Economists Hate Math

So, this is the inaugural post to this blog. And I am dedicating it to the impetuous for starting the blog, namely, economics. I have an interest in economics for a number of reasons, one of them being I am interested in my financial well-being, especially because I am paying student debt. It also intersects with my political interests, and with, well the fact that I like money.

When I was in engineering school, there was a common joke amongst my fellow to-be rocket scientists. That joke was a mathematical formula, and it went like this Lim (GPA -> 0) AERO = BMGT, or in English, the limit as GPA approaches 0 of an Aerospace Major is a Buisiness major, which is a fancy way of saying that most Aero students who couldn't keep up with their coursework eventually became Business majors. This might as well have been Lim (GPA -> 0) AERO = ECON, which is to say that a fair amount of them became Economics majors instead of Business majors. This has a follow-up, in that a lot of Math majors make money tutoring Econ majors, but we'll get to that.



This is a bit of snark, but as I've taken an interest in economics through the housing bubble and the following crisis, I've found it to be depressingly true. And there are reasons for it; most people going into Engineering do it for similar reasons. Engineering is fun, especially aerospace engineering. If you like space and are a dork, or you like fast jets, then you get into engineering probably because you figure that you're not going to make the cut to be a test pilot or an Astronaut. Heck, even if you think you might be a test pilot or an Astronaut, Aerospace Engineering is the degree you want if you want to have a one-up on your fellow pilots or Astronauts. Engineering is also a smart career choice if you want to secure a stable income, doing work that isn't boring. You go into engineering because you want more hands-on-stuff than theoretical stuff; you want to deal in nuts and bolts, otherwise you'd just be a physicist where you could talk about all the cool science theory that goes into figuring out how the universe works, or some other area of science where you get to do cool lab experiments rather than design working technology, or if you didn't care about the experiments or theory, you might go into being a pure math major because you like fiddling with math equations.

That's all assuming, though, that you can hack the math. 'Hard' science, math, engineering-- they're all very math intensive. Some people hate math; they don't want to be stuck doing equations for the rest of their life. They imagine that it must be something like doing endless hours of calculus homework. And to be fair, especially in the degree-attaining part, and in the upper reaches of Masters and Doctorate work, it is a lot of crunching numbers that make your high-school pre-calc homework look like child's play.

So people who don't like math tend to eschew the math-intensive studies. You can choose to be an artist, or get some other liberal arts degree, for example. English. Woman's Studies. Theater. Music. History. That's the choice a lot of people make, because contemplating spending a career doing math homework isn't generally appealing, even if it means you get to do cool things as well. But, liberal arts degrees don't really pay so well.

That creates a new subset of people: people who want to get paid, but don't want to do a lot of math. These people start contemplating doing some math, but not math that is too complex. There's the social sciences, which have some math but are mostly study and qualitative. Psychology, for those who are interested in people on an individual basis. Sociology, for people interested in people on aggregate. Political Science, for people who like people on a political basis. So on and so forth. These pay better, or at least some of them do, but not very much.

If you're looking to get PAID paid, the straightforward way of looking at it is Business, where you have to do some math, but it's generally simple and you get paid. Accounting; it's a steady paycheck, if boring, but it means you get paid, because you're handling the money. Or business management, because the guys making the business calls get paid even more. But if you're ok at math and you want to get paid even more, there's Economics, where you theoretically will get paid even more for trying to predict how people will spend their money.

Now, to be fair, there are people who go into all these other non-science things because it's genuinely what they like, and they don't care one way or the other about math. I, for example, am not so fond of it, but I'm good enough at it that it wasn't a barrier for entry into doing what I wanted to do as a career (yes, even rocket scientists can hate math, they just have to be good at it anyway). And to be fair, there are even Economists who like math but genuinely like Economic theory because it presents them with interesting math puzzles.

Here's the thing, though-- those are the guys who get paid a lot to tinker with the math behind huge-money investment stuff like quantitative investment. Because the fact is that economics is a lot of math. More, it's a lot of numerical math, and trying to curve-fit data. This is why mathematicians are sometimes awarded the Nobel Prize in Economics-- math theory, when applied to economic problems, can yield some really powerful results.

This is interesting when it comes to politics for a good reason: the guys/gals who are good at math AND economics tend to have real jobs making real money in the real economy. That's why it's not surprising that, say, Tim Geithener has industry experience-- when you're good enough at math and economics, it's not so hard to go make millions running the numbers on say commodity exchanges or stock trades. For some, they make enough money, then start pursuing other interests, like public service. Others just retire early, or never get tired of making money.

What that means to the academic portion of Economics is that there are a few different types of Economists who go into the academic field, rather than the money-making field. They break down along several axis (this is a highly multivariate equation).

Axis 1: Wants money NOW <-> Wants to make money <-> Can delay gratification <-> Doesn't care about making money
Axis 2: Likes math <-> Good at math <-> Bad at math <-> Hates math
Axis 3: Likes economic theory <-> Good at economic theory <-> Bad at economic theory <-> Hates economic theory

Here's the problem with that: economists who are bad at/hate economic theory, bad at/hate math, and want money now/want to make money-- well, there's a place for them, because of another equation, namely:

Power = f(Money), or power is a function of money, be it directly proportional or some other formula.

Money != Power, for example, there are Sox fans who you couldn't pay a million dollars to root for the Yankees. But money and power are definitely strongly related, be it directly proportional, or more likely according to some complex other function. There are plenty of Sox fans who would root for the Yankees if you paid them a million dollars, but not if you paid them 5 bucks. That means people with an interest in power (and people interested in money) have work for people who can write economic theory, particularly people who can write economic theory that supports their interests in power and/or making money. These are generally political think tanks, which produce an inordinate amount of writing on economics.

Economists who wants to make money and are good at/like math, however, can make more money by going to work for people who are more interested in making money then they are in attaining power. Which is how you end up at someplace like Goldman Sachs, or the quantitative investment funds, etc. etc. etc.

Economists who like / are good at economic theory, want money, but are bad at/hate math can make more money in academics than in the political think tanks, because they can struggle through the math to write quality papers that get them key academic posts. Academics is also the place for people who are like/are good at math, like/are good at economic theory, and can delay gratification / don't care about making money.

What this means in parsing economic theory, though, is that the majority of people who are writing about economic theory are bad at, or likely flat out hate, math. By volume, most of the material readily available to the public is written by those think tanks, in turn funded by people who want to make money or attain power. Even in academia-- if you assumed an equal ratio of people who were good at/like math to people who are bad at/hate math, then half of it would be coming from people who were bad at math. Realistically, it's much more than half, because the stronger monetary incentive for economists who are good at math is to go make money outside of academia. Meaning that the greater bulk of economic material you read is written by people who are bad at/hate math.

And it shows.

It shows because economists are always making these simplifying assumptions, assumptions that are so simple that similar behavior in engineering would mean we didn't have cool things like jet engines or rockets. From Akin's laws of spacecraft design: everything is linear if plotted on a log-log curve with a fat enough marker.

My favorite of these is the 'rational actor' assumption. This is the assumption in microeconomics that people will always make the most rational decision possible when it comes to money. Then then gets blown way out of proportion when you get to macroeconomics, which, especially in conservative economic thinking, tries to incorporate all the assumptions that go into the mathematical model of microeconomics into a whole, closed system.

The thing is that it's a blatant and obvious lie.

People make bad decisions with their money all the time; in fact it's fair to say that everyone has made a bad decision with money at some point, and that there are significantly large numbers of people who make bad decisions with money most of the time. That is how we end up with 'bubbles,' after all, which economists recognize as a 'patch' to their general theories, but don't incorporate throughout.

More, that assumption implies a much deeper assumption: that the decision makers are operating in a perfect information environment, where they have sufficient information to tell a 'good decision' from a 'bad decision' in the first place. But that's not true either.

Another gem I just picked up today: "The fundamental proposition of monetary theory is that an individual household can adjust its money stock to the amount demanded, but the economy as a whole cannot. " The first part of which is also a big fat lie. The fundamental assumption wrong with the statement "an individual household can adjust it's money stock to the amount demanded", that is not always true here, is that the household can always find a way to find enough money to pay for the things it needs if it (a) cuts spending (b) invests right, or (c) reduces it's debt.

In the real world, sometimes you don't have enough money to invest in the first place, much less reduce your debt without declaring bankruptcy. For plenty of households, declaring bankruptcy or defaulting on debt doesn't help because you don't have sufficient income to meet your financial needs even if your debt was offloaded, not to mention that declaring bankruptcy cuts you off sharply from credit, meaning that it reduces the amount of credit available. This creates a scenario in which money stock != amount demanded. Which is what's happening in a lot of the country-- many households have reduced debt by going into foreclosure on their homes, have insufficient funds to invest sufficiently to increase their income appreciably, leaving the only option to cut spending, and cutting them off largely from access to credit.

But recognizing that would require more complex mathematics to describe in monetary policy, which would make the math harder to deal with. So monetary theorists don't do it, because they hate math.