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Advertisers want information about your tastes and habits so they can decide how much they are willing to pay to advertise at you.  That information is stored by your web browser on your hard drive.  Did you know that every time you access a web page you freely hand over that information to a broker who immediately sells it to advertisers who then immediately use it to bid for access to your eyeballs?

Here’s how it works.  Internet vendors, say Amazon, pass information to you about your transactions and your browser stores them in the form of cookies. Later on, advertisers are alerted when you are accessing a web page and they compete in an auction for the ad space on that page.  At that moment, unless you have disabled the passing of cookies, your browser is sending to potential advertisers all of the cookies stored on your hard drive that might contain relevant information about you.

However, many of the really valuable cookies are encrypted by the web site that put them there.  For example, if Amazon encrypts its cookies then even though your browser gives them away for free, they are of no use to advertisers.

That is, unless the advertisers purchase the key with which to decrypt your cookies. And indeed Amazon will make money from your data by selling its keys to advertisers.  It could sell them directly but it will probably prefer to sell them through an exchange where advertisers come to buy cookies by the jar.

The interesting thing about the market for cookies is that you are the owner of the asset and yet all of the returns are going to somebody else.  And its not because your asset and mine are perfect substitutes.  You are the monopolistic provider of information about you and when you arrive at a website it is you the advertisers are bidding for.

How long will it be before you get a seat at the exchange?  Nothing stops you from putting a second layer of encryption over Amazon’s cookies and demanding that advertisers pay you for the key.  Nothing stops me from paying you for exclusive ownership of your keys, cornering the market-in-you, and recouping the monopoly profit.

File under “Feel Free To Profit From This Idea.”

(I learned about the market for cookies from Susan Athey’s new paper and a post-seminar dinner conversation with her and Peter Klibanoff, Ricky Vohra, and Kane Sweeney.)

(Picture:  Scale Up Machine Fail from http://www.f1me.net)

This was Mallesh Pai last month:

Everyone here has heard about price discrimination. I know something about your willingness to pay (from other data about you or people like you), and use that to charge you a ‘better’ price. This has mostly been restricted by some combination of ethics, vague legal standards and technology to use ‘coarse’ information, e.g. your age (student/ senior discounts), your address (mailed coupons), and so on. As we pointed out a few months back there are cleverer methods on the way. But today, I think I’ve seen the best yet. A company calledKlout (indubitably with the cooler K-based variant of the spelling) looks into your social network and offers a ‘score’  estimating the influence you have. Some geniuses have decided that one’s ‘Klout score’ might be a good way to discriminate on what website you see (and indeed, what free swag you get offered): http://mashable.com/2011/06/22/klout-gate/ .

And this is Spotify this week proving him right.

The Spotify invites are part of the Klout Perks program, which rewards top influencers with special deals based on their interests and comprehensive Klout score rating. People who are rated as influential on Klout get access to the free trial version of the music service. They can also get a free month of Spotify’s premium service if enough people within their community sign up for the music service.

“The Spotify guys actually reached out to us about launching in the U.S. They had been using Klout and thought it was really cool,” said Klout CEO Joe Fernandez. “We talked a lot about how to hit the people in middle America that are also early adopters but don’t read the tech blogs and stuff.”

In January I made a prediction and kept it a secret.  Now I can tell you what it was.

For fun I wanted to see how well I could predict the Economics PhD job market. As a simple test I tried to predict who would be selected for the Review of Economic Studies Tour, a kind of all-star team of new PhDs. Here was my predicted list

1. Gharad Bryan (Yale)
2. Matt Elliot (Stanford)
3. Neale Mahoney (Stanford)
4. Alex Torgovitsky (Yale)
5. Glen Weyl (Harvard)
6. Alex Wolitzky (MIT)
7. Alessandra Voena (Stanford)
8. Kei Kawai (Northwestern)

And here is the actual list (the RES Tour website is here.)

1. Alex Wolitzky (going to Stanford?)
2. Daniel Keniston (MIT, going to Yale)
3. Mar Reguant (MIT, going to Stanford GSB)
4. Kei Kawai (going to Princeton?)
5. Alex Torgovitsky (coming to NU)
6. Alessandra Voena (going to Chicago?)
7. Peter Koudijs (Pompeu Fabra, going to Stanford GSB)

So I got 4 out of 8.  (There are usually 7 people, and I predicted 7 originally, but I updated it the next day adding Kawai to the list.  I had been so involved in recruiting students from other schools that I had completely forgotten about our own star student Kei Kawai and as soon as I remembered him I added him to the list.)

I previously blogged about Torgovitsky, Mahoney, and Koudijs.

You can see why I wanted to keep the prediction a secret until the market was over.  You can verify my prediction by cutting and pasting the text in this file and generating its unique SHA1 hash (a digital signature) with this web tool and cross check that it is the hash that I originally posted here, and that I tweeted here, and that is reproduced below.

f502acfb48395d6ab223ca30803f98b9bd6fd6ce

(Here is the original prediction before I added Kawai, and here is the hash for that one.)

I did this as an experiment to see how easy it is to predict job market outcomes.  At the time I made this prediction I had read the files of each of these candidates and interviewed most of them.  I didnt know where else they had interviews and I made the prediction before the stage of flyout interviews so I had little information about how their job market was going overall.

Getting half right is about what I expected.  To me this is evidence that the market is hard to predict even after having interviewed the candidates. In particular I take it as evidence against the cynical view that the market herds on certain candidates early in the process.  Indeed I would not have changed my prediction much even a week or two later when flyout schedules were in place.

Incidentally the Review Tour rosters say something about the strength of PhD programs.  Here’s a breakdown of the last 6 years and where the tourists received their PhDs:

MIT 12
Harvard 7
NWU 4
Yale 3
Stanford 3
Stanford GSB 2
BU, Duke, LSE, Michigan, NYU, Penn, Princeton, Ohio State, Stern, UPF, UCL —  1 each

Northwestern is doing very well!  (In addition to producing stars, we also do well hiring them.  3 from the tour in the past 6 years, including Alex Torgovitsky this year, an outstanding hire.)

Also I understand that a team is at work creating the web tool that I suggested here for creating and managing secret predictions.  If and when it hits I will announce it here.

You probably heard about the Facebooks of China. Facebook and Twitter are blocked there and filling the vacuum are some homegrown social networks. Obviously the biggest issue with this in the particular instance of China is freedom of information and expression, so the thought experiment I will propose requires a little abstraction to focus on a separate issue.

Sites like Renren and Kaixin001 are microcosms of today’s changing China — they copy from the West, but then adjust, add, and, yes, even innovate at a world-class level, ultimately creating something unquestionably modern and distinctly Chinese. It would not be too grand to say that these social networks both enable and reflect profound generational changes, especially among Chinese born in the 1980s and 1990s. In a society where the collective has long been emphasized over the individual, first thanks to Confucian values and then because of communism, these sites have created fundamentally new platforms for self-expression. They allow for nonconformity and for opportunities to speak freely that would be unusual, if not impossible, offline. In fact, these platforms might even be the basis for a new culture. “A good culture is about equality, acceptance, and affection,” says Han Taiyang, 19, a psychology major at Tsinghua University who uses Renren constantly. “Traditional thinking restrains one’s fundamental personality. One must escape.”

Goods (like social networks) that have bandwagon effects create the greatest value when the size of the market is largest. But that same effect can cause convergence on a bad standard. One argument, very narrow of course, for trade barriers is to prevent that from happening. We allow each country to develop critical mass in their own standard in isolation before we reduce trade barriers and allow them to compete.

Bryan Caplan wonders whether economic theory is on the decline. Here are some signs I have noticed:

1. Econometrica, the most theory-oriented of the top 4 journals has a well-publicized mission to publish more applied, general interest articles, and this is indeed happening.  This comes at the expense of pure theory as well as theoretical econometrics.
2. The new PhD market was, on the whole, difficult for theorists this year.  Strong candidates from Yale, Stanford, NYU and Princeton were placed much lower than expectations, some without a job offer in North America as of yet.  As far as I can tell, there will be only two junior theorists hired at top 5 departments.

But there are many positive signs too

1. Theorists have been recruiting targets for high-profile private sector jobs.  Michael Schwarz and Preston McAfee at Yahoo!, Susan Athey at Microsoft for example.  In addition the research departments in these places are full of theorists-on-leave.
2. Despite some overall weakness, theory is and always has been well represented at the top of the junior market.  This year Alex Wolitzky, as pure a theorist as there is, is the clear superstar of the market.  Here is the list of invitees to the Review of Economics Studies Tour from previous years.  This is generally considered to be an all-star team of new PhDs in each year.  Two theorists out of seven per year on average.  (No theorist last year though.)
3. In recent years, two new theory journals, Theoretical Economics and American Economic Journal:  Microeconomics, have been adopted by the leading Academic Societies in economics.  These journals are already going strong.
4. Market design is an essentially brand new field and one of the most important contributions of economics in recent years.  It is dominated by theorists.

In my opinion there are some signs of change but, correctly interpreted, these are mostly for the better.  Decision theory, always the most esoteric of subfields has moved to the forefront as a second wave of behavioral economics.  Macroeconomics today is more heavily thoery-oriented than ever.  Theorists (and theory journals) are drawn away from pure theory and toward applied theory not because pure theory has diminished in any absolute sense, but rather because applied theory has become more important than ever.

Professor Caplan offers some related observations in his commentary:

…mathematicians masquerading as economists were never big at GMU, and it’s hard to see how they could do well in the blogosphere either.

I am sure he is not talking about Sandeep and me because we are just as bad at math as all of the other bloggers who pretend to be economists.  But just in case he is, I invite him to take a look around.  Finally,

My econjobrumors insider tells me that its countless trolls are largely frustrated theorists who feel cheated of the respect they think the profession owes them.  Speculation, yes, but speculation born of years of study of their not-so-silent screams.

He is talking about the people who anonymously post sometimes hilarious, sometimes obnoxious vitriol on that outpost of grad student angst known as EJMR. I wonder how he could possibly know the research area of anonymous posters to that web site? Among all the economists who feel cheated out of the respect that they think the profession owes them why would it be that theorists are the most likely to troll?

You can find it here, thanks to a reader Elisa for hunting it down. The core is paragraphs 43-112 (starting on page 27) which lay out the new rules. I will give some excerpts and my own commentary.

The regulations break down into 4 categories: transparency, no blocking, no unreasonable discrimination, and reasonable network management. Transparency is what it sounds like: providers are required to maintain and make available data on how they are managing their networks. The blocking and discrimination rules are the most important and the ones I will focus on.

No Blocking.

A person engaged in the provision of fixed broadband Internet access service, insofar as such person is so engaged, shall not block lawful content, applications, services, or non- harmful devices, subject to reasonable network management. (paragraph 63)

This is the clearest statement in the entire document. (Many phrases are qualified by the “reasonable network management” toss-off.  In the abstract that could be a troubling grey area, but it is pretty well clarified in later sections and appears to be mostly benign, although see one exception I discuss below.)  The no-blocking rule is elaborated in various ways:  providers cannot restrict users from connecting compatible devices to the network, degrading particular content or devices is equivalent to blocking and not permitted, and especially noteworthy:

Some concerns have been expressed that broadband providers may seek to charge edge providers simply for delivering traffic to or carrying traffic from the broadband provider’s end-user customers. To the extent that a content, application, or service provider could avoid being blocked only by paying a fee, charging such a fee would not be permissible under these rules. (paragraph 67)

No Unreasonable Discrimination

A person engaged in the provision of fixed broadband Internet access service, insofar as such person is so engaged, shall not unreasonably discriminate in transmitting lawful network traffic over a consumer’s broadband Internet access service. Reasonable network management shall not constitute unreasonable discrimination.

This rule is heavily qualified in the paragraphs that follow.  Here is my framework for reading these.  There are three typical ways a provider would discriminate:  differentially pricing various services (i.e. you pay differently whether you are accessing Facebook or YouTube), differentially pricing by quantity (i.e. the first MB costs more or less than the last), or differentially pricing by bandwidth (i.e. holding fixed the quantity you pay more if you want it sent to you faster, for example by watching HD video.)

The rules seem to consider some of these forms of discrimination unreasonable but others reasonable.  The clearest prohibition is against the first form of discrimination, by data type.

For a number of reasons, including those discussed above in Part II.B, a commercial arrangement between a broadband provider and a third party to directly or indirectly favor some traffic over other traffic in the broadband Internet access service connection to a subscriber of the broadband provider (i.e., “pay for priority”) would raise significant cause for concern. (paragraph 76)

Such a ban is clearly dictated by economic efficiency.  The cost of transmitting a datagram is independent of the content it contains and therefore efficient pricing should treat all content equally on a per-datagram basis.  This principle is the hardest to dispute and the FCC has correspondingly taken the clearest stand on it.

As for quantity-based discrimination:

We are, of course, always concerned about anti-consumer or anticompetitive practices, and we remain so here. However, prohibiting tiered or usage-based pricing and requiring all subscribers to pay the same amount for broadband service, regardless of the performance or usage of the service, would force lighter end users of the network to subsidize heavier end users. It would also foreclose practices that may appropriately align incentives to encourage efficient use of networks. The framework we adopt today does not prevent broadband providers from asking subscribers who use the network less to pay less, and subscribers who use the network more to pay more.  (paragraph 72)

So tiered service by quantity is permitted.  Note that the wording given above is off the mark in terms of what efficiency dictates.  It is not quantity per se that should be priced but rather congestion.  A toll-road is a useful metaphor.  From the point of view of efficiency, the purpose of a toll is to convey to drivers the social cost of their use of the road.  When drivers must pay this social cost, they are induced to make the efficient decision whether to use the road by comparing it to their their private benefit.

The social cost is zero when traffic is flowing freely (no congestion) because they don’t slow anybody else down. So tolls should be zero during these periods.  Tolls are positive only when the road is utilized at capacity and additional drivers reduce the value of the road to others.

So “lighter users subsidizing heavier users” sounds unfair but its really orthogonal to the principles of efficient network management.  In an efficiently priced network the off-peak users are subsidized by the peak-users regardless of their total amount of usage.  And this is how it should be not because of anything having to do with fairness but because of incentives for efficient usage.

There is one big problem with this toll-road metaphor when it comes to the Internet however.  The whole point of peak-pricing is to signal to drivers that its costly now to drive.  But when you are downloading content from the Internet things are happening too fast for you to respond to up-to-the-second changes in congestion.  It is just not practical to have prices adjust in real time to changing network conditions as dictated by peak-load pricing.  And without users being able to respond to congestion pricing their purpose would not be served by calculating prices ex post and sending users the bill at the end of the month.

Given this, it could be argued that a reasonable proxy is to charge users by their total usage.  It’s a reasonable approximation that those with greater total usage are also most likely to be imposing greater congestion on others.  And the FCC rules permit this.  (Note that in particular, what is implied by tiered pricing as a proxy for congestion pricing is not a quantity discount but in fact a quantity surcharge. The per-datagram price is larger for heavier users.)

Discrimination by bandwidth is not directly addressed.  It is therefore implicitly allowed because paragraph 73 reads “Differential treatment of traffic that does not discriminate among specific uses of the network or classes of uses is likely reasonable. For example, during periods of congestion a broadband provider could provide more bandwidth to subscribers that have used the network less over some preceding period of time than to heavier users.”

But the following paragraph comes from the section on Network Management.

Network Congestion. Numerous commenters support permitting the use of reasonable network management practices to address the effects of congestion, and we agree that congestion management may be a legitimate network management purpose. For example, broadband providers may need to take reasonable steps to ensure that heavy users do not crowd out others. What constitutes congestion and what measures are reasonable to address it may vary depending on the technology platform for a particular broadband Internet access service. For example, if cable modem subscribers in a particular neighborhood are experiencing congestion, it may be reasonable for a broadband provider to temporarily limit the bandwidth available to individual end users in that neighborhood who are using a substantially disproportionate amount of bandwidth. (paragraph 91)

At face value it gives well-intentioned providers the ability to manage congestion.  But there doesn’t seem to be a clear statement about how this ability can be integrated with pricing.  Can providers sell “managed” service at a discount relative to “premium” service?  One re-assuring passage emphasizes that network management practices must be consistent with the no-discrimination-by-data-type mandate.  So for example, congestion caused by high-bandwidth video must be managed equally whether it was from YouTube or Comcast’s own provided video services.

Finally, the rules permit what’s called “end-user controlled” discrimination, i.e. 2nd degree price-discrimination.  This means that broadband providers are permitted to offer an array of pricing plans from which users select.

Maximizing end-user control is a policy goal Congress recognized in Section 230(b) of the Communications Act, and end-user choice and control are touchstones in evaluating the reasonableness of discrimination.215 As one commenter observes, “letting users choose how they want to use the network enables them to use the Internet in a way that creates more value for them (and for society) than if network providers made this choice,”and “is an important part of the mechanism that produces innovation under uncertainty.”216 Thus, enabling end users to choose among different broadband offerings based on such factors as assured data rates and reliability, or to select quality-of-service enhancements on their own connections for traffic of their choosing, would be unlikely to violate the no unreasonable discrimination rule, provided the broadband provider’s offerings were fully disclosed and were not harmful to competition or end users.

While this paints a too-rosy picture of the consumer-welfare effects of 2nd degree price-discrimination (it typically makes some consumers worse off and can easily make all consumers worse off) it seems hard to imagine how you can allow the kind of tiered pricing already discussed and not allow consumers to choose among plans.

So the FCC is allowing broadband providers to rollout metered service, possibly with quantity premiums, and there is a grey area when it comes to bandwidth restrictions.  These are consistent with, but not implied by efficient pricing, and of course we are putting them in the hands of monopolists, not social planners.  They certainly fall short of what net-neutrality hawks were asking for but it was wishful thinking to imagine that these changes were not coming.

I think that the no-blocking and no unreasonable discrimination rules are the core of net-neutrality as an economic principle and getting these is more than sufficient compensation for tiered pricing.

Final disclaimer:  everything above applies to “fixed broadband providers” like cable or satellite.  The FCC’s approach to mobile broadband can be summarized as “wait-and-see.”

If Twitter bans the sale of usernames then they take away any incentive to squat.  But is the commitment credible?

While Twitter tries to work out how to make money, a Spaniard has sold his username on the site for a six-figure sum.

In 2007 Israel Meléndez set up a Twitter account under his first name. This year he was approached by the state of Israel, which wanted to buy @Israel from him for a quantity of dollars that, he told Spain’s Público newspaper, included “five zeroes”.

The sale went through despite Twitter’s stated policy of preventing username squatting and Meléndez, who runs adult websites for a living, said Twitter itself had advised the Israeli government on how this could be done.

“All the business of getting in contact with Twitter was done by them [Israel],” Meléndez said. “I never saw any emails [between them] and Twitter never contacted me, but if the @Israel account is open and working I imagine it means that Twitter had no problem with the transaction.”