How to Think Like an Economist

Welcome to Economics 101. Please check your politics at the door.

The best piece of advice I can give anyone who is studying economics for the first time is this: leave your politics at the door. It's hard, I know, because economics is a subject that can have a very personal impact on all of us. When biology works against you, you get sick. It's sad, of course, but you can't exactly go and blame nature for doing its thing. When math works against you, you just need to study harder or get help from someone who has more training. When literature works against you, you just find something better to read. But when economics works against you, you're out of a job, you can't pay your mortgage, and -- here's the kicker -- it's probably because someone else did something that, intentionally or unintentionally, has seriously screwed you over.

Peter Norvig's Economic Simulator

Let's build an economy!

I've wanted to do this blog for a while, but I had no idea where to begin.  So I want to thank Peter Norvig for giving me the entry point I was looking for.

Peter Norvig is an artificial intelligence super guru, and a director of research at Google.  He's a very bright guy. Last week he posted an entry on his blog about how to program an economic simulator in Python. This is something I've wanted to do for quite some time, so I was very interested to see how he put it together.  I would recommend you at least skim through his blog post before reading on, if you're interested in understanding how the simulation works.  In his words:

This is a simulation of an economic marketplace in which there is a population of actors, each of which has a level of wealth (a single number) that changes over time. On each time step two agents (chosen by an interaction rule) interact with each other and exchange wealth (according to a transaction rule). The idea is to understand the evolution of the population's wealth over time.

The simulator has four components.  There's a population of people with randomly distributed wealth. There's an interaction model that matches people in the population to trade with each other.  There's a transaction model that determines who gets what when they trade.  And there's a simulation model that ties it all together by creating a population, randomly choosing which people interact, executing their transactions, and reporting on the simulation results.  (In this case, the results are measurements of how the wealth is distributed among the members of the population.)

Why call it "Econometheus"?

Why the funny name?

First things first.  What's with the ridiculous name?  I'm glad you asked, observant reader, because that's probably the best way to introduce what this blog is about.  In Greek mythology, Prometheus and his brother Epimetheus were Titans who were given the responsibility of creating humans and animals to populate the earth.  While Prometheus was teaching the humans things like how to do math and write poetry, Epimetheus was giving all the cool gifts, like fangs and claws and wings and venom, to the animals.  When Prometheus finally was done with our lessons, there were no good physical traits left to give us.  Not wanting to see his beloved humans devoured by lions and tigers and bears, he decided to steal Fire from the gods and give it to us.  I'd love to go more in depth, but if I start talking about mythology here I'll probably never stop, so we'll leave it at that.

Econometheus will be a blog about artificial intelligence and economics; specifically, how to use economic models to design methods useful for artificial intelligence.  Similar to Prometheus teaching humans about reason and culture, it's about my efforts to give computers the gift of thinking according to utility-maximizing behavior.