What Computer Science Can Teach Economics

eldavojohn writes "A new award-winning thesis from an MIT computer science assistant professor showed that the Nash equilibrium of complex games (like the economy or poker) belong to problems with non-deterministic polynomial (NP) complexity (more specifically PPAD complexity, a subset of TFNP problems which is a subset of FNP problems which is a subset of NP problems). More importantly there should be a single solution for one problem that can be adapted to fit all the other problems. Meaning if you can generalize the solution to poker, you have the ability to discover the Nash equilibrium of the economy. Some computer scientists are calling this the biggest development in game theory in a decade."

Comments

The problem is not an efficient algorithm

[iamacat]

Polynomial time approximate, probabilistic or special case solutions to NP problems are wide spread. The problem is that real human being in economics can not be easily described by an equation - and when they can be, they quickly change their behavior based on that knowledge. What both computer scientists and economists need to learn is stop being geeks addicted to a single theory and start dealing with people.

Re:The problem is not an efficient algorithm

[gerddie]

Well, I'm not surprised there is such school. My impression is, that economists in general don't have a good grasp of math, specifically, they don't seem to understand the exponential function, otherwise they would not speak of "growth" all the time.
I'm not saying one should not take human behavior into account, but at least they should get the boundary conditions right, and one of those is that our resources are limited.

another intersection of CS and econ

[WhiteDragon]

Here's a proof that detecting "toxic assets" is impossible (or at least NP)

Psychonomics

[woolio]

But economics is not a zero-sum game. I give you $150 and you give me an hour of labor. We've both benefited by the trade.

In all but the world's oldest profession, I'm inclined to disagree.

Here's one:

Person A runs a tavern. Person B (after a few beers) drives his car into that of Person A. Person B pays $150 to Person C to fix the scratches on Person A's car. Person C uses his $150 income at Person A's tavern.

Who profited by the exchange of $150? Are all three people better off?

Here's another: Person B drinks at Person A's bar. Person A runs a farm to grow barley. The farm uses water that slightly increases (~1%) water prices for 100k other persons. Are person A and B both economically better off for their trade? (Yes). Are persons A,B, and the 100k others all better off? (They might or might not all agree, but what if their generation's children do not!). Even more interestingly, the 1% cost will manifest as slight increases in other goods. Eventually someone will be holding the hot potato...

In examples with larger populations, the zero-sum exists but is more blurry. Fundamentally, most economists seem to think that the optimal solution for a 2-person economy is optimal for an n-person economy. Well, logical induction doesn't work way! (The implication from "n" to "n+1" doesn't exist!) It is well known in Mathematics that optimizing a function with multiple variables not the same as finding the set of variables where each individually optimize the function.

I'm not saying that there isn't value to distributing tasks across people that are specialized at them. I just don't buy the argument that economics is never a zero-sum game. I think in all but the most ideal circumstances, it is indeed zero-sum game. Often the case, the true cost is hidden in the form of time. If the costs do not happen at the same time as the benefits, people only see the benefits for a long time and then lament the cost later.

I realize I may sound like the reincarnation of Marx. Well, I don't like Communism either.

Re:Didn't they already prove...

[justinlee37]

Just because it can't make perfect predictions all of the time doesn't mean that it is useless. You're right, people aren't rational and random chance plays into most things. If you ever take an Econometrics class, you'll learn that predictive Econometric equations always include a random error variable.

Furthermore, in your example, I don't think that showing that people don't take the most selfish path is a "useless" finding. What they did was generate data about how people usually behave. Concepts from Psychology such as empathy and the norm of reciprocity may help to explain this behavior (and the data is capable of reinforcing these theories). The data can be used to predict how people will behave in the future. THAT is invaluable.

Despite what you say, game theory is very intriguing and Econometrics is incredibly useful. You just have to be aware of the limitations, and know how to use the tools in your toolbox effectively.