Constrained Bliss Point

What am I going to do when I finally live in one place?

I’ve moved more than a few times in my life. During my early years I moved within New Jersey, one time that I can’t remember, and five or six that I can. Actually most of those moves were within the same town. Then at some point I went off to college, where moving in and out of one’s dorm room each year is part of the natural ebb and flow of semesters coming and going. Nowadays I find myself living in DC for some reason, and I have the feeling moving will be commonplace for the foreseeable future.

I kind of like moving around. That’s not to say I don’t like staying in one place — because I do. But there is no better way to get one’s material possessions in order than to pack them all up and head on out. One reason college is awesome is that you can pack up all your worldly belongings into a car and then drive away. There is something liberating about living with as few possessions as feasible. Then again, unpacking thereafter is a necessary consequence. I think I still have some boxes still packed in my basement from younger moves, and that’s been quietly nagging at me for years.

The truth is that packing up clears my head. There are never enough opportunities to fit the world so neatly into little boxes with cleanly demarcated edges. Some day I might live in the same house for years at a time. I think at that point I’ll need to take turns every few months boxing up a whole room and then unpacking it into a different configuration.

Dear Microsoft,

I used to not like you a whole lot. I was kind of mean, too, sometimes calling you the Evil Empire or something similar. I want to take this opportunity to apologize, and to try to explain myself.

A whole lot of people used to not like you. I admit I got swept up in the anti-Microsoft rhetoric and jumped on the bandwagon when I should have given it more thought. You know the whole FOSS-vs-MSFT posturing, people hating on Windows because it’s not free, stuff like that. I even came up with a whole tirade about the economics of monopolies and marginal cost pricing, how charging so much for Windows is inefficient. I was petty, and it was silly of me; I recognize this now.

Here is why I came around:

First, you gave $15k to Creative Commons at the end of their 2008 fundraising campaign to put them above their goal. That was big. And I know you’ve been funding CC for a while. They’re a cause I really care about, so it means a lot that you’d be such a supporter.

Second, you’re really not that bad. I read an argument that the Microsoft Windows monopoly really amounted to extracting economic rents from middle-class Americans and, through the Gates Foundation, channeling those funds to aid efforts in Africa. Not to mention, Windows gave everyone a standardized platform in the meanwhile, and that is really valuable.

Third, you’re just a profit-maximizing firm, after all. You have a duty to your shareholders to make as much money as you can, even if sometimes that means using underhanded tactics. Spreading fear uncertainty and doubt, or engaging in “embrace, extend, extinguish“, while uncool, isn’t out of the ordinary in the business world. I can’t blame you for the system you’re a part of.

So it took me this long to realize that, no, Microsoft is not evil. You’re just doing your thing, you know? Maximizing profits and all is hard work. And right now Google is in a position to do a lot more damage to freedom than you are. I hear Windows 7 is pretty awesome, too.

I hope you accept my apology. Give Google a hard time for me, okay guys?

Amicably yours,

-Frank

I had a thought while sitting in class the other day. (This is, in fact, less common than you might imagine.) In loose terms, graduate school can be cast as a constrained optimization problem. Students have preferences over their classes, so that they prefer to spend time on the topics they enjoy learning about. I for one used to like microeconomics, but now I am leaning toward macro, for reasons to be discussed in the future. Students also prefer not to fail. So, other things equal, they will spend more time on classes that they’re doing poorly at.

I posit that, for whatever reason, not liking a class and not doing well in a class are correlated. For students who are sufficiently intelligent, and thus not close to failing any one of their classes, this doesn’t matter. They can spend the most time on the classes they like most. Those are good times.

But if you are up against the failure constraint, you will tend to be spending less time on the classes you like and more time on the classes you need to make sure you pass. It is all the worse if the classes you are doing poorly at are also those you do not enjoy very much. (This is probably the case: see above). Those are not very good times.

Here’s hoping my constrained optimization problem has a feasible solution.

Last week I purchased Tegan & Sara’s new album Sainthood, which has quickly become my second favorite musical purchase this year. For those of you just tuning in, Tegan & Sara are Canadian identical twin lesbian singer-songwriters, which is even more awesome than it sounds. They are streaming their new album on Myspace, so if you’re into that sort of thing you can navigate over there and listen to their glorious tunes as you read the rest of my post. I implore you: such a decision is full of epic win.

Even though they are like seven years older than I am, I feel like I’ve been watching (listening) to them grow up. I was introduced to Tegan & Sara through Grey’s Anatomy, back when it was good. I think I bought their album So Jealous first, which was new at the time, and which, while I still like it a lot, was and stayed my least favorite of their albums. So Jealous was their third-or-so album at the time, not including a beautiful little gem called Under Feet Like Ours which they released on cassette when they were just starting out, and which you could order from a website that charged you in Canadian dollars.

Under Feet Like Ours was insanely worth the purchase. It is incredibly genuine, without the studio finish that comes with big budgets and famousness, and all the better for it. You can hear how T&S developed and matured through their albums. Every album is different, every one is good, and they all lead to where they are right now. Which, right now, just happens to be Sainthood, but it used to be The Con, and before that So Jealous (and then If It Was You and then This Business of Art).

And some day in the future they will grace us with something we will have been waiting for the whole time.

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.

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.

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.

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.

Two quick things:

First, the fan on my laptop died last weekend, rendering me without a PC at home. I can’t blame the poor thing; it’s been on it’s last legs for months now, and the laptop itself is over four years old. Without the internets distracting me, I’ve seen a boost in productivity, though my blogging will likely be more intermittent than usual.

Second! my favorite non-profit organization Creative Commons has kicked off its annual fundraising campaign. You should consider donating so you can get a sweet t-shirt, and also to support a worthy mission. Saving the world from failed sharing is a noble goal, the people are amazing, and come on, look how good you can look in a CC t-shirt (that’s me in my superhero pose, for those of you keeping score at home). I cannot recommend Creative Commons highly enough. And tell your friends to send them lots of money too.

Here’s a really cool instance of life hacking I heard the other day from Brian Rowe:

First, an introduction. When you’re at a restaurant, and you pay by credit card, how do you decide what to tip? That is, how do you choose an exact amount that’s within the acceptable range? Two common strategies are 1) to choose a round number for a tip and add it to the (not round) total, or 2) choose a value for the tip that will make the final amount a round number.

I have heard that one way is less secure, though I can’t remember which, because the person running the bill can input another amount and you wouldn’t know just from checking your credit card statement. I don’t know how credible this threat is. But now I happen to have a solution.

You can use a checksum for your checks. Leave a final amount such that the last digit is equal to the sum of all the digits preceding it. For example, instead of paying $42, leave a tip such that the amount you pay is $42.06. This method is straightforward, awesome, and helps curtail credit card fraud.