culture but because creating disruptive companies is so hard what matters is exceptional genius and you should be willing to accept even very extreme personality flaws to get it.

    ‘I’ll take strength over lack of weakness every day… This isn’t WalMart or something; to do something new that is going to be the best in the world you need greatness.’ Ben Horowitz

    Similarly, predicting economic recessions is probably the hardest thing you can do in economics so you should be willing to trade-off likeability for genius.

    Thirdly, I think there should be an effort to employ a true diversity of people. Not just across different academic backgrounds and cultures but personality types as well. Despite the incredible (and commendable) racial diversity at most major corporations I still believe there is a striking monochromatic feel to modern corporate culture.

    Fourthly, if every six months you had advisers come in on short-term contracts to offer their perspectives I think this would really help freshen up our thinking. You might eventually even want to have several small offices around the world and rotate staff to really mix up the influences on our thinking.

    Fifth, have someone in the firm who regularly thinks about every person in the office and how they probably feel about their career. Are they excited? Do they feel listened to? Do they feel like they are important? Is there anything we can do to make their lives better? And then try and make office policies to improve things. I think this would be especially do-able if you have a small team of people.

    I’ll finish with some parting words from Charlie Munger

    It’s my opinion that anybody with a high I.Q. who graduated in economics ought to be able to sit down and write a ten page synthesis of all these ideas that’s quite persuasive. And I would bet a lot of money that I could give this test in practically every economics department in the country and get a perfectly lousy bunch or synthesis. They’d give me Ronald Coase. They’d talk about transactions costs. They’d click off a little something that their professors gave them and spit it back. But in terms of really understanding how it all fits together, I would confidently predict that most people couldn’t do it very well. By the way, if any of you want to try and do this, go ahead. I think you’ll find it hard. In this connection, one of the interesting things that I want to mention is that Max, Planck, the great Nobel laureate who found Planck’s constant, tried once to do economics. He gave it up. Now why did Max Planck, one of the smartest people who ever lived, give up economics? The answer, he said, “It’s too hard. The best solution you can get is messy and uncertain.” It didn’t satisfy Planck’s craving for order, so he gave it up. And if Max Planck early on realized he was never going to get perfect order, I will confidently predict that all of the rest of you are going to have the same result.

    In fact, when Charlie Munger was asked in 2010, in a lecture at the University of Michigan, about his views on the economy the first thing he said was

    Well let me start with a qualification. Warren and I have not made our way in life by making successful macroeconomic predictions and betting on our conclusions. Our system is to swim as competently as we can and sometimes the tide will be with us and sometimes it will be against us but by and large we don’t much bother with trying to predict the tides because we plan to play the game for a very long time. I recommend to all of you exactly the same attitude. It’s kind of a sneer and a delusion to outguess macroeconomic cycles. Very few people can do it successfully and some of them do it by accident. When the game is that tough why not adopt the other system of swimming as competently as you can and figure that over a long life you’ll have your share of good tides and bad tides.


    Peter Thiel likes to ask the question ‘what valuable company is nobody building?’ and the more I think about the more I think this Frodo Risk company is one of them. It’s been less than a month since I wrote my first article about Frodo Risk as a concept and I can’t really remember where I got the idea from but already it just has that feeling of ‘this makes so much sense, why is nobody doing it?’ Part of the problem is that it’s very difficult to execute. In particular you are trying to be simultaneously systematic and comprehensive about ultimately unknowable future events. My initial best guesses on how to do this will be the focus of this article.


    Political Uncertainty – e.g. Eurozone crisis, Iranian Revolution 1980s, US September 11th, 1997 Asian Financial crisis

    Asset price bubbles – e.g. 2008 US Housing crisis, dot-com bubble early 2000s, US 1857 railroads bubble

    Fiscal tightening – e.g. US 1937-38

    Monetary policy/Interest rate – e.g. 1980 US,

    Market collapse – e.g. US 1836-38 Cotton market

    Bank failures – e.g. US 1836-38

    Cost-push (particularly energy) – e.g. 1973-74 US oil crisis, 2007-08 food prices

    High leverage – e.g. 2008 US Housing crisis,

    Post-war – e.g. US 1920-21

    Lack of technological progress – e.g. Peter Thiel argument is bubbles form if no better alternative e.g. 2008 US Housing, Early 2000s tech bubble

    Big company – e.g. 1926-27 Henry Ford switched production from Model T to Model A closing factories for 6 months, US 1873 – failure of Jay Cooke & Company, 1857 US Ohio Life Insurance & Trust company failure

    Other country – e.g. 1980s Iranian Revolution, US 1847-48 because of British Financial Crisis


    Even if you set a low bar of predicting 1 year in advance just 25% of the recessions that occur (according to IMF economist Prakash Loungani the market 1 year in advance predicts about 5% of the time), spotting recessions is an awesomely difficult task.

    Clearly there are some shocks that are going to be beyond a few researchers in a room e.g. terrorism or natural disasters. Nonetheless I think comprehensive monitoring of asset price bubbles, government fiscal/monetary tightening and failure of one big company/market leading to general uncertainty are all situations that could be mapped out in advance with reasonable predictive power.

    Of course the whole challenge is for any research firm trying to predict recessions crying wolf is just a big a sin as missing recessions. Ultimately the goal goes way beyond selling research to a few hedge funds, really you’d want the firm (or firms like it) to become so widely listened to that their research can move markets and recessions can not only be predicted but actually prevented. But that’s a dream for the future.

    Aggressive Novelty

    This is a fun piece about a new life philosophy that I’ve developed for myself called ‘Aggressive Novelty.’ All it involves is a) developing awareness of my interests and habits and then b) systematically introducing new influences, preferably those that are very different from my current set

    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 int he 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.
    — Winston Churchill

    There are two schools of thought on what form the new influences should take. One is a form of sampling. The other is to choose less things but really let them move into your heart. Although I like sampling a lot, I prefer the latter. Part of my reasoning relates to my experience lifting weights. For several years I had the ambition of getting a bigger body but it was only after I completely immersed myself in the culture that I found I became consistent at getting myself to the gym. Part of that process for me was, willingly, watching endless hours of body building documentaries. Listening and absorbing the mindsets of top body builders like Kai Greene and Ronnie Coleman, even just watching them train is more than just a burst of short-term inspiration, it’s a long-run change in who I am as a person.

    Whilst at Tsinghua, a friend and I made our own body building documentary of my Chinese friend Tung, who is probably one of the biggest guys I have ever seen in my life. I asked him what he felt was important for a beginner and he said that the type of person who trains say three times a week for forty-five minutes, something that is more than sufficient in the long-run, is fundamentally a completely different person to the guy just starting out. Therefore if you try to as a beginner to immediately go straight to the 3x a week you will fail. Why? Because you are not that person yet. So Tung’s suggestion is to for three months make lifting/body building your life. Go to the gym five/six times a week, don’t just get in and out but talk to the other guys and absorb their mindsights, watch documentaries, even buy fancy gym clothes so you look good when you go. The objective here is not temporary short-term gains of a quick six pack but instead shocking your mind and body into a whole new way of thinking and living.



    So anyway these are list of categories that I think pretty comprehensively cover my interests and current habits.

    This include: types of friends, languages, music taste, favourite TV shows, favourite films, habitual thinking, style of thinking, my main ideas/pet theories, favourite sports to both watch, do and play, favourite thinkers and favourite books.

    As an example right now my favourite music genre wise is probably

    • Korean Hip Hop – esp. Jay Park (박재범), Verbal Jint (버벌진트), Bumkey (범키), Swings (스윙스)
    • CPOP – esp. Jay Chou (周杰伦), Rainie Yang (杨丞琳)
    • American Hip Hop – esp. Drake
    • KPOP – esp. Rain (비), Ballads like Baek Ji Young’s (백지영), KPOP girl groups like SNSD (소녀시대), AOA (에이오에이), Red Velvet (레드벨벳)

    In the future I want to pro-actively get into music that isn’t East Asian or American mainstream like house music or maybe music from Arabia or India.

    Another example might be currently a lot of my thinking is influenced by Silicon Valley culture and in particular the ‘disrupt’ mindsight. Exposing myself to how artists thing about similar problems of doing something new I think might be really interesting.


    I think there are three main benefits of the ‘Aggressive Novelty’ approach to life.

    1 Greater creativity

    As outlined in Steven Johnson’s book ‘Where Good Ideas Come From’ creativity can be thought of as a the simple result of diverse influence bashing together. By pro-actively and periodically introducing new influences I will become more creative!

    2 Transfer

    There are so many things in life that are beyond our control. I think many old people get worn down by their particular culture’s societal hierarchy, what is deemed high status and what is not. And perhaps most pervasive is the sense of what is possible and what is not. In my own small way, as a recent university graduate I’ve noticed a seismic difference in the feeling of possibility that other graduates friends and I have compared to first year students that I’ve become friends with. I find the more I hang out around them the more I stay hopeful and full of possibilities.

    I think that is why immigrants in all societies tend to do much better. They are not constrained by the collective cultural memory of what is possible and not possible to achieve. As an example, I was recently discussing with a friend how I would be very willing to live in the poorest areas of Beijing (a city I don’t know very well) but very unwilling to live in a similar part of London (a city I have lived in all my life). With London I would feel that I would be forever shackled by the feeling that I am not going to escape this place whereas in Beijing I would feel a sense of adventure and not such feeling of being trapped. Although there are lots of universals across different cultures the differences can still feel liberating.

    For example I used to think that East Asian men could never have an amazing body but people like Youtube star Mike Chang and Frank Yang have forced me to change my assumptions.

    ‘Running an ultramarathon can’t be good for you. I can’t imagine how it’s possibly good for your body,’ I said. I wasn’t biting on endurance. Running wasn’t my thing and it never has been. Brian MacKenzie laughed: ‘Good for you physically? No. But you’ll recover. And I assure you: if you run 50K or 100 miles, when you finish,you won’t be the same person who started.’ I thought for a minute and that’s when I bit. I’d seen a strange ripple effect dozens of times in the world of strength but for some reasons I’d never connected the dots with endurance. Perhaps just as you haven’t connected the dots with some subjects in this book. After all, in a knowledge economy, what’s the value of deadlifting more or losing 2% body fat? Or hitting a home run? In a word: transfer. The physical changes were incredible, but the curious side effects (the mental improvements) were the strongest incentives to continue… This book is a Trojan Horse full of unexpected transfers.’ Tim Ferriss

    3 Life extension

    Finally, I noticed that the year I was in Beijing the first month felt much longer, and my brain is packed with emotionally-charged memories, however I remember the final three or four months all sort of merged into one, one week indistinguishable from the next. My basic idea then is if I can consistently introduce ‘aggressive novelty’ then I in effect (although of course not literally) extend my life. As Einstein said, ‘time is relative!’ Of course this can get pretty exhausting so right now I’ve settled on one new thing every 3 months or so. My latest new habits include joining a Sci-Fi book club, starting to watch DOTA and LOL competitions as well as starting to meditate. The latter is something I’ve wanted to try for a long time but doing it consistently is really difficult so right now I am just doing 3 minutes a day after I shower to build the habit and then once that is established I’ll slowly increase the amount of time. .

    Also it’s fun!

    Do not go gentle into that good night, Old age should burn and rave at close of day; Rage, rage against the dying of the light

    Demand derived analysis: A new form of investing

    There are many different schools of investing such as fundamental analysis, quantitative analysis and technical analysis. This essay is an exploratory look into what I’m going to call ‘demand-derived analysis.’

    The idea came from an essay I wrote on housing, where because housing lacks an obvious fundamental to tie prices to, I instead used incomes. The basic idea was that as housing (in London at least) has relatively fixed/inelastic supply you could assume that in the long-run house prices in an area should be highly correlated with incomes in that area, in particular, your long-run views on housing should simply be a function of your long-run view on incomes. If you believe there is going to be increasing inequality in incomes across London then you should invest in expensive areas like Chelsea/South Kensington. If you believe there is going to be increasing equality in incomes then you should target poorer areas. What’s interesting about this approach is incomes and the associated maximum buying power (as dictated by lending standards etc.) mean above a certain price threshold demand just disappears (it’s not even price elastic it’s just a complete disappearance).

    What is not clear to me is how this highly budget sensitive market operates with speculators. I suppose the key question is what percentage of the market are speculators? If the number is very large then perhaps they can collectively lead to self-reinforcing bubbles with the presumption that the bubble will burst to a level that is aligned with most house buyers budget constraints. The implication, seems to be, that even in markets with a high number of speculators there is a long-term envelope which is demand-derived and a function of buyers budget constraints.

    The reason I think this is interesting is because none of the investing approaches seem to look to directly measure investors demand-constraint. Instead as with fundamental, quantitative and technical approaches the focus is more on the thing getting traded rather than the constraints of those doing the trading. The financial crisis however, would seem to suggest that – in recessions at least – the investing appetites of market participants seems to not just a factor but the most important factor in determining prices.


    The basic idea then is to try and predict the demand-constraints of market participants. Market participants rather than the safer approach of trying to find the best deals possible and then mapping those out on a spectrum of risk and reward and building portfolios accordingly instead first decide upon their required risk and reward appetites and then try to find assets that match those descriptions. I suspect this, admittedly subtle, distinction leads to lots of self-enforcing bubbles as market participants who need, for example, 10% of their portfolio to be high return, say 20%+ then go find assets that fit that description and collectively make those assets have those returns through their collective buying behaviour. Peter Thiel, the billionaire investor and entrepreneur has in fact argued that one of the reasons for the housing crisis and the technology bubble is that investors are looking for massive returns where there are none. The returns should be found in investing in technologies but Thiel argues that VCs have been too conservative focusing on the world of bytes rather than bits which has led to the weak returns in VCs and the bubbles in other markets.

    Thus my demand-derived investing approach starts with the risk-reward appetite of investors. This appetite is not so much a function of the actual risk-reward returns that are possible but rather what risk-rewards are required to be a competitive fund. Therefore if a competitive fund requires:

    10% high yield (20%+) 30% mid yield (10-20%) 40% low yield (5-10%) 20% T-bills (0-5%)

    Then this will in turn determine the demand for the different asset classes that match these different yields and my main hypothesis is that the investor demand for level of yield is the biggest factor in determining the price of assets that match each yield class.

    If that hypothesis is true then

    1) the buying power of market participants (including the a priori competitively determined portfolio yield requirements) is the primary factor in determining the prices of assets. Self-reinforcing bubble dynamics can mean that simple excess demand and constrained supply can be sustained for long periods of time – thus even if high yields don’t exist the market’s demand for them can make them appear (in the short-run).

    2) each yield band of asset class can be treated as largely independent markets from each other. Within each band assets are direct substitutes because investors chase returns wherever they can find them regardless of which asset class they are found in.

    3) In the long-run the appetite for different levels of risk is a function of the perceived level of uncertainty. Thus even if you cannot accurately predict what will happen you can still make money as an investor simply by tracking the increases and decreases in uncertainty around different asset classes and the resulting affect on demand and supply. I.e. demand = f(level of uncertainty) not a f(what will actually happen). Thus in analyzing future events you only need to evaluate whether the outcome is increased or decreased uncertainty rather than the implications of what will actually happen in the different states of the world.



    Competition risk and why all VC investors are wrong

    There are two things that everyone in Venture Capital agrees on:

    1. Most start-ups fail
    2. Returns are exponential so of the few start-ups that succeed only the biggest winners matter.

    Silicon Valley billionaire Peter Thiel wrote in his book that VCs should

    ‘Only invest in companies that have the potential to return the value of the entire fund.’

    Y Combinator’s Paul Graham has said one of the

    ‘most important things to understand about startup investing, as a business, are (1) that effectively all the returns are concentrated in a few big winners… The first rule I knew intellectually, but didn’t really grasp till it happened to us. The total value of the companies we’ve funded is around 10 billion, give or take a few. But just two companies, Dropbox and Airbnb, account for about three quarters of it.

    Ben Horowitz of Venture Capital firm Andreessen Horowitz gave a presentation where one of the slides was

    The result of this has been investors, or at least the smart ones

    1. Make lots of small investments
    2. Use the investment criteria of if this works could it become a $10 billion company?

    But of course the number and type of businesses which can be launched on a few hundred thousand dollars but with the potential of becoming multi-billion dollar companies are very small and limited. Thus it’s hardly surprising that VCs have a strong bias towards software based platforms because these are the only start-ups that fit their criteria.

    My assertion in this essay is that VCs have learnt the wrong lesson and in particular capital-intensive start-ups, where angel rounds may be in the tens of millions, could be very profitable.

    Whether I’m right or the VCs are right all depends upon why start-ups fail. This is actually an incredibly complex question where risks include founder/team risk, product risk, market risk, financial risk and execution risk. It is therefore not surprising that capital-intensive technology companies are deemed such terrible investments because in addition to all these risks you throw in significant technology risk plus much higher stakes (because they require more capital).

    What I would argue here though is that this is looking at the problem of VC investing from the wrong perspective and in particular it forgets the most important risk of all: competition risk. Companies, when they are small, understandably focus on a niche of the market but the problem is this gives the false impression of differentiation. What is hidden is that for these companies to succeed (which in terms of VC returns means being a multi-billion dollar company) there is going to be an incredible amount of convergence to similar problems. As every VC knows these markets are inherently winner takes all but every year hundreds of start-ups are funded where the long-run convergence is to the same billion dollar company/market.

    Using the above example where you have seven different start-ups this means that the long-run chance of success is already just 14% (=1/7) and that is assuming that at least one of the companies will succeed. If we take as given that no top VC is significantly better at choosing the long-term winner than another (which evidence suggests is the case) this means that there is a huge incentive to invest in companies that have no competition.


    Elon Musk’s story is remarkable because he invested in two industries which are both very capital-intensive and widely deemed to be very risky. Clearly Musk is a remarkable person but perhaps his story also speaks to a deeper truth which is that these capital-intensive industries for all the additional technology risk may actually have a better risk-reward profile than software companies because you can avoid competition risk.

    Systematic Framework for Narrative Investing

    The most basic approach to investing is to have a linear narrative of cause and effect where an opinion about the movement of one variable leads to a knock on effect in the price another variable. Of course, this sort of investing can be dangerous because it’s easy to fall prey to other variables moving against you. Nonetheless the simplicity of developing out a narrative of events seems to be sufficient to make this style of investing remarkably popular. I suppose the underlying assumption is that, if your narrative is correct then on average the other variables with be with you as much as they are against you.

    Nonetheless, even simple narratives can often rely on hidden assumptions that I feel it’s probably worthwhile to be systematic about laying out the narrative and the specific evidence that underpins each assumption.

    Doing this, especially in highly liquid asset classes, where the trade volumes and consequently market discussion is so much higher means that if there is a change in one of the assumptions you as a trader may be able to react quicker to the changing situation.


    To illustrate what I mean consider a simple narrative in which the price of iron ore depends upon the Chinese government’s decision to embark on a stimulus package or not.

    As you can see the proposed narrative is that a Chinese government stimulus package would lead to an increase in Chinese iron ore demand which in turn leads to an increase in iron ore price. The arrows between represent the assumption that one variable acts on another (β) and crucially how strong this causal relationship is. For example, to what extent does Chinese iron ore demand determine iron ore price. What is really cool about this approach is in carefully laying out the assumptions it becomes very clear what data needs to collected to test each piece of the narrative and in particular the individual investor can start to leverage the huge weight of academic financial literature (particularly Econometrics research) that exists out on the internet largely untapped. Over time this framework allows you to track a simple narrative over several months and provide a context to interpret news events within.

    For example, increase in Australian iron ore production not only increases supply but also decreases Chinese iron ore demands importance in determining iron ore prices.

    The hidden distortion of equity markets

    The structure of our capital markets and norms in accounting practises have led to an hidden distortion in our companies. Put simply, investors look for returns to equity which involves driving down labour’s share of income in favour of capital’s share.

    These selection pressures have, as billionaire Hedge fund manager Paul Tudor Jones II has pointed out in his TED lecture on ‘Why we need to rethink capitalism’, led to a significant decline in US share of income going to labour from north of 64% in 1974 to less than 57% today*. As Jones goes onto say ‘higher profit margins do not increase societal wealth. What they actually do is exacerbate income inequality. And that’s not a good thing.’ The profound implications of this is that if labour (through human capital investment) was put at the heart of the investing world, not as a cost but as a potential return to investment, then for the first time you might expect to see those companies that reward their staff the best to be those that are the best financed. The result of this may not just be a significant changes in the incentives structure of our companies but even have consequences on the level of income equality and meritocracy in our societies.

    *And by implication, potentially a way to change Piketty’s formula from r > g to one where labour’s share increase and perhaps r</= g

    Startup hiring

    A friend from university recently wrote a blog post about working at a start-up as a non-tech person. Initially I had a violently negative reaction to what he wrote because he embodies the ‘no-conviction, chasing the trend’ type of behaviour that I hate (Peter Thiel’s classic example are MBAs). However, upon reflection I think I am probably wrong and that someone like him could probably add a lot of value to a start-up. Outside of the co-founders and the first few hires (<5-10 people) I’m not sure that passion for the particular business/product is actually that important, especially if it’s substituted with a general passion for an area of technology/business etc. Employee number 11 onwards are unlikely to be key decision makers around product or company direction and as consultancy and investment banking shows there are lots of really smart and driven people who don’t need to be passionate about something to work really hard at it. I think the problem then becomes how do you make start-up hiring that works for both sides?


    For the employee

    Joining a start-up rather than an established company probably means you are going to get paid less to work at a less prestigious company but may be worth it for some people for

    1. small team dynamics
    2. greater responsibility/opportunities to learn
    3. passionate about technology/business area
    4. the (admittedly small) chance to become fabulously wealthy.

    For the start-up

    Hiring is one of the main problems start-ups face for a number of reasons

    1. Limited number of quality people want to join risky start-up.
    2. Hiring is very time consuming
    3. Competitive salaries are expensive


    My solution to the hiring problem (particularly of non-specialist business or programming hires) for start-ups is to have an Entrepreneur First type programme but for founders rather than early hires. Graduates interested in working for start-ups would apply to our ‘Start-up graduate scheme’ just like they would for an investment banking job but rather than different divisions there would be different ‘competencies’ e.g. front-end developer, back end developer, sales/business, accounting etc. Of course these would be fairly loose given that in start-ups everyone is expected to muck in. The graduates when then be rotated every six months across four different start-ups which would allow both the start-ups and employees to find a fit that works for them with the  approach them as longer term hires. For the two year period though, technically the graduates would be employees of the ‘Start-up graduate scheme’ not any given specific start-up. Finally, in addition to saying that they completed the 2 year ‘Start-up graduate scheme programme’ – a sort of practical MBA graduates could also over that time study for professional qualifications, take classes (maybe the graduate scheme could have 1 day a week of basic business, accounting, programming classes) and get high quality references from where they have worked.

    There are a number of advantages of this scheme.

    For employees

    1. Get a prestigious qualification/signalling in addition to real world business experience. If the ‘Start-up graduate scheme’ is prestigious enough even if the 4 start-ups you join all fail (and no one ever hears of them) you still have good signalling.
    2. No one (including VCs) know how to ‘pick the winners’ of which start-ups will be a massive success, so the idea that early stage employees can do any better is of course ridiculous. If wages (including stock options) were tied to the portfolio of companies that the Start-up graduate scheme works with this would allow employees (even those not working for a specific start-up) to, despite only being able to work for one company at a time, diversify across a portfolio of start-ups. Of course if you are worried about incentives you could have a 50% start-ups you’ve worked at, 50% portfolio company returns etc.
    3. You can learn from different companies and cultures and the problems they face. I suspect after six months the learning curve (as most start-up tasks are mundane) slows down anyway.
    4. Better way to build up relationships in a technology/business area through both the ‘Start-up scheme’ and the people you meet at the different companies

    For the start-ups

    1. Outsource the hiring process
    2. Although, there would be a learning curve for each new batch of employees every six months a lot of the tasks would be relatively simple and would still be a net time save (given less hiring time).
    3. A lot of employees skills are transferable e.g. sales, programming, accounting etc.
    4. With chance at prestigious qualification/CV builder can get higher quality people working at your start-up, earlier on and probably at a discounted price.

    How To Be Successful

    Compared to other areas of human expertise ‘success advice’ seems to be a relatively unhelpful body of knowledge which is surprising because being successful is something that we are all so interested in. In fact, my pet theory re: giving advice is that it is a just a socially acceptable way to show off and it is not really about genuinely helping others replicate their success but even that cynical perspective doesn’t explain why the advice that is offered (no matter what the true motives) doesn’t make replicating success much easier. There seem to be two explanations: the first is that people don’t really follow the advice or second they follow the advice but it’s not very useful. I’m not sure which is true, probably a combination of both. One thing I have been struck by is the number of successful people who advocate taking risks and following ones passions even though it is against what almost everyone I know does. The obvious explanation is that these successful people are suffering from sample selection bias where it worked out for them and so they have their perspectives skewed by this but I find this hard to believe given the large number of extremely smart people who have given this advice. I think part of the problem is that there are three fundamentally different ways to be successful in life and the belief systems and approaches that each require are extremely different, maybe even opposed.

    1. Competitive success
    2. Creative success
    3. Corporate success

    I shall try and discuss each of the three types and suggest the type of thinking required to succeed at each.



    • Sports


    • Success is inherently zero-sum and defined as beating someone else.
    • Extreme power law in returns – Michael Jordan the greatest basketball player ever is worth $1bn, Lebron James the greatest player today is worth $300m, but the 500th best player in the world doesn’t even play in the NBA.
    • Success is largely a function of execution not creativity. Messi is a very creative player but he’s not doing anything fundamentally new on a football pitch.
    • Success = talent + hard work.


    • How to deal with failure/losing – being resilient etc.
    • Being very competitive – motivation is external i.e. beating someone else.
    • Importance of work ethic (over talent).
    • Need to develop self-confidence, self-belief.
    • Selflessness of putting the team ahead of the individual.



    • Startups, Music


    • Success is still zero-sum but rather than beating someone it’s about doing something completely new.
    • Similar extreme power law in returns – but harder to tell if on path to success. Einstein was a patents clerk, Airbnb’s Brian Chesky was heavily in debt and unemployed.
    • Success is largely a function of doing something radically new.
    • Success = basic competence + radically new insight


    • Courageous about risk-taking – dealing with lack of external signs of progress/success.
    • Need a passion/mission to motivate hard work.
    • You only need to be right once. The failures/experiments dont’ matter.
    • Okay to be weird/do weird things – it increases the probability do something new.



    • Education qualifications, corporate life


    • Much less extreme power law of returns but still very competitive. Larger number of successful people – e.g. 100,000 best lawyer in the world and you are still a very well-paid partner.
    • Success is about avoiding major negatives e.g. personality problems, bad qualifications, lack of work experience.
    • People should be well-rounded – smart, sociable, team work etc.
    • Success = education + work experience + soft skills – big problems

    Advice/expertise (usually from parents)

    • Work hard so you can play hard outside work.
    • Play the game – office politics, how to win friends and influence people etc.
    • Don’t take any major risks/deviations from the standard path or risk losing the corporate route (you don’t want any gaps on your CV).
    • Grow up/be realistic/take responsibility.


    The, albeit uncomfortable, conclusion of all this is I think that it is extremely difficult to pursue more than one type of success at a time. In fact, I might even go as far to argue that each person is only has a realistic chance (at most) of one type of success. If you really, want to become that Olympic gold medal winning gymnast you are not going to be able to study sufficiently to do well in school and maintain the insurance option of being a corporate success. Similarly, the very competitive people that do well in sports tend to not do well as founders because extremely competitive people tend to copy others and fail to do anything truly creative (just think about all the dismissive things that YC’s Paul Graham and Paypal’s Peter Thiel have said about extroverted, but low conviction MBAs). Similarly, the exact qualities that helped investor Michael Burry who has Asperger’s, a glass eye and refuses to communicate with anyone except via email see what others could not and successful short the sub-prime mortgage market would at the same time made it very difficult for him to succeed in a large bureaucratic organisation. I think this explains why there is such a large disconnect between the advice that someone like investor Vinod Khosla gives and most peoples’ Mum. It’s not that the advice is bad but that it’s just not relevant to the type of success that most people are trying to pursue.The scary implication of all this, of course, is that the path I have chosen/have had chosen for me is the ‘creative success’ route where the extreme power law in returns means a very high chance of failure.

    Temporary Laws

    Elon Musk was recently asked at a talk in Germany how would you use your first principles framework to redesign society? His answer was

    1. Direct democracy > representative democracy esp. with development of fast communication (e.g. the internet) and this should help diminish the affect of special interests.
    2. Laws have an infinite lifetime and an inertial effect – to counter this laws would automatically expire unless they are revoted as correct.
    3. Have a hysteresis where you require 60% but at any point 40% or more can remove the law.

    He argues that this measures will lead to a system that better represents the true will of the people.

    From my perspective, I think that direct democracy would be (as Elon concedes) a bit of anarchy and personally I believe in quite a paternalistic role for government. However his ideas of temporary laws I think solves a very interesting problem that the law increasingly faces which is that the time when clear laws are most valuable, which is the dawn of new technologies and industries lawyers are least willing to write laws because it is unclear how things are going to turn out.

    This leads to one of two outcomes both of which are negative. The first is that the technology develops in vacuum of regulation and legal framework and only once the technologies are fully formed and the markets are developed to lawyers come in to clean up the mess. The second possibility is, I would argue, even worse which is that without the legal clarity the technological progress doesn’t occur at all because entrepreneurs and investors need some assurances that they will be protected when inevitably there are mistakes and people get hurt.

    Yesterday I went, with a friend, to a very interesting LSE law lectureabout how to create laws with the rise of artificial intelligence and potentially sentient machines. The speaker Professor Andrew Murray argued that lawyers should have a seat at the table from the beginning. Obviously commercial lawyers would be too expensive but academic lawyers should look to create formal channels through which to have a dialogue with entrepreneurs and technologists. In my own small way, have faced these same problems where my startup – which relates to a new type of loan – faces a vacuum of legal regulation. This makes it is extremely difficult to raise money from investors because it is impossible for us to answer even basic questions like ‘is this legal?’ We have had the good fortune of talking with many prominent academic lawyers in the field but they too are at pains to stress that they cannot guarantee what the future laws will be and therefore can provide no assurances one way or the other. The result is as I have suggested above 1) we give up or 2) we continue but with an absence of legal guidance.

    The obvious solution is that academic lawyers should be able to assemble small teams of experts who for all the niche and developing technologies and markets write into law temporary laws and regulations (perhaps lasting just 5-10 years). This would force academics to transition from the sometimes ‘academic’ papers they write and wrestle with the real, practical trade-offs and come to the best consensus that they can but at the same time create sufficient legal certainty to allow entrepreneurs and technologists to continue. Crucially though this academic lawyers should not be optimizing for the long-term safety or protection of consumers but rather the safe development of the industry or technology.

    I would argue that the enactment of laws and the speed at which laws are put into place need to be thoroughly reconsidered. We seem to be moving into a society where the pace of change is ever increasing and if we are not careful we may find that where society needs the law the most the law is conspicuously absent.

    Returns To Capital And Labour Independent?

    This essay is an attempt to explore the implications of human capital a little more deeply.

    In Economics we are used to thinking about how market structure (competition vs monopoly) affects (supernormal) profit levels. What is left unexplained is what determines how much of that profit goes to labour and how much goes to capital – and in fact already our economic definitions are breaking down because profit is net of costs which includes labour. A naive first cut would suggest that surely returns to labour and capital are correlated and the real determining factor is how much pie (profits) there is to share around. Certainly, the technology industry with companies like Apple seem to have high returns to capital and labour and conversely the restaurant industry suffers from both minimum wage waiters and bankrupt restaurant owners.

    However, just as Peter Thiel argues that the value that an industry gives to the world and the % of that value that a company captures are independent I would argue that return to capital and return to labour are also independent. Supermarkets are a good example of industries where the return to capital (e.g. the shareholders of Walmart) is high but where the return to labour (salary of Walmart employee) is low. Conversely, the airline industry is notorious for the tiny profit margins but airline pilots actually enjoy quite high salaries. Another example is the finance industry where I saw a lecture with the economist John Kay where he argued that investment banking CEOs were getting absurdly high bonuses despite delivering very low returns to shareholders.

    The obvious economic explanation is that the labour market has its own demand and supply which is largely independent of the demand and supply for the product/service. At a simple level, industries that employ low-skilled labour pay that labour less regardless of how much profits the industry is making, similarly high skilled labour tends to be highly paid.

    The implication of this analysis is that maybe the best industries for us to start the human capital idea in are those industries where equity investing isn’t attractive (because the companies don’t make much money) but the labour does.