## Water, IPL and the ease of doing business

The latest controversy surrounding the just-about-to-start ninth edition of the IPL (a court case challenging its staging in Maharashtra while farmers are dying in Vidarbha) is a clear illustration of why the ease of doing business in India doesn’t look like it will improve.

At the bottom of it, the IPL is a business, with the IPL and teams having invested heavily in team building and marketing and infrastructure. They have made these investments so far hoping to recover them through the tournament, by way of television rights, gate receipts, etc.

Now if the courts were to suddenly decide that the IPL should not take place in Maharashtra, it will mean that alternate arrangements will have to be found in terms of venues and logistics, teams which have prepared grounds in Nagpur, Pune and Mumbai will have to recalibrate strategies, and most importantly, the people of these cities who have bought tickets (they clearly believe that the value of these tickets is higher than the price) will also end up losing.

Farmers dying for lack of water is a real, and emotive, issue. Yet, to go after a high-profile event such as the IPL while not taking other simpler measures to curb fresh water wastage is a knee-jerk reaction which will at best have optical effects, while curbing the ability of businesspersons to conduct legitimate business.

There has been much talk about how policy measures such as the retrospective taxation on Vodafone or Cairn have been detrimental to investor sentiment and curbed fresh investments in India. This court case against the IPL days before it began is no different, and a strong signal that India’s policy uncertainty is not going away quickly.

Unless the political class manages to fix this, and provide businesses more stable environments to operate in, it is unlikely we’ll see significant increase in investments into India.

## The Economics of Shakespeare and Company

During my vacation, I finished reading Salil Tripathi’s Detours, an enhanced collection of his columns in Mint Lounge of the same name. I quite liked the book. In fact, I liked it much more than his columns in Mint Lounge. I think the lack of word limit constraints meant he could add depth when necessary making it a steady and pleasing read (read Sarah Farooqui’s formal review of the book here).

In one of the chapters, he describes Paris in the way Hemingway saw it (literature and art are constant figures in this book, and the fact that I could connect to it (the book) despite my general lack of interest in these topics speaks volumes about the quality of the book). More specifically, this is about the Shakespeare and Company bookshop in Paris where Hemingway occasionally lived, and wrote his books.

George Whitman, a US army veteran who settled down in Paris after the Second World War, bought the store and ran it until his death. During these years, he hosted writers who wanted to visit Paris in an upstairs room, allowing them to basically live in the store as they wrote. There were frequent readings organised in the store where writers could connect with their readers, and writers and other regular patrons were frequently allowed to use the bookshop as a library – to simply read rather than buy books.

There was an occasion when Whitman’s store license ran out and he got into a dispute with the municipal authorities who refused to renew it, to which he responded by stopping the sale of books and running the shop as a library until the license was ultimately renewed.

While Salil describes this as a measure of Whitman’s commitment to good literature and helping authors, it was hard for me to read this chapter without wondering about Whitman’s finances, for none of the above is cheap. One of the biggest costs to running a bookshop is the cost of real estate, and if Whitman had an upstairs room for writers to live and write in, and could redeploy his shop as a library, it came at a significant cost of real estate. While readings might help sell additional books (most readers who attend buy at least a copy of the book that is being discussed), it can disrupt the regular flow of business in the store, and affect sales. The question that I couldn’t escape while reading the book was about the store’s finances and how Whitman managed all these activities.

One hypothesis is that he had alternate sources of funding (patrons of literature’s contributions, or family funds, for example) that allowed him to spend in writer welfare. The other is that margins from the book selling business were fat enough to allow Whitman to spend on writer welfare, and this spending paid him back by way of improving overall sales from his store. Back in the day when you could only buy books from shops, shops that curated well or stocked rare books could afford to charge a premium, and make significant margins which could go into activities such as writer promotion and welfare.

If this hypothesis is correct, it could explain why the traditional literature industry, including authors, are so incensed by Amazon’s rise, even if it leads to significantly better revenues. What Amazon allowed, by its initial print book mailing model, was for readers to access the “long tail” of books which they could purchase at a reasonable cost (they weren’t beholden to curator-bookseller any more). While the more passionate readers remained loyal to their curator-bookseller, the mass moved to the cheaper option.

While this created value for readers (in terms of lower prices for their books), it had the effect of cutting retail margins for books by a significant amount. Several bookshops became unprofitable under this new regime, and with the new margins not compensating for increasing real estate costs, many of them (including chains such as Borders) closed down. Writers weren’t directly affected economically – for readers who would have earlier purchased in such shops could now simply purchase the same books at Amazon for a lower price, but the dropping profitability of conventional bookstores affected them in other ways.

As Salil’s chapter on Shakespeare & Co illustrates, independent bookshops performed a social function far higher than curating and selling books – they provided an author a platform to connect with readers and enabled authors to meet and exchange ideas. They organised events for authors which raised their profile, and helped sell more books.

Their replacement by low-cost retailing models has cut out this additional social function they performed (without direct rewards). Without independent bookshops organising readings and offering writing spaces, writers have lost something they had access to earlier (though they’ve been monetarily compensated for this by means of higher sales driven by lower prices on Amazon). Hence it’s no surprise that writers have taken sides with their publishers in the battle against Amazon, online retailing and e-books.

In this context, this old piece by Matthew Yglesias in Vox is worth reading, where it talks about why Amazon is performing a socially useful function by curtailing the book publishing industry. Yglesias writes:

My best guess is that this is too pessimistic about the financial logic behind giving advances. It is not, after all, just a loan that you may or may not pay back. An advance is bundled with a royalty agreement in which a majority of the sales revenue is allocated to someone other than the author of the book. In its role as venture capitalist, the publisher is effectively issuing what’s called convertible debt in corporate finance circles — a risky loan that becomes an ownership stake in the project if it succeeds.

## On liberalism and government control

My first exposure to political ideologies took place in 2004, when I joined the now-defunct (but then brilliant) social networking site Orkut. While filling up my personal details, I was asked to pick my political beliefs from a drop-down.

It had things such as “left-liberal”, “very left-liberal”, “right-conservative”, etc. Now, while I considered myself liberal back then (I’ve moved far more liberal on personal freedom issues since then), there was no way I could describe myself as “left”, since I’ve always been a free market fundamentalist. Finally I noticed there was something called “libertarian” in the dropdown, and assumed it might stand for my beliefs and chose that. In hindsight, it turns out I was right (no pun intended).

A year or two later, I got introduced to a “libertarian cartel” (I was never a member, so don’t know who were members). Presently, I was invited to join some of them in discussions, and my love for the libertarian philosophy grew (these discussions were instrumental in me moving far more liberal on personal freedom issues). Yet, looking around the political spectrum, you had few libertarian parties (going across countries).

You had the set of parties that can be broadly classified as “Republican” which allowed you to do business the way you liked, but sought to restrict personal freedoms. And there were the parties that can be classified as “Democrat” which promoted personal freedoms, but restricted how you could do business. And you had philosophies such as communism which sought to control both. The “fourth quadrant” was (and is) largely empty.

It is not hard to understand why this fourth quadrant is empty – in exchange for responsibilities of governing, politicians desire power, and this power can only come at the cost of restricting freedoms of the constituents. Different political formations choose to exercise this power along different axes, but little differentiates them – they all seek to control. While libertarianism is appealing for the constituent, it doesn’t make sense for politicians since it doesn’t compensate sufficiently for the responsibility of  governance. Hence you don’t find libertarian political parties.

Yet, we find that slowly but surely, reforms do happen. Over time, restrictions on freedoms (both personal and economic) do get relaxed, albeit at a glacial pace, and this is true across countries, despite there being no “libertarian” politicians. Why does this happen?

The simplistic answer is that politicians in functioning democracies have to face lengthy periods of time in opposition, when they are at the mercy of the party that is then in power. Since politicians tend to be vindictive animals, you don’t want to leave behind any laws that might be used to harass you while you are out of power. So the ruling party should tend to ease restrictions that can be used against its members when they are out of power.

Again, this is fine in theory, but why does it not always happen? The answer is that opposing political parties are not “orthogonal enough”. If politicians on multiple sides of the divide have broadly similar ideas on certain issues, there can be a tacit understanding (a “doctrine of no first use”, perhaps) to not use the laws that they agree on against each other.

When you have parties that have orthogonal philosophies, you can expect them to do their bit while in power to undermine the sources of their rivals’ control, so that their rivals might enjoy less control the next time they are in power. And citizens in such democracies are likely to enjoy greater freedoms.

As the old saying (paraphrased) goes, “when politicians from all parties agree to something, it is unlikely to be in the interests of the people”.

## Counter staffing and service levels

I’m writing this from the international section of the Bangalore International Airport, as I wait to board my flight to Barcelona. It was a plan I’d made in October 2014 to “hibernate” for a few months in Barcelona during my wife’s last term of classes there, and this is the execution of the same plan.

There was a fairly long line at the passport control counters this morning, and it took me perhaps twenty minutes to cross it. When I joined the line, there were about 10 passport officers to say goodbye to Indian passport, so the line moved fairly quickly.

Presently, officers started getting up one by one, and going to one side to drink tea. I initially thought it was a tea break, but the officers drinking tea soon disappeared, leaving just four counters in operation, implying that the line moved much slowly thereafter. Some people were pissed off, but I soon got out.

It is not an uncommon occurrence to suddenly see a section of “servers” being closed. For example, you might go to the supermarket on a weekday afternoon to expect quick checkouts, but you might notice that only a fraction of the checkout counters are operational, leading to lines as long as on a weekend evening.

From the system of servers’ point of view, this is quite rational. While some customers might expect some kind of a moral obligation from the system of servers to keep all servers operational, the system of servers has no obligation to do so. All they have an obligation towards is in maintaining a certain service level.

So coming back to passport control at the Bangalore airport, maybe they have a service level of “an average of 30 minutes of waiting time for passengers”, and knowing that the number of international flights in late morning is lower than early morning, they know that the new demand can be met with a smaller number of servers.

The problem here is with the way that this gets implemented, which might piss off people – when half the servers summarily disappear, and waiting period suddenly goes up, people are bound to get pissed off. A superior strategy would be to do it in phases – giving a reasonable gap between each server going off. That smoothens the supply and waiting time, and people are far less likely to notice.

As the old Mirinda Lime advertisement went (#youremember), zor ka jhatka dheere se lage.

## Bias in price signals from ask only markets

Yesterday I listened to this superb podcast where Russ Roberts of the Hoover Institution interviews Josh Luber who runs Campless, a secondary market for sneakers (listen to the podcast, it isn’t as bizarre as it sounds). The podcast is full of insights on markets and “thickness” and liquidity and signalling and secondary markets and so on.

To me, one of the most interesting takeaways of the podcast was the concept that the price information in “ask only markets” is positively biased. Let me explain.

A financial market is symmetric in that it has both bids (offers to buy stock) and asks (offers to sell). When there is a seller who is willing to sell the stock at a bid amount, he gets matched to the corresponding bid and the two trade. Similarly, if a buyer is willing to buy at ask, the ask gets “taken out”.

The “order book” at any time thus contains of both bids and asks – which have been unmatched thus far, and looking at the order book gives you an idea of what the “fair price” for the stock is.

However, not all markets are symmetric this way. In fact, most markets are asymmetric in that they only contain asks – offers to sell. Think of your neighbourhood shop – the shopkeeper is set up to only sell goods, at a price he determines (his “ask”). When a buyer comes along who is willing to pay the ask price of a good, a transaction happens and the good disappears.

Most online auction markets (such as eBay or OLX) also function the same way – they are ask only. People post on these platforms only when they have something to sell, accompanied by the ask price. Once a buyer who is willing to pay that price is found, the item disappears and the transaction is concluded.

What makes things complicated with platforms such as OLX or eBay (or Josh Luber’s Campless) is that most sellers are “retail”, who don’t have a clear idea of what price to ask for their wares. And this introduces an interesting bias.

Low (and more reasonable) asks are much more likely to find a match than higher asks. Thus, the former remain in the market for much shorter amount of time than the latter.

So if you were to poll the market at periodic intervals looking at the “best price” for a particular product, you are likely to end up with an overestimate because the unreasonable asks (which don’t get taken out that easily) are much more likely to occur in your sample than more reasonable asks. This problem can get compounded by prospective sellers who decide their ask by polling the market at regular intervals for the “best price” and use that as a benchmark.

Absolutely fascinating stuff that you don’t normally think about. Go ahead and listen to the full podcast!

PS: Wondering how it would be if OLX/eBay were to be symmetric markets, where bids can also be placed. Like “I want a Samsun 26 inch flatscreen LCD TV for Rs. 10000”. There is a marketplace for B&Bs (not Airbnb) which functions this way. Would be interesting to study for sure!

## Continuous and barrier regulation

One of the most important pieces of financial regulation in the US and Europe following the 2008 financial crisis is the designation of certain large institutions as “systemically important”, or in other words “too big to fail”. Institutions thus designated have greater regulatory and capital requirements, thus rendering them at a disadvantage compared to smaller competitors.

This is by design – one of the intentions of the “SiFi” (systemically important financial regulations) is to provide incentives to companies to become smaller so that the systemic risk is reduced. American insurer Metlife, for example, decided to hive off certain divisions so that it’s not a SiFi any more.

AIG, another major American insurer (which had to be bailed out during the 2008 financial crisis), is under pressure from its activist investors led by Carl Icahn to similarly break up so that it can avoid being a SiFi. The FT reports that there were celebrations in Italy when insurer Generali managed to get itself off the global SiFi list. Based on all this, the SiFi regulation seems to be working in spirit.

The problem, however, is with the method in which companies are designated SiFis, or rather, with that SiFi is a binary definition. A company is either a SiFi or it isn’t –  there is no continuum. This can lead to perverse incentives for companies to escape the SiFi tag, which might undermine the regulation.

Let’s say that the minimum market capitalisation for a company to be defined a SiFi is $10 billion (pulling this number out of thin air, and assuming that market cap is the only consideration for an entity to be classified as a SiFi). Does this mean that a company that is worth$10 Bn is “systemically important” but one that is worth \$9.9 Bn is not? This might lead to regulatory arbitrage that might lead to a revision of the benchmark, but it still remains a binary thing.

A better method for regulation would be for the definition of SiFi to be continuous, or fuzzy, so that as the company’s size increases, its “SiFiness” also increases proportionally, and the amount of additional regulations it has to face goes up “continuously” rather than being hit by a “barrier”. This way, the chances of regulatory arbitrage remain small, and the regulation will indeed serve its purpose.

SiFi is just one example – there are several other cases which are much better served by regulating companies (or individuals) as a continuum and not classifying them into discrete buckets. When you regulate companies as parts of discrete buckets, there is always the temptation to change just enough to move from one bucket to the other, and that might result in gaming. Continuous regulation, on the other hand, leaves no room for such marginal gaming – marginal changes aer only giong to have a marginal impact.

Perhaps for something like SiFi, where the requirements of being a SiFi are binary (compliance, etc.) there may not be a choice but to keep the definition discrete (if there are 10 different compliance measures, they can kick in at 10 different points, to simulate a continuous definition).

However, when the classification results in monetary benefits or costs (let’s say something like SiFis paying additional regulatory costs) it can be managed via non-linear funding. Let’s say that you pay 10% fees (for whatever) in category A and 12% in category B (which you get to once you cross a benchmark). A simply way to regulate would be to have the fees as a superlinear function of your market cap (if that’s what the benchmark is based on).

## Why Delhi’s odd-even plan might work

While it is too early to look at data and come to an objective decision, there is enough reason to believe that Delhi’s “odd-even” plan (that restricts access to streets on certain days to cars of a certain parity) might work.

The program was announced sometime in December and the pilot started in January, and you have the usual (and some unusual) set of outragers outraging about it, and about how it can cause chaos, makes the city unsafe and so forth. An old picture of a Delhi metro was recirculated on Monday and received thousands of retweets, by people who hadn’t bothered to check facts and were biased against the odd-even formula. There has been some anecdotal evidence, however, that the plan might be working.

It can be argued that the large number of exceptions (some of which are bizarre) might blunt the effect of the new policy, and that people might come up with innovative car-swap schemes (not all cars get out of their lots every morning, so a simple car-swap scheme can help people circumvent this ban), because of which only a small proportion of cars in Delhi might go off the roads thanks to the scheme.

While it might be true that the number of cars on Delhi roads might fall by far less than half (thanks to exemptions and swap schemes) due to this measure, that alone can have a significant impact on the city’s traffic, and pollution. This is primarily due to non-linearities in traffic around the capacity.

Consider a hypothetical example of a road with a capacity for carrying 100 cars per hour. As long as the number of cars that want to travel on it in an hour is less than 100, there is absolutely no problem and the cars go on. The 101st car, however, creates the problem, since the resource now needs to be allocated. The simplest way to allocate a resource such as a road is first come-first served, and so the 101st car waits for its turn at the beginning of the road, causing a block in the road it is coming from.

While this might be a hypothetical and hard-to-visualise example, it illustrates the discontinuity in the problem – up to 100, no problem, but 101st causes problem and every additional car adds to the problem. More importantly, these problems also cascade, since a car waiting to get on to a road clogs the road it is coming from.

Data is not available about the utilisation of Delhi roads before this new measure was implemented, but as long as the demand-supply ratio was not too much higher than 1, the new measure will be a success. In fact, if a fraction $f$ of earlier traffic remains on the road, the scheme will be a success as long as the earlier utilisation of the road was no more than $\frac{1}{f}$ (of course we are simplifying heavily here. Traffic varies by region, time of day, etc.).

In other words, the reduction in number of cars due to the new measure should mean significantly lower bottlenecks and traffic jams, and ensure that the remaining cars move much faster than they did earlier. And with lesser bottlenecks and jams, cars will end up burning less fuel than they used to, and that adds a multiplier to the drop in pollution.

Given that roads are hard to price (in theory it’s simple but not so in practice), what we need is a mechanism so that the number of cars using it is less than or equal to capacity. The discontinuity around this capacity means that we need some kind of a coordination mechanism to keep demand below the capacity. The tool that has currently been used (limiting road use based on number plate parity) is crude, but it will tell us whether such measures are indeed successful in cutting traffic.

More importantly, I hope that the Delhi government, traffic police, etc. have been collecting sufficient data through this trial period to determine whether the move has the intended effects. Once the trial period is over, we will know the true effect this has had (measuring pollution as some commentators have tried is crude, given lag effects, etc.).

If this measure is successful, other cities can plan to either replicate this measure (not ideal, since this is rather crude) or introduce congestion pricing in order to regulate traffic on roads.