Archive for the ‘Economics’ Category

More on celebrity

Saturday, July 10th, 2010

In re-reading my previous post, I notice I was less than diligent in ensuring the case for taxation of celebrity was well-supported. I imagine that someone not quite as tax-happy as I am would be able to argue that, no, celebrities are not hurting anyone, and taxing them impinges upon their economic freedom or something like that. I’ll just lay out a few more ideas that hopefully clarify my position.

The urge to become a celebrity is not a societally-useful urge, in and of itself. Now, if by trying to become a celebrity, someone does something societally useful, then that’s another story. But we need not encourage children to grow up to be famous moreso than they are already encouraged. I’m willing to posit that the desire for fame is a consequence of the human condition, whatever that means. Likewise, for the same reason, I don’t think a tax on celebrity would significantly decrease the prevalence of this desire. But, even if it did, I’m willing to bet that nothing bad would come of it.

Next, the quantity of celebrities isn’t significantly correlated with societal well-being. If tomorrow there were twice as many celebrities, no one would be much better off — well, the new celebrities would, but the old celebrities would be worse off. I don’t know that society would be in a different position on net. My guess is that the attention we spent on our existing celebrities would nearly half, given the new targets of attention which sprung up. People have a more-or-less fixed proportion of their time, effort, and money that they spend on celebrity. I guess I’m just arguing that we don’t really need to be encouraging more people to go about becoming famous.

At its highest levels, celebrity is a rat race. Or an arms race, or a prisoner’s dilemma. For everyone who makes it, lots of others don’t, and precious little separates the haves from the have-nots.

I shouldn’t really advocate a tax on all celebrity, just a tax on excessive celebrity. I’m sure 90% or more of “celebrities” are just normal people who common folk recognize for some reason. Most people don’t make money on their celebrity. Even microcelebrities like David After Dentist, who do in fact make money off of their notoriety, do not make very much, at least not in the grand scheme of things. What it comes down to, really, is that I have a problem with large arbitrary lotteries paying off to people who haven’t provided a great deal of benefit to anyone.

I hope that clarifies things.

Taxing Britney Spears heavily

Friday, May 7th, 2010

First I’m going to note (or assume) some things about celebrity. Celebrity is a scarce resource. Celebrities are like monopolistically competitive goods since there’s only one of each but they can be substituted for other goods or other celebrities. I also assume that there are at least some classes of celebrities where they aren’t intrinsically valuable. For example, many people can sing and dance and be scantily clad on occasion, but only some people can be Britney Spears. I’m not sure if this is true, but I am assuming that some celebrities are just anointed, somehow chosen by the demigods of entertainment, for no particular earthly reason. The best example I can think of right now is Paris Hilton. She would just be another nobody with a sex tape on the internets if her family hadn’t been rich and famous.

If the above is a reasonable approximation of reality, then celebrities should be taxed. Specifically, the quantity we define as “celebrity” should be taxed.  Heavily. Notice this is not about taxing celebrities for doing productive things, but instead taxing them just because they have celebrity. The fact of the matter is that they already have lots of fringe benefits of being a celebrity, like getting to go to all the cool clubs and hanging out with all the cool people or whatever. And they should profit a little bit from their celebrity. But they shouldn’t profit to the tune of millions and millions of dollars.

I am thinking here of the case of Britney Spears. It’s my opinion that pretty much any young attractive girl with a decent singing voice could have replaced Britney Spears and would have had the same ride, except maybe she wouldn’t have gone crazy a while back. Celebrity in this case amounts to a huge arbitrary redistribution of wealth. Why Britney and not some other girl who could have made it? I can’t think of a reason. Since celebrity is an important resource, and a scarce resource of that, we should treat it as a public resource. And we should regulate it with some sort of average cost pricing, like we do with power plants and water companies.

Of course then we run into having to design mechanisms to track, measure, and tax celebrity. I know it’d be really hard to do. But I still think it would be cool.

Cocktail party theory of life

Friday, April 23rd, 2010

I want to revisit the “what is the meaning of life?” question with an economics bent: If life is an optimization problem, then what should we be optimizing? Put another way, if life is a constrained maximization problem, then asking “what is the meaning of life?” is akin to choosing and studying one’s objective function. In this case you could also choose your life’s purpose by selecting the right function and thus optimizing the right thing.

So then, what should we be optimizing? Perhaps we should try to be as interesting and personable and awesome as possible. There’s two things going on in there: 1) be awesome and interesting and doing cool things, and 2) be able to share what you’re doing with other people so they can be all “whoah that is awesome and interesting and you are doing cool things”. I think awesomeness is a very important quantity to be maximized, and the second point alludes to the fact that awesomeness is inherently subjective, and when awesomeness falls in a forest and no one is around to hear it it doesn’t make a sound.

I propose a novel theory, the Cocktail Party Theory of Life, to crystallize the above sentiments. You should live your life in order to optimize interaction at a cocktail parties. All your time outside of cocktail parties should be spent on interesting activities you can later share with people. Your work, or the projects you’re working on, should turn into good stories (“Let me tell you about the cool stuff I’ve been doing lately…”). Of course, most of what goes on at cocktail parties is social, so you should be comfortable navigating the social scene. You should be a good story teller. You should be personable and likable. You should know how to engage in conversation with another human being, and generate positive social interaction. And you should be genuinely interested in the people around you, because they’re what makes for a really good time at a cocktail party.

You have to be successful to even be invited to the cocktail party. You need to know your surroundings and what the people around you think are interesting. You have to be good at switching contexts: no one wants to hear about all the technical work you’ve done with NASA at a sports bar. If you don’t like going to cocktail parties alone, you should have a partner you can rely on to navigate the social scene with you. And, of course, you should enjoy a few drinks, though not to excess, unless you’re into that sort of thing. It’s your life, after all.

High point

Saturday, January 23rd, 2010

Yesterday was unequivocally the high point in my graduate school career to date. The big event was our first Micro 2 class, in game theory. Micro was the only class we hadn’t had yet, and my expectations were high: Econometrics is typically dry and exceedingly difficult, and our Macro class is shaping up to be intense, courtesy of our new professor. I was hoping that Micro could be the class to keep me sane this semester.

Luca Anderlini is our professor for Micro. He’s the new Director of Graduate Studies too, so my performance in Micro serves the dual role of not failing out of the program and not embarrassing myself in front of the guy running things. I had seen him present a paper last semester, and this gave me high hopes. He had a sense of humor, an entertaining manner of lecturing, and a way of making the topics at hand seem relevant.

Let me cut to the chase: my hopes were realized. The lecture was interesting, but most important, something crucial happened, something I have been waiting my entire time at Georgetown to hear someone admit. Before Professor Anderlini got into the meat of the lecture, he made a caveat. He expressed to us, in no uncertain terms, that math is not the point of what we’re doing. While, he explained, he enjoys math a great deal, and even considered a career in math, he stressed that math is a just a tool to clarify our thinking. Anyone can reason, he argued, and make a convincing case. The key is that math is a rigorous formal language to express our ideas,  so that we can make sure we are not just deluding ourselves with words. Again, math is not the end, it is only the means.

That was the breath of fresh air I needed.

Supporting alcohol in Sudan

Monday, January 18th, 2010 is a person-to-person micro-lending website, which allows prospective do-gooders in the developed world to fund micro-finance operations for entrepreneurs in the developing world. I found out about Kiva around two years ago, and even though I gave a few gift certificates, it took me until today to make my first loan.

My lendee is so awesome that I felt the distinct need to blog about her. First, her name is Joice Pita, which is cool in and of itself. She lives in South Sudan, and runs a pub. I know very little about the Sudan — Wikipedia reminded me that Darfur is part of the country, and also noted that Sudan’s motto is “victory is ours” — but I can posit a guess that they could use more pubs. The thought of helping a pub-owner in the Sudan was too much to pass up.

Here’s her blurb, straight from her Kiva page:

Joice Pita is currently in the business of selling local alcoholic beverages, beer, and soda, and is requesting a loan to stock more crates of beer and soda to sell. Joice is 33 years old and is married with a husband that is a soldier. She has 6 children, and her children go to school. With the extra profits from her loan, she hopes to be able to open a hotel.

Now try and tell me that is not a cause worth funding. I thought so.

If you have some spare time, definitely check out Kiva. The money you put in isn’t a donation or a handout (though you can donate to itself to cover their operating expenses), which means that when your lendees pay you back, you can find new lendees and start the cycle over. You can even withdraw the money in your account after you’ve done some lending with it. So, if your bank account has some extra money in it, and you decide that instead of earning one percent interest you want to help save the world, you should head over to and start lending, like rite nao.

FOSS crashes economy?

Thursday, November 19th, 2009

Not to be alarmist or anything, but Free and Open Source Software (FOSS) is probably to blame in bringing the global financial system to its knees. A few months ago I came across an intriguing article in the New York Times about fat tails and gaussian copulas. It was a pretty good piece, worth at least a glance.

The interesting part begins on page six. Long story short, JPMorgan developed a way of using maths to quantify financial risk into a dollar value. Value at Risk, or VaR, as it was abbreviated, was a useful tool internal to JPMorgan. Then they did something totally bonkers: they gave VaR away. Anyone who wanted to learn and implement VaR could do it, and JPMorgan would help you out. Why would they just give away such a valuable piece of proprietary technology? This quote sums it up nicely:

As Guldimann wrote years later, “Many wondered what the bank was trying to accomplish by giving away ‘proprietary’ methodologies and lots of data, but not selling any products or services.” He continued, “It popularized a methodology and made it a market standard, and it enhanced the image of JPMorgan.”

The story ends with a score of financial firms coming to rely too heavily on VaR, then they overextend themselves, get lulled into a false sense of security, and finally fat tails come in and kick everyone’s asses. Also the economy exploded.

I can’t help but wonder if it was the tactically-superior give-it-away model of FOSS that allowed JPMorgan’s mathematical monstrosity to consume the world’s financial sector in a blaze of nihilist glory.

A different kind of difficult

Thursday, November 12th, 2009

In a previous post I challenged Georgetown’s economics department to “bring it” and kick my ass as best it could. I’m happy to report that they succeeded in winning the first round. Their tactics were a bit sneaky and underhanded, but nothing I couldn’t have anticipated. The fact is that I haven’t been putting in enough time and effort to be learning the most and getting the best grades I can. But that will change: I’m gearing up for round two.

See, what they don’t tell you about serious graduate school programs is the extent to which you are expected to know everything without having been taught it. In undergrad, the professor would only test you on things you covered in class. In grad school, you are lucky if what the professor covers in class is vaguely useful. More than half of what I’ve learned so far has been outside the classroom. This trend will surely continue into the future.

There’s also the little caveat about expectations. Some classes grade homework assignments strictly and care more about answers than methods and effort; some classes don’t even bother to grade homeworks (though if you don’t do them you’re almost guaranteed to fail the exams). Some exams test whether you can regurgitate proofs seen in class, some test mechanical problem solving skills and intuition, and some want you to know damn near everything. Sometimes you may spend more than half of your allotted time on two questions that, you find out after the fact, were only actually worth 18% of the exam grade, and you didn’t get any partial credit on them besides, but that your last five minutes of scribbling on a seemingly unimportant question netted you the majority of your points (a question which, by the way, was worth almost half of the points on the exam). No, you shouldn’t expect all exam questions to be weighted equally, either.

I know how I’m studying for the next round of exams: memorizing proofs, practicing my mechanics, and trying to learn damn near everything. And I am not making any more assumptions about how many points each question is worth.

Why I like economics

Monday, October 19th, 2009

I’m an intuitive person: I’m more concerned with broad-reaching theories than with any particular instantiation of fact. I scored a solid N on the Myers-Briggs Type Indicator. That’s not to say I don’t like facts. On the contrary, theories need to be generalized from somewhere, and starting with the known state of the world is common sense. But I don’t operate in Sensing-land — I need to be able to clearly see the general pattern in order to understand something.

Framed this way, I like economics for the same reason I like engineering. The extensive maths used in both fields are a means of grounding one’s intuition in something substantial, something provable. Maths allow one to derive, from a set of axioms and real-world data, a bunch of consistent theorems, equations, etc. that describe the system the axioms (and data) generate. If your intuition clashes with your results, either you’re wrong or you made a math mistake. Here you have a very solid check to balance out your intuition.

This allows me to satisfy two competing objectives: first, I don’t want to spend all my time in math land; second, I don’t want my intuitions to be wildly off base. So I ponder my intuition, I learn the requisite maths, and then I can go write a bunch of equations to ensure that my intuition is correct.

Why internet research?

Thursday, October 8th, 2009

The internet is an unprecedented treasure-trove of quantitative data on social systems. Before now researchers could only dream of such data. I believe this provides the potentially fruitful opportunity to engage in formal, mathematical analysis of social systems (while remaining in a social-scientific vein, of course).

In the past century the field of economics underwent a mathematical revolution, focusing theoretical research on formal (mathematical) models to aid analysis and intuition, and empirical research to strengthen or rebut those models. This would have been impossible if the phenomena economics studies hadn’t been quantitative in nature; for example, if GDP numbers and employment data weren’t regularly compiled by developed nations, then modern macroeconomics could not have developed. This is one example of readily accessible quantitative data fueling a course of research, and surely there are others. (And perhaps the causation runs the other way too: when a group wants to study something, they do all they can to find good data, but this seems like the weaker direction.) Notable is the opposite case, though difficult to observe: when a particular field or direction of research is impossible because of a lack of useful data. Particular objects of study I’m interested in include “attention” or “influence,” which do not have clearly observable and measurable forms (what is the smallest unit of influence, anyway?); maybe something like “reputation”; or even abstract measures of happiness (utility, anyone?), which can explain why economics often treats consumption as a drop-in replacement. And so I turn to a study of the internet.

Out of the epic amounts of information generated by the plethora of internet-born social structures, data are lurking that could revolutionize the way we study social behavior. These data haven’t been compiled in appropriate forms yet — there is a lot of theoretical work to be done on what paradigm to use, how to aggregate the data, etc. I task Web Ecology with making sense of the morass of information, and turning it into useful data for researchers to study, build models around, and predict emergent phenomena. Once relevant data are identified and available, we can get to work on the fun stuff: the science of understanding people.

Economics has the most developed mathematical tool set for studying social behavior of any social science. With access to the data described above, researchers have an opportunity to apply those tools to something completely different, and maybe supremely worthwhile. For example, perhaps everyday social interaction (which we can approximate by interactions on the internet, maybe) can be modeled using the tried-and-true machinery of neoclassical microeconomics. Consumers of “reputational” or “social” goods would optimize utility given their (expanded notion of) budget constraints. What would be the arguments to their utility functions? What would prices and income represent in this system? All the quantities would represent something different, but all the relationships would stay the same.

Possible? Sure. Likely? Not really. But when we are harvesting the right data from the internet, we will be able to put these ideas to the test. We will be able to make changes to the theoretical apparatuses we have, develop some we haven’t even imagined, and set those to work helping us better understand human behavior.

Pride comes before the fall

Sunday, September 13th, 2009

I’m in my first year of the economics PhD program at Georgetown University, and classes started last week. Everyone I talk to says how hard the first year is. Everyone. They are so certain of the time and effort we’ll have to put in, the sixty hours a week, the studying every day in the library. I’m going to be honest and say that I don’t entirely believe them.

Of course it will be tough. Tough is what I signed up for. But economics is not rocket science. And let’s be honest, I’m kind of good at school. At this point in my life I’ve been through a lot of it, and I’ve gotten my ass kicked a fair number of times. I am certainly no n00b.

So you know what? I hope the econ department gives me its worst. I’m ready. I can take it.

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This work is licensed under a Creative Commons Attribution 3.0 Unported.