From yesterday’s NYT, here. This year’s Nobel laureate in economics is of the firm opinion that the field of neuroeconomics is going to become increasingly important because humans do not behave rationally. I agree with the basic point but I would add two things: first, at least in the US (probably less so in China) fMRI studies are often statistically underpowered. I think this is generally a challenge for all of behavioral economics. Second, in real economic ecosystems (with millions of human agents) complexity plays an important role in emergents (such as market prices for goods). To capture these complex adaptive systems we really need the tools of computational social science and especially the tools of agent-based models. These models have the strength of accommodating millions of agents (in silico) and potentially provide insights and predictive power to the above types of emergents.
From Andrew Sullivan’s blog here. Seems like the sort of assertion that could be tested out using agent-based models of cities. Any takers out there?
This time not referring to the University, but rather to our own homegrown and widely used java-based simulator for agent based modeling. You can find it here. The link has great simulation demonstrations that you can watch in your browser.
What does MASON stand for as an acronym?
From the web site:
” Multi-Agent Simulator Of Neighborhoods… or Networks… or something… “
Here’s some serious agent-based modeling (or what seems like it):
According to IEEE Spectrum Online, the researchers have re-created the lives of 100 million Americans based on census data. Within six months, they hope to simulate the day-to-day lives of the country’s 300 million residents. Each fake person is given an age, education level, and job, which reflect the demographics of the communities they populate.
Using Navteg, a digital-mapping company, information is pulled from directories and databases to determine where each person may work, shop, or attend school.
The simulation may help to answer a few nagging questions. How do fads and trends grow? How does traffic flow? One major component of the project so far is determining how contagious diseases, like flu, spread, IEEE Spectrum reports.
Here’s a really interesting Op-Ed piece in today’s NY Times that I think is a perfect follow up to Rob’s blogpost.
Sadly, the academic economics profession remains reluctant to embrace this new computational approach (and stubbornly wedded to the traditional equilibrium picture). This seems decidedly peculiar given that every other branch of science from physics to molecular biology has embraced computational modeling as an invaluable tool for gaining insight into complex systems of many interacting parts, where the links between causes and effect can be tortuously convoluted.
Something of the attitude of economic traditionalists spilled out a number of years ago at a conference where economists and physicists met to discuss new approaches to economics. As one physicist who was there tells me, a prominent economist objected that the use of computational models amounted to “cheating” or “peeping behind the curtain,” and that respectable economics, by contrast, had to be pursued through the proof of infallible mathematical theorems.
If we’re really going to avoid crises, we’re going to need something more imaginative, starting with a more open-minded attitude to how science can help us understand how markets really work. Done properly, computer simulation represents a kind of “telescope for the mind,” multiplying human powers of analysis and insight just as a telescope does our powers of vision. With simulations, we can discover relationships that the unaided human mind, or even the human mind aided with the best mathematical analysis, would never grasp.