## Who do you subsidise?

Customers with a lower consumer surplus end up subsidising those with a higher consumer surplus

One basic rule of pricing is that it is impossible for all buyers to have the same consumer surplus (the difference between what a buyer values the item at and what he paid). This is because each buyer values the item differently, and is thus willing to pay a different price for it. People who value the item more end up having a higher consumer surplus than those who value it less (and are still able to afford it).

Dynamic pricing systems (such as what we commonly see for air travel and hotels) try to price such that such a surplus is the same for all consumers, and equal to zero, but they never reach this ideal. While the variation in consumer surplus under such systems is lower, it is impossible for it to come to zero for all, or even a reasonable share of, customers.

So what effectively happens is that customers with a lower consumer surplus end up subsidising those with a higher consumer surplus. If the former customers didn’t exist, for example, the clearing price would’ve been higher, resulting in a lower consumer surplus for those who currently have a higher consumer surplus.

Sometimes the high surplus customer and the low surplus customer need not be different people – it could be the same person at different times. When I’m pressed for time, for example, my willingness to pay for a taxi is really high, and I’m highly likely to gain a significant consumer surplus by taking a standard taxi or ride-hailing marketplace ride then. At a more leisurely time, travelling on a route with plenty of bus service, I’d be willing to pay less, resulting in a lower consumer surplus. It is important to note, however, that my low surplus journey resulted in a further subsidy to my higher surplus journey.

When it comes to markets with network effects (whether direct, such as telecommunications, or indirect, like any two-sided marketplace), this surplus transfer effect is further exacerbated – not only do low-surplus customers subsidise high-surplus customers by keeping clearing price low, but network effects mean that by becoming customers they also add direct value to the high surplus customers.

So when you are pleasantly surprised to find that Uber is priced low, the low price is partly because of other customers who are paying close to their willingness to pay for the service. When you pay an amount close to the value you place on the service, you are in turn subsidising another customer whose willingness to pay is much higher.

This transfer of consumer surplus can be seen as an instance of bundling, but from the seller’s side. Since a seller cannot discriminate effectively among customers (even with dynamic pricing algorithms such as Uber’s surge pricing), the high-surplus customers come bundled with the low-surplus customers. And from the seller’s perspective, this bundling is optimal (see this post by Chris Dixon on why bundling works, and invert it).

So the reason I thought up this post is that there has been some uncertainty about ride-hailing marketplaces in Bangalore recently. First, drivers went on strike alleging that they weren’t being paid fairly by the marketplaces. Then, a regulator decided to take the rulebook too literally and banned pooled rides. As i write this, a bunch of young women I know are having a party, and it’s likely that they’ll need these ride-hailing services for getting home.

Given late night transport options in Bangalore, and the fact that the city sleeps early, their willingness to pay for a safe ride home will be high. If markets work normally, they’re guaranteed a high consumer surplus. And this will be made possible by someone, somewhere else, who stretched their budget to be able to afford an Uber ride.

Think about it!

## Comparing Airline Pricing across countries

The WSJ reports, based on a survey, that airline prices are cheapest in India (HT: Nitin Pai). They evaluate the cost of flying in terms of cost per 100 km. The usual ridiculous comparisons that go with any such article are present in full here – they compare the per kilometer cost of flying to train and bus fares, and conclude that flying is cheapest (this reminds me of an equally ridiculous report in the Times of India which showed that the cost of India’s Mars mission was less than that of taking a bus in Mumbai).

A few thoughts on this report by the WSJ:

• Per km is a wrong way at looking at air fares. In most markets (from my experience pricing air tickets and cargo), fares are set based on competition and to fill capacity. Notice that marginal cost of a passenger is really really low, so once a flight is in place airlines will do what they can to maximize their revenues from that.
• Taking this forward air fares depend on the competition in a particular sector (btw, the way airlines price it, Bangalore-Barcelona is one sector, and the price of that doesn’t depend on the Bangalore-Frankfurt and Frankfurt-Barcelona prices. These are three independent markets and triangle inequality doesn’t necessarily hold. Just FYI). So going by the report, India has a lot more competition compared to other countries in most sectors.
• Now think of other large countries (you need big area for flights to make sense) and think of their income levels compared to India. Only developed countries and other BRICS come to mind. All of them have a higher willingness to pay than India.
• Airline prices are thus a function of simple (elastic) demand and (inelastic – flight schedules are announced by “season”) supply. So once in a season we have a lot of flights scheduled, competitive forces push prices down
• Given that it’s demand and supply that determines airline prices and not costs, in my opinion the airline industry goes through cycles. You have lots of competing airlines. Prices are low and they lose money. In the course of time one or two go out of business or scale down, and that leads to increased prices. Airlines make money for a while, and then looking at the supernormal profits you have new entrants and so on. India right now is going through the phase where you aer getting more investors (Air Asia, Air Costa, Tata-SIA, etc.). That depresses prices. In a year or so I would think someone like SpiceJet will go out of business and that might push fares up for a while.
• There’s also the seasonality factor – based on regular travel to Bombay over the last two years I’ve found that fares in the monsoon months are half of the fares at any other point in the year. It’s a function of demand, again (Indian seasons don’t exactly tally with international seasons according to which schedules are made, so this results in flawed matching)! Given the timing of the piece it is possible that Indian fares in the monsoon months have been sampled.

## Charging for parking can solve a lot of problems

Bangalore city has this bizarre policy in that the city doesn’t charge for public parking (barring one or two roads). The ostensible reason was to cut the wings of the so-called “parking mafia”, which had taken over the concessions for operating parking lots through the city. However, not charging for parking means giving away parking for a non-monetary fee (first come first served, for example, or the cost incurred in driving around looking for a place to park). And there are a number of other problems that charging for parking can be solved that the current no parking fee dispensation doesn’t take care of.

• The lack of parking charges anywhere in the city, including the central business district, means that it is impossible to profitably take your car (without a driver) to such areas. There are non-monetary costs that people pay for parking – cost of time, cost of fuel driving around, cost of paying touts to hold down a parking spot, etc. Now if only these costs can be monetized then it would be a valuable source of revenue to the impoverished city  council
• Every weekday afternoon the middle of the city gets gridlocked thanks to the presence of four high-profile schools (Bishop Cotton Boys’, Bishop Cotton Girls’, Sacred Hearts and St. Joseph’s Boys) on the same stretch of road. The reason for gridlock is that people double and triple park on the four lane road (albeit with a driver in the car so it’s not strictly “parking”), and this leads to massive jams. Thanks to these schools it is impossible to move from the southern part of the city to the central business district in the afternoons. Now, if we could have dynamically priced parking on these roads, the cost of parking there for picking up kids might be deterrence enough for people to make alternate arrangements (such as school buses) for picking up the kids, and thus decongest the zone. The city has taken several other initiatives (titled “safe route to school”) but the gridlock continues.
• Thanks to free street parking there is no incentive for people to provide for parking spaces. I live in what is classified by the city as a “mixed zone”. So there are a number of commercial establishments close to where I live. Few of them actually provide parking, leading to major parking chaos around where I live (especially if there is a function at any of the three convention centres located within 100m of my house). The presence of paid street parking can lead to more regulated parking (currently lack of regulation means parking is rather haphazard and blocks gates). It will also create an incentive for the commercial establishments to provision for their own parking spots
• Establishments (mostly eateries, but some shops too) in the city have responded to the parking problem by providing valets – who will save you the time you would take to find a place to park. This is a rather inefficient solution. What if I have to visit four shops on the same street in an area where parking is difficult, for example?
• Some buildings in the CBD which have excess parking space let you use their parking space for a fee that is not unreasonable. What we need is more such buildings opening up their parking spaces to public (the “park here only if you have business in my building” paradigm is nonsense). And for that they need to be assured of a reasonable fee. With the city undercutting them at a price of zero they have no real incentive to open up.
• In the short run, until supply of parking the CBD increases, parking charges can be a good substitute for congestion charge to put a price on people driving into the city. While this will ease out once the supply of parking responds to the demand, in the short run it might work. Though it could be argued that the non-monetary costs of parking are already achieving this objective!

There are many more such reasons I’m sure you can think of. Yet, for close to ten years now the city of Bangalore has steadfastly refused to charge for parking spaces, which is extremely inefficient. Maybe we need MonkeyParking to enter Bangalore. That’s perhaps the only way the municipal authorities will recognize their folly and start monetizing their parking fees.

## Using illegal markets as price discovery mechanism

One of the pet projects of my former MLA (former because I moved residence, not because he was voted out) is to set up a formal mechanism for regulating street vendors. He wants to introduce some kind of a medallion for street vendors so that they have legal sanction, and at the same time subject them to health and food safety checks. Considering this is a fairly common practice abroad, and even in some parts of India (like Goa), it is high time something like this is introduced.

The question, however, is how we will price these “medallions”. Price them too high and existing vendors will not want to get into the new regime, and will remain outside regulatory bounds. Price them too low and it can result in missed opportunities and rent seeking (the current situation, where the price is zero, can be seen as a degenerate case of too low a price).

One way to do this would be through an auction. However, one thing we need to preserve is continuity – current existing street vendors need to get a chance to enter the legal fold without too much disturbance from their current business. An auction might see them being priced out and then continue to operate in the illegal framework – which is not an optimal solution.

The solution lies in status quo, and in illegal markets. Given that street vendors currently operate without a license, they are essentially illegal. The way they manage to keep their carts and not get arrested is by paying off a set of public (and private) officials. Perhaps there is the cop who seeks his weekly rent (hafta). Perhaps a municipal officer seeks the same. Maybe a local thug, too.

If you think about this, the sum total of all these payments is essentially the “license fee” that the vendor pays in order to do his business currently. Can we take this as a proxy for the appropriate license fee in a particular location? Can we do an anonymised survey among street vendors (after having classified them into different “areas”) in order to determine the clearing price?

The basic idea is that illegal markets (like that of the “hafta” for being a street vendor) are markets, too, and their price discovery mechanism is as legitimate as those of more legitimate markets. Thus, the price discovered by these illegal markets are a great starting point for regulated pricing!

There is one thing to examine, though – if we price the license at the same “fee” that the vendors are currently paying different rent seekers, will the rent seekers still be able to seek rent? My hypothesis is “no”. The reason rent seekers seek rent is because in its absence there is a “surplus” that the vendors generate which they are willing to share with the rent seekers. If all the rents that are now being collected by illegal rent seekers are subsequently sought by the state, there is no room left for the illegal rent seekers to operate in!

The question is if this framework can be used for eliminating other forms of rent-seeking, too. The answer, sadly, is no. A large number of the rents that are currently being sought are for “public services” which are not supposed to have a fee. I had to get a document from a court recently, and had to pay rents at different points in the chain in order to get it on time. Using this framework, the way to eliminate this would be by increasing the official court fee, but what one must keep in mind is that court services are inelastic – the increase in fee by a few thousand rupees will not deter me from asking for an order. Thus, even if the court fees are increased, nothing prevents the current rent-seekers from continuing to operate.

In other more elastic markets, however, this approach will work, and better be tried.

## The WhatsApp Effect

On the national data site (data.gov.in) the Telecom Regulatory Authority of India (TRAI) has put out some data on GSM telephony in the last five years. This has aggregate all-India data, and one of the data points available is “Outgoing SMS per subscriber per month”. The following graph plots this data over time:

Notice how the number of SMSs per user which rose sharply till mid 2011 then started suddenly dropping off! There seems to be a minor revival between March and June 2012, but apart from that it seems to be a secular decline. I can’t think of any reason apart from the profusion of smartphones and messaging apps on such phones such as WhatsApp, WeChat, etc. for this decline.

The total number of GSM subscribers also shows an interesting pattern,  going by the TRAI data. There is massive increase in the number of subscribers till 2012, and then the graph flatlines!

The only reason  I can think of for this is that there might have been some sort of a subscriber clean up in 2012. If you remember, when telcos introduced “unlimited subscription” plans for prepaid mobiles back in 2006, these so-called “unlimited plans” expired sometime in 2012. This was on account of re-auction of telecom spectrum that year. It is possible that users who were “active” only because of possession of unlimited plans were weeded out after 2012, and hence the flatline. Otherwise, the above trajectory is hard to believe.

Finally, what about the telecom tariffs? The supplied data set has information on the Average Revenue Per User (ARPU) per month, and the number of outgoing minutes of usage per subscriber. Assuming SMSs don’t cost anything (wrong assumption – since they do), we can calculate the telecom tariffs (in Rs. per minute). The following graph shows that:

Back in 2009, tariffs were close to a rupee a minute. However, between 2009 and 2010, tariffs dropped sharply, to the range of about 60 paisa per minute, which comes down to a paisa a second! Interestingly, tariffs have remained constant ever since.

## Pricing railway safety

Yet another railway accident has happened. As someone on twitter pointed out,

The problem with the Indian Railways is that there is no real measure of safety. How do we know how much safer the trains and tracks are compared to last year? Given the way the Railway finances are put out currently, there is no way to figure this out. Without the railways putting out more disclosures, is there a way to put a number on how safe the Indian Railways are? In other words, is there a way to “price” railway safety?

As you are well aware, and as the above tweet points out, it is standard practice in Indian Railway accidents for the Railway Minister to announce an ex-gratia payment to the families of the dead and the injured in case of any accident. I’m not sure if there is a formula to this but one cannot rule out the arbitrariness of this amount. As I had pointed out in an earlier post on RQ, accident compensation needs to be predictable and automatic. Can we use this to price railway safety?

First of all, we need to point out that the railways follows a cash accounting system, and thus doesn’t need to account for any contingent liabilities such as ex-gratia payment (last weekend I sat through an awesome lecture by Prof. Mukul Asher (councillor to Takshashila) on public finances, and he pointed this out). Hence, it would be prudent on behalf of the Indian Railways to hedge out this contingent liability.

How do you hedge a contingent liability? By buying insurance! What the Indian Railways needs to do is to buy group accident insurance – all the ex-gratia payments will then by paid out by the insurance company, and the railways will only pay a premium to these companies, thus hedging out the risk! And this process will help put a price on railway safety!

How is that? Let us say that given the railways’ bad record in safety, and its continued promises that safety will be improved each year, the railways decides to take up group accident insurance on an annual basis. Let us say that there is a competitive bidding process among general insurers in India (both public and private sector) to provide this insurance (railways is a large organization, and insuring them will be a matter of prestige, so companies will bid for it). The premium as determined by this competitive bidding process is the price of railway safety!

We can do better – instead of buying one overall policy, the Railways can think of insuring different routes separately, or perhaps zones. This will help put a price on the safety of each route or zone! There will be some transaction cost, of course, but price discovery will happen, and we will be able to put a price on risk!

But then, this is all wishful thinking. It is unlikely this will happen because:

1. Given the cash accounting system followed by the railways, there is no incentive to hedge contingent liabilities
2. Buying insurance means increasing scrutiny. The railways will not want to be scrutinized too hard. It is currently an opaque organization and it will want to be that way.
3. Given the railways are wholly government owned and there are government owned general insurers, there might be some collusion which might  result in underpricing the risk.
And so forth…

Nevertheless, the point of this post is that it is possible to put a price on safety!

## Pricing fines for ticketless travel

In large mass transit systems such as those in Mumbai (or even Chennai), ticket checking turnstiles can significantly slow the flow of human traffic. The sheer number of passengers that use these transit systems daily makes it impossible to check the ticket of each and every traveler. Hence, the Railways, rather than checking the tickets of every passenger, instead relies on random checks. During these random ticket checking efforts, people traveling without a ticket are asked to pay a fine. This, the Railways hope, will be deterrent enough for people to purchase tickets before travel.

However, rather than ensuring deterrence, what this system has resulted is in an informal “ticketless travel insurance” economy. The concept is simple – rather than buying a ticket from the official ticket counter, you instead buy protection from an “informal insurance provider”. For a nominal “premium” (believed to be in the range of Rs. 100 per month) these providers insure you against ticketless travel. In other words, in case you get caught by the ticket checkers during the course of your “insurance”, these “insurance providers” step in to pay your fine! Check out this article in The Hindu about how these insurance providers work (WARNING: The link isn’t working too well for me, and is taking me to a third party site a few seconds after loading The Hindu page, so be careful before clicking through).

The very existence of this market, however, implies that fines for ticket less travel are not being priced properly. The math is fairly simple: if the price of the ticket is $latex p$ and the probability of your ticket getting checked is $latex \frac {1}{N}$, then the fine for ticketless travel should be strictly greater than $latex Np$. If not, it works out cheaper for your to pay the fine each time you are caught rather than buying the ticket.

So what role is being played by these “informal insurance companies”? Risk management! People don’t like risk. While on an average your ticket might be checked only once in 30 days (number pulled out of thin air), there is no reason that you will not be pulled up for ticket less travel multiple times in a month. By outsourcing the risk to a central party who pools the risks (from several commuters), you have a steady cash out flow and are hedged against getting caught multiple times (you might get caught but your insurer pays the fine). In fact, this is how insurance works in other sectors also.

What should the Indian Railways do to drive these “informal insurance companies” out of business? Currently, if the fine is $latex S$, $latex S \le Np$. From this equation, you can see that the Railways can do one of three things so that this inequality gets reversed – the price of a ticket can be reduced – but that would be equivalent to cutting off the nose to spite the face, for it would have significant adverse impact on the railways’ revenues. Next, N can be reduced, or in other words the frequency of surveillance be increased. This, too, is not easily implementable since the Railways will have to invest in additional resources to check tickets. The last option is to increase $latex S$, and there is nothing that prevents the railways from doing this!

How will this work, though? By raising the cost of fines for ticketless travel while keeping the frequency of ticket checking constant, the “premium” a commuter will have to pay to these insurance companies will increase. If the fine amount is increased to a certain level, the premium a commuter will have to pay to buy ticketless travel insurance will exceed the price of buying tickets! And the insurance market will implode.

While this seems like a simple solution in theory, I’m not confident of it being implemented any time soon. Who knows – one might have to go to the Union cabinet to increase the level of fines in local trains. That’s how our railways is structured.

## Minimum Support Prices

In India, we have this concept of “Minimum Support Price” for agricultural commodities. It is basically an unlimited put option written by the Government in order to protect farmers against not getting “appropriate remuneration” for their produce. In that sense it can be thought of as an implicit subsidy towards agriculture. There is merit in the argument in favour of such a measure – agriculture is a fundamentally high risk business and in the absence of such safety nets, not enough people might take the risk to sow a particular crop, leading to shortages.

On the other hand, it can be distortionary too. If the MSP is set too high, it can lead to a glut in that particular crop in that year, at the cost of other crops, leading to shortages in the latter. Hence, it is a tool that is necessary but one that should be used with care.

Now, the MSP has to be set in advance – so the MSP for the 2013-14 season has already been set.  This is again a risky move but a necessary move – farmers need to know the minimum amount they can get for each crop before they make their sowing decision.

The figure on shows the Compounded Annual Growth Rate (CAGR) in the MSP of a few important agricultural commodities between 2007-08 and 2013-14. Notice that the CAGR is lowest for crops such as wheat or rice, and high for crops such as Tur Dal or Moong Dal. Under the current Public Distribution System (PDS), families below the poverty line get rice and wheat at subsidized rates, but not pulses. Note that I’m only mentioning facts and not trying to suggest any causation here.

Interestingly, the MSP for coarse grains such as Ragi and Bajra has also grown significantly faster than that of rice or wheat. Also note that prices of cotton and jute have grown rather slowly over the period of consideration.

Now, while this tells us by how much prices have changed in the last six years, it is also pertinent to see how the prices have changed – did the price rise consistently over the last 5-6 years or were there some discontinuities? The next figure tries to address this issue.

The figure on the left here charts the actual year by year growth in the Minimum Support price of the crops under consideration. To me, two things jump out from this graph – apart from sugarcane, there was a steep increase in the minimum support prices of all commodities between 2007-8 and 2008-9. You might want to be reminded that India went to polls in the summer of 2009 and Maharashtra, a prime sugarcane growing state, went to polls in the winter of the same year. Again, I don’t want to claim any causation.

Then, from 2009 to 2012, minimum support prices of these commodities remained largely constant – perhaps compensating for the large jump from 2008 to 09? And then again there was a spike from 2012 to 2013. There is no such jump from 2013 to 2014, though. Note that the nation goes to the polls in 2014.

Tur and Moong dal, however, have seen a rather secular increase in prices in the last five-six years.

How the proposed Food Security Bill will affect the MSP is left as an exercise to the reader. Comments are open.

PS: Data that I’ve used for this post is available at the website of the Commission for Agricultural Costs and Prices.