Magnus Carlsen’s Endowment

Game 12 of the ongoing Chess World Championship match between Magnus Carlsen and Fabiano Caruana ended in an unexpected draw after only 31 moves, when Carlsen, in a clearly better position and clearly ahead on time, made an unexpected draw offer.

The match will now go into a series of tie-breaks, played with ever-shortening time controls, as the world looks for a winner. Given the players’ historical record, Carlsen is the favourite for the rapid playoffs. And he knows it, since starting in game 11, he seemed to play towards taking it into the playoffs.

Yesterday’s Game 12 was a strange one. It started off with a sharp Sicilian Pelikan like games 8 and 10, and then between moves 15 and 20, players repeated the position twice. Now, the rules of chess state that if the same position appears three times on the board, the game is declared a draw. And there was this move where Caruana had the chance to repeat a position for the third time, thus drawing the game.

He spent nearly half an hour on the move, and at the end of it, he decided to deviate. In other words, no quick draw. My suspicion is that this unnerved Carlsen, who decided to then take a draw at the earliest available opportunity available to him (the rules of the match state that a draw cannot be agreed before move 30. Carlsen made his offer on move 31).

In behavioural economics, Endowment Effect refers to the bias where you place a higher value on something you own than on something you don’t own. This has several implications, all of which can lead to potentially irrational behaviour. The best example is “throwing good money after bad” – if you have made an investment that has lost money, rather than cutting your losses, you double down on the investment in the hope that you’ll recoup your losses.

Another implication is that even when it is rational to sell something you own, you hold on because of the irrationally high value you place on it. The endowment effect also has an impact in pricing and negotiations – you don’t mind that “convenience charge” that the travel aggregator adds on just before you enter your credit card details, for you have already mentally “bought” the ticket, and this convenience charge is only a minor inconvenience. Once you are convinced that you need to do a business deal, you don’t mind if the price moves away from you in small marginal steps – once you’ve made the decision that you have to do the deal, these moves away are only minor, and well within the higher value you’ve placed on the deal.

So where does this fit in to Carlsen’s draw offer yesterday? It was clear from the outset that Carlsen was playing for a draw. When the position was repeated twice, it raised Carlsen’s hope that the game would be a draw, and he assumed that he was getting the draw he wanted. When Caruana refused to repeat position, and did so after a really long think, Carlsen suddenly realised that he wasn’t getting the draw he thought he was getting.

It was as if the draw was Carlsen’s and it had now been taken away from him, so now he needed to somehow get it. Carlsen played well after that, and Caruana played badly, and the engines clearly showed that Carlsen had an advantage when the game crossed move 30.

However, having “accepted” a draw earlier in the game (by repeating moves twice), Carlsen wanted to lock in the draw, rather than play on in an inferior mental state and risk a loss (which would also result in the loss of the Championship). And hence, despite the significantly superior position, he made the draw offer, which Caruana was only happy to accept (given his worse situation).

 

 

How markets work

A long time back, there was this picture that was making the rounds on Twitter and (more prominently) LinkedIn. It featured three boys of varying heights trying to look over a fence to see a ball game.

Here is what it looked like:

Source: http://www.freshshropshire.org.uk/about-us/equality-and-diversity/equality-of-opportunity/

These pictures were used to illustrate that equality of outcomes is not the equality of opportunity, or some such things, and to make a case for “justice”.

As it must be very clear, the allocation of blocks on the right is more efficient than the allocation of the blocks on the left – the tallest guy simply doesn’t need any blocks, while the shortest guy needs two.

And if you think about it, you don’t need any top-down “justice” to allocate the blocks in the right manner. All it takes is a bit of logical thinking and markets – and not even efficiently.

Think about how this scenario might play out at the ball park. The three boys go to see the ball game, and see three blocks at the fence. Each of them climbs a block, and we get the situation on the left.

Shortest boy realises he can’t see and starts crying. There are many ways in which this story can play out from here onward:

  1. Tallest boy realises that he doesn’t really need that extra block, and steps down and gives it to the shortest guy, giving the picture on the right.
  2. Tallest boy continues to stand on his block. Shortest boy realises that the tallest boy doesn’t need it, and requests him for the block. Assuming tallest boy likes him, he will give him the block.
  3. Tallest boy continues on the block. Shortest boy requests for it, but tallest boy refuses saying “this is my block why should I give it to you?”. Shortest boy negotiates. Tells tallest boy he’ll give him a chocolate or some such in return for the block. And gets the block.
  4. Tallest boy doesn’t want chocolate or anything else the shortest boy offers. In fact he might want to settle a score with the shortest boy and refuses to give the block. In this case, the shortest boy realises there is no point being there and not watching the ball game, and makes an exit. In some cases, the middle boy might negotiate with the tallest boy on his behalf, leading to the transfer of the block. In other situations, the shortest boy simply goes away.

Notice that in none of these situations (all of them reasonably “spontaneous”) does the picture on the left happen. In other words, it’s simply unrealistic. And you don’t need any top down notion of “justice” to enable the blocks to be distributed in a “fair” manner.

Service charges

So the Indian government has said that it is not mandatory for customers to pay “service charges” at restaurants. It will be interesting to see how the restaurant industry will react to this.

The basic idea of a “service charge” is a “forced tip”. Given that Indians aren’t big tippers, restaurants, about a decade ago, started levying a service charge on top of the bill, ranging from 5% to 15%. Some restaurants mention this on the menu explicitly. In others, the print is fine. Some customers have come to accept the service charge. Others fight it.

The National Restaurants Association of India hasn’t taken too kindly to the notification, and has said they’ll take the government to court on this matter. It sounds like a rather extreme reaction, but illustrates the effect of behavioural studies.

Lower end eateries typically publish menus with “all inclusive” prices. If a cup of coffee is listed at Rs. 10, you pay Rs. 10 for it. Mid-priced and higher-end restaurants, however, have defaulted to showing prices exclusive of taxes and charges. With a 5% VAT, 15% Service Tax and (typically) 5% service charge, the final bill comes out to about 25-30% higher than the labelled price.

Now, frequent restaurant goers are aware of all these charges, and that the bill will be much higher than the sticker price. If they are rational, they should be taking into account these additional charges when deciding whether to go to restaurants, and when they do, what to order.

The problem, however, is that these charges are not immediately visible at the time of ordering, and so the customers end up ordering more expensive food than they had budgeted for (after controlling for the overall price level of the restaurant itself). It is a behavioural effect, where the customers’ minds are tricked by the number in front of them rather than what they will immediately end up paying.

The order that service charge is not mandatory will now push restaurants to include them in the sticker price of the food itself (it doesn’t matter what you call it – it’s ultimately revenue to the restaurant). The immediate impact of this will be that sticker prices will have to go higher, which will put a “bigger price” in front of the customers’ eyes, and they will order less.

How much less is not clear, but the fact that the restaurants association wants to take the government to court suggests it’s not insignificant. The high end restaurant business runs on extremely low margins (think what you may of the pricing), and even a less than 5% impact on revenues can have a significant impact on the bottom line.

It will be interesting to see if the government next mandates menus to print prices inclusive of taxes. It will be another behavioural nudge, but will end up ruining the restaurant business even more.

Elasticity and Discounted Pricing

The common trend among startups nowadays is to give away their product for a low price (or no price), and often below what it costs them to make it. The reasoning is that this helps them build traction, and marketshare, quickly. And that once the market has taken to the product, and the product has become a significant part of the customer’s life, prices can be raised and money can be made.

The problem with this approach is the beast known as elasticity. Elasticity means that when you increase your price, quantity demanded falls. Some products are highly elastic – a small increase in price can result in a large drop in quantity. Others are less so. Yet, it is extremely rare to find a product whose elasticity is zero, that is, whose quantity demanded does not vary with price. And even if such products exist, it is extremely unlikely that a product produced by a startup will fall in that category.

A good example of elasticity hitting is the shutting down of this American company called HomeJoy. As this piece in Forbes explains, the chief reason for HomeJoy shutting down is that it couldn’t hold on to its customers when it started charging market rates:

Not only did that kind of discounting make Homejoy lose significant money, it also brought in the wrong kind of customer. Many never booked again because they weren’t willing or able to pay the full price, which ranged from $25 to $35 an hour. Homejoy changed its pricing last year to make recurring cleanings cheaper and encourage repeat business. In response, some customers simply booked at the cheaper price and cancelled future appointments.

Based on the above explanation, it seems like subsidising customers to gain traction is a bad idea, and that a business should not be willing to make losses in the initial days in order to gain market. Yet, that would be like throwing out the baby with the bathwater, for subsidising at the “right level” can help ramp up significantly without elasticity hitting later. The question is what the right level is.

A feature of many businesses, and especially marketplace kind of businesses that startups nowadays are getting into, is economies of scale. This means that as the number of units “sold” increases, the cost per unit falls drastically. In other words, such businesses work well when they have built up sufficient scale, but collapse at lower levels. For such businesses, the thinking goes, it is impossible to bootstrap, and the solution is to subsidise customers until the requisite scale can be built up, at which point in time you can start making money.

The question is regarding the “sweet spot” of subsidy that should be given to the customer in order to build up the business. If you subsidise the customer too much in the initial days, there is the risk of elasticity hitting you at steady state, and things rapidly unravelling. If you subsidise too little, you may never build the scale.

The answer is rather straightforward, and possibly intuitive – start out by charging the price to the customer at which the business will be profitable and sustainable in the steady state. This will imply losses in the initial days, since your unit costs will be significantly higher (due to lack of scale). Yet, as you ramp up and hit steady state, you don’t have the problem of raising the price which might result in elasticity hitting your business.

What if, on the other hand, the subsidy you are giving out is not enough, and you are not willing to build traction? That is answered with the “Queen of Hearts” paradigm. The paradigm says that if the only way you can make your contract is if West holds the Queen of Hearts (talking about contract bridge here), you simply assume that West holds the card and play on. If he held the card, you would win. If not, you would have never won anyway!

Similarly, the only way your business might be long-run-sustainable is if you can generate sufficient traction at your long-run-sustainable price. If you need to drop the price below this in order to gain initial traction, it means that you will have the risk of losing customers when you eventually raise the price to the long-run-sustainable-price, which means that your business is perhaps not long-run-sustainable, and it is best for you to cut your losses and move on.

 

Now think of all the heavily-discounted startups out there and tabulate who are the ones who are charging what you think is a long-run-sustainable price, and who runs the risk of getting hit by elasticity.

The Box: A review

So over the weekend I started and finished reading “The Box: How the shipping container made the world smaller and the world economy bigger” by Mark Levinson. It’s a fascinating book, and one that I had been intending to read for a very long time. Somehow it always kept slipping my mind whenever I wondered what book to buy next, and I’d pushed buying it for a long time now.

Finally, a few days back, when “unknown twitter celebrityKrish Ashok asked his followers to send him reading recommendations, and when he published the list, and I saw this book on the list, and I saw that the book was available on Kindle for Rs. 175, I just bought it. This is the first book in a very long time that I’ve bought “straight” off the Kindle Store, not bothering with a sample.

It’s a fascinating book, as it takes us through the 50-odd years of history of the shipping box. And on the way, it gives us insights into the development of the world economy through the 50s and 60s, and factors that led to the logistic revolution ushered in by the box.

We think of post world war America as this capitalist haven, where markets were free, and you could get jailed for communist leanings. We tend to think about this time as one of innovation and freedom of business, leading to high economic growth.

This wasn’t the case, though. While the US was nominally capitalist and markets were supposedly free, this was a time of heavy regulations, and the presence of cartels. International shipping rates, for example, till the mid-1970s, were set by “conferences” (basically cartels), after which the cartels broke down. It was not possible for a carrier to quote an integrated source-to-destination rate, and rates had to be quoted by leg. Someone who wanted to start a new train route had to prove to the regulators that it would not harm existing players!

And then there were the unions. Levinson devotes an entire chapter to how the unions were managed. Basically containerisation meant greater mechanisation and a reduction in demand for labour. And this was obviously not acceptable to the dockworker unions, and led to protracted battles which needed to be resolved before containerisation could take off. The most interesting story came from the UK, where unions in most established ports (primarily London and Liverpool) blocked containerisation, and went on strike in the specially developed container port at Tilbury. Felixstowe, which had hitherto been too obscure a port to attract unions’ attention, now unencumbered by unions, jumped on to the container business and is now by far the UK’s biggest port.

Levinson also pays much attention to how the container shaped economies in general. Prior to containerisation, the cost of changing mode of transport was very high, since individual items needed to be unloaded from one means of transport and loaded to another. Industries were usually located based on access to port, and ports came up to service nearby industries. Containerisation changed all that. Now that it was easy to transport using a series of different means of transport, the location advantage of being close to port was lost. And this had massive effects on the economy of regions.

Massive effects on economies also happened due to the scale factor that containerisation brought in. Small ports didn’t make any sense any more, since the transaction cost of berthing was too high. And so small ports started dying, with business being soncolidated into a few larger ports. The game changed into a winner take all mechanism.

In the 1950s and 60s, before the coming of the container, shipping was a low-capex high-opex (operational expenditure) business. Most ships were old and cheap, but costs in terms of labour and other things was high. With the coming of the containership, the cost structure inverted, with the capital expenditure now being extremely high, but opex being quite low. This led to “revenue management”, and a drop in prices, and ultimately the breaking of the cartels.

The book is full of insights, and chapters are organised by subject rather than in chronological order. It gets a little repetitive at times, but is mostly crisp (I read it in a weekend), and the insights mentioned above are only a sample. And it tells us not only the story of the box (which it does) but also the story of the world economy, and regulation, and competition, and unionisation and economies of scale. Highly recommended.

 

Aggregate quality of life

I was going through some discussions on the “Bangalore – Photos from a Bygone Era” (membership required to view) group on Facebook. From some of the discussions, it is evident that people are nostalgic about the quality of life in Bangalore in “those bygone days” compared to now (irrespective of your definition of bygone).

For example, someone was marvelling about how empty the HAL airport used to be in those days, until it became intolerably crowded in the late 1990s necessitating the construction of the new airport in Devanahalli. Someone else, perhaps in the same thread, wondered about how one could make a dash from HAL airport to Commercial street and back in 30 minutes “back in those days”. Outside of the group, I remember Vijay Mallya mention in an interview a couple of years back about how when he was young he could drive from his home in the middle of town to HAL airport in 15 minutes, and it’s not possible any more.

Reading such reports, you start thinking that life back in those days was truly superior to life today.

While narratives like the above might indeed make you believe that life in a “bygone era” was significantly superior, what that doesn’t take into account is that life was possibly superior for only certain people back then – airports were empty because tickets were prohibitively expensive and the monopolist Indian Airlines ran few flights out of Bangalore. Traffic was smooth because there were few cars, so if you were lucky to have one you could zip around the city. However, if you were not as lucky, and one of the many who didn’t have access to a personal vehicle, things could be really bad for you, for you had to either walk, or wait endlessly for a perpetually crowded bus!

One of the ostensible purposes of the socialist model followed by India in the early decades after independence was to limit inequality. Yet, the shortages that the system led to led to widening inequality rather than suppressing it. By conventional metrics of inequality – such as the Gini coefficient, it might be that wealth/income inequality in India today is significantly higher than in the decades immediately after independence.

However, if you were to take into account consumption and access to living a certain way, inequality today is far lower than it was in those socialist years. In the 1970s you could get an asset only if you knew someone that mattered (my father waited four years (1976-80) before he was “allotted” his scooter. His first telephone connection took six years (1989-95) to arrive), and this only served to exacerbate the inequality between those that had access to the “system” and those that didn’t. Today on the other hand you are able to purchase any asset on demand as long as you can afford it! And so a lot more people can afford a “reasonable” quality of life that was beyond them (or their ancestors) back in those days!

What we need is a redefinition of the concept of inequality from a strictly monetary one to one based on consumption and access to certain goods and services. While wealth inequality is indeed a problem (because of lower marginal utility of money the super-rich don’t spend as much as the less rich), what matters more is inequality in terms of quality of life. And this is something standard measures such as the Gini coefficient cannot measure.

I tried getting some students work on a “quality of life index” to show the improvements in quality of life (as explained above) since the “bygone era”. Perhaps I didn’t communicate it well enough, but they just stuck to standard definitions like per capita income, education, life expectancy, etc. What I want to build is an index that captures and tracks “true inequality”.

Weak ties and job hunting

As the more perceptive of you would have figured out by now, the wife is in her first year of business school, and looking for an internship. I’m at a life stage where I have friends in most companies she is interested in who are in roles that are at a level where it is possible for them to make a decision to hire her.

Yet, so far I’ve made few recommendations. I’ve made the odd connection but that’s been mostly of the “she is applying to your company and wants to get to know the company better. Can you speak to her about it?” variety. I don’t think there’s a single person to whom I’ve written saying that the wife is in the market for an internship and they should consider hiring her.

I initially thought it was some inherent meanness in me, or lack of desire to help, that prevented me from recommending my wife to potential hirers who I know well. But then a little bit of literature survey pointed out an economic rationale to my behaviour – it is the phenomenon of “weak ties”. Now I was aware of this weak ties research earlier – but I had assumed that it had only referred to the phenomenon where acquaintances are more likely to help than friends because the former’s networks are much more disjoint from yours than the latter’s.

Anyway, in a vain attempt at defence, I hit “weak ties and job hunting” into google, and that led me to this wonderful post on the social capital blog that contained exactly what I was looking for. Here is the money quote:

It turns out, that people generally don’t refer their close friends to jobs for two reasons: 1) they are more worried that it will reflect badly on them if it doesn’t work out; and 2) they are more likely to know of the warts and foibles of their close friends and believe these could interfere with being a good worker (e.g., Jim stays up late to watch sports, or Charles has too much of an attitude, or Jane is too involved with her sick father).  Weak friends one can more easily project good attributes onto and believe this will work out.

So if I were to request you to hire my wife and it doesn’t work out, it can affect the relationship between you and me, so I wouldn’t risk that. When I’m recommending someone very close to me, I’m putting my own reputation on the line and I don’t like that. I’m happy referring cousins or other slightly distant acquaintances because there I have no skin in the game and hopefully some good karma can get created.

Now, while I’m loathe to recommend my wife to people I know well,  I wouldn’t be so hesitant recommending her to people I don’t know that well! For while my tie with my wife is strong, my tie with these people is weak enough that it not working out won’t affect me, and there is little reputational risk also. The problem is when the ties on both sides are strong!

 

 

Geek Talk

So I was talking to the wife using Viber when Viber acted up and disconnected. This happened a couple of times. Then I moved to FaceTime, but that too had problems, and started acting up. Finally I got irritated and decided I wouldn’t mind spending some money for uninterrupted conversation, so picked up my phone and dialled ISD.

And I told the wife, “I was getting damn irritated with packet switching, so I moved to circuit switching”. And then we got talking on why Viber was so irritating, and we talked about Tanenbaum (both of us really loved that textbook of Networking) and acknowledgements and transmission of messages on unreliable channels – which can only happen by introducing redundancy – which becomes painful in a human-to-human direct conversation.

I have an engineering degree, and am fairly good at maths, and read a fair bit of economics and history, so keep popping up concepts from these in my regular conversation. Some people find it abhorrent, and wonder if I’ve landed from another planet, given that I talk this way. For example, I remember using  the word “incentivise” while answering a question at a quiz (which had nothing to do with economics). I often rationalise purchases saying they offer “option value” – real options are one thing that I think I understand. And so forth.

From this perspective I think it’s really wonderful that I’m married to someone who not only tolerates this geek talk but actively encourages and participates in it! Like the wife has now become a big proponent of the concept of option value (though admittedly she has just joined B-school so is yet to appreciate the finer points of the Black-Scholes-Merton model). I’m not sure if before she met me she would quote as regularly from Harry Potter as she does now (or maybe I’m taking too much credit). And she keeps peppering examples from physics and astronomy and electrical engineering in her normal day-to-day conversation.

And speaking of physics and option theory and sporting analogies, I get damn irritated when people describe curves as the one below as “hockey sticks”.

I’m Indian, and the only hockey I know is “field hockey”, whose stick looks like a J. So whenever someone mentions “hockey stick” I start imagining a J-shaped curve. As for the above curve, I sometimes (especially when I’m hanging out with banker types) describe it as “call option payoff”. When I’m hanging out with more scientific types, I describe it as “photoelectric effect”.

I wonder how our kids will turn out!

In which I thulp the RBI

I’m still so pissed off with the Reserve Bank of India doing a Ramanamurthy that I’ve written a serious editorial in Pragati – the Indian National Interest Review (published by the Takshashila Institution). In this piece I take on measures by the RBI to limit ATM transactions and the thing on two factor authorization.

I claim that both these decisions are economically unsound and there is only possibly a farcical explanation for them:

There is perhaps only one idea (more a conspiracy theory) that possibly explains the above decisions from the RBI. Both these decisions, it might be noticed, help push up the usage of hard currency and decrease the levels of bank deposits. Less bank deposits means less money available for banks to lend out, which means that the cost of borrowing from a bank implicitly goes up. Could it be that the above regulations are a move by the RBI to curtail money supply without necessarily doing the politically tricky task of raising interest rates?

If it is (and it is a very remote possibility), we should commend the RBI for what will then amount to be a sneaky decision

Link

Why Keynes’s prediction has not come true

Writing in the 1930s economist John Maynard Keynes predicted at at the “time of our grandchildren” (figurative term since he himself had no kids) people would live a life of leisure and work for an average of fifteen hours a week. Yet, it’s been eighty years since and we still slog away, putting in anywhere between forty and sixty hours a week as we earn our living. And it doesn’t look like things are going to change soon

So why did this happen? I propose two reasons. When I quit my first job almost eight years ago within three months of joining I complained that the workload was way too high. I added that I didn’t need all the money that job paid me and wouldn’t mind taking up something that paid half the money and where I had to work only half the time. No such thing materialized and I slogged away, before going freelance two years back.

Now why does this little anecdote matter? I’m using this to show that the returns to work are not linear. If you were to plot the number of hours worked per week on the x axis and the total value added on the y axis you are likely to get a convex function. In other words the marginal benefit out of every additional hour you work per week is an increasing function of how much you’ve already worked.

The question is why this is so. One simple answer is that in jobs with a high degree of learning by working longer you end up learning faster. Then within the job you can have network effects where the work you do in one part of the job can help you do another part better (I constantly see this in my freelancing where I work on several projects at a time). If there is a steep learning curve it is easier for the firm to appoint one worker to work sixty hours a week than two to work thirty each – since the starting costs get saved. And so forth.

So this increasing returns to effort (in terms of the hours worked) is that the trade off between work and leisure gets resolved in favour of leisure only at a very high level of work – where you are working close to capacity and don’t want to risk burnout and want to maintain your sanity. Before that the increasing returns to effort means that you are likely to put off leisure in favour of “just a little more work”.

The question is if all jobs work this way, and why an economist as brilliant as Keynes didn’t see this concept of increasing returns to work. The answer is that increasing returns to work applies only to a certain kind of jobs – jobs that require a high level of skill and learning and which can be broadly classified as “knowledge jobs”.

Back in Keynes’s time such knowledge jobs were few – far fewer than they are today. Most workers were in jobs that didn’t require a high degree of skill or learning. In unskilled jobs or jobs that are physically demanding the expanding returns to effort part of the curve is extremely short. Once you have figured out the best way to bolt together two metal pieces doing more of this job is not going to make you much faster in bolting together two metal pieces.

Instead since it is physical after you’ve put in a certain number of hours in a day you begun to tire and become less efficient (notice this point occurs at a later stage for knowledge jobs). And the returns to hours curve starts flattening out much sooner. If you were to do the trade off with leisure using such a curve the equilibrium might occur much earlier than for knowledge work – perhaps at Keynes’s predicted value of fifteen hours per week.

Now even today while the proportion of non knowledge jobs is smaller than eighty years back the number of people doing such jobs is not small. So if the work-leisure equilibrium happens at fifteen hours a week why do people work longer?

The answer is that work-leisure is not the only equilibrium one is solving for. You also need to work enough to be able it fund your living. And it has happened that fifteen hours of non knowledge work pays nowhere close tO what is required to fund a reasonable living. For this reason non knowledge workers are forced to work much longer than their work-leisure equilibrium rule permits!

So why didn’t Keynes see this? I think what he missed was the boom in the knowledge economy in the postwar period. With the rise in the knowledge economy what you had was a set if jobs that had increasing returns to effort. Moreover these returns, on an hourly basis, were far larger than the returns on a non knowledge job. The boom in the knowledge economy meant that people working in such jobs impacted general prices and this forced the non knowledge workers to work longer!

So we have the unique situation now that those people who can afford to work for only fifteen hours a week have no incentive to do so. On the other hand people who have an incentive to work no more than fifteen hours a week are forced to work longer because otherwise they cannot find their lives!!