Enthought and Economic Science

A few of us at Enthought (Peter Wang, Robert Kern, and I) traveled to Toronto two weeks ago to attend a very interesting summit of scientists and others connected to finance and economics to discuss whether and how science can provide assistance in understanding economics sufficiently to prevent or at least mitigate economic breakdowns such as the one we’ve just experienced (and are still dealing with). The conference was titled The Economic Crisis and its Implications for the Science of Economics. Some background material for the conference can be read at Edge.org, and at least two blog-posts covering the conference can be read: one by Stephen Hsu and another by Barkley Rosser.

We were invited because Eric Weinstein is a fan of Python and the tools in the Enthought Python Distribution (including NumPy, SciPy, SymPy, MayaVI, and Chaco). Robert Kern produced some very nice visualizations for Eric’s talks in the conference using MayaVi and Chaco which can be seen in Eric Weinstein’s two talks: 30 minutes into the first one and 45 minutes and again 1:30 minutes into the second one (Actually, the second talk was Pia Malaney’s talk and Eric enthusiastically joined her half-way through — I guess being married has its advantages for getting more air time.)

The conference was intellectually stimulating and very enjoyable. I enjoyed all of the conversations I personally had with the participants which ranged from probability theory to cognitive neuroscience to quantum mechanics to computer platforms for agent-based modeling. I encourage you to read and listen in more depth to what the participants had to say in their talks because I won’t be able to provide sufficient summary to the conference. All of the conference talks are online. What isn’t shown in the videos, though, are the break-out discussions that took place between sessions and at meal-time.

In these break-out discussions I enjoyed getting to know all four members of the PartEcon team. Apparently, Mike Brown organized this group after an agent-based model (discussed at the conference by Alexander (Sasha) Outkin) predicted some useful results of changing the tick-size to decimals on the NASDAQ. They have incorporated principles of double-entry book-keeping into their agent-based model. They also stayed after the conference to continue comparing notes with another team from the Perimeter Institute that had written about an agent-based model using a more formal setup (by Samuel Vazquez and Simone Severini).

While there was one early talk on the first day by Richard Alexander that touched on the genetic component of human agents, the impact of having evolutionary biologists present (like him and one of his students, Bret Weinstein) was much larger than their presentation footprint. They provided insightful discussions during several break-out sessions (Peter Wang even commented that in another life he might have become a biologist).

Lee Smolin sent around a very nice summary of the conference and suggested a unifying theme of “path-dependence in economic dynamics.” Eric and Lee were both there to explain how gauge theory provides the tools to solve the problem of changing preferences that has plagued traditional academic economics. Eric did a great job of showing how this manifestly untrue concept of unchanging preferences has at least been put forward by several leading economists. It’s still unclear to me whether or not gauge theory actually provides new results, but it definitely seems like a more useful mathematical toolbox to use and build from.

I was disappointed that amidst all the discussion of the failure of economic modeling there was not at least some discussion about the Mises-Rothbardian ideas of fiat currency and fractional-reserve banking being the primary source of the booms and resulting busts. I wanted to learn from the people there rather than try and debate this one particular theory of economics so I pretty much stayed quiet. One gentleman sitting next to me during the first day asked the panel whether the crises shows the failure of fiat currency and and got a very unsatisfying answer from Nouriel Roubini that simply dismissed the question, but did not really address it.

Given that the economic experts have basically shown repeatedly they don’t know what they are doing, intellectual honesty would seem to me to require listening to all sides of a debate, instead of dismissing a whole theory of economics (such as the Austrian school) primarily because it doesn’t use math as its starting point. Fortunately, there are very good texts that argue against fractional-reserve banking and the role it may actually play in causing economic instability. One of them is “Money, Bank Credit, and Economic Cycles” by Jesus Huerta de Soto.

I really enjoyed the conference because it seemed to combine all of the interests I’ve developed over the years: math, probability theory, neuroscience, economics, and computers. I’ve had a hobbyist interest in Economics ever since graduate school at the Mayo Clinic when I was learning about Linux and Python. I fell in love with open source software but wanted to understand how “giving software away” could work sustainably in a society. It was this question that led to me finally reading Mises and Rothbard and a whole host of other non main-stream economists. I can’t say I’ve figured anything out, but I have very much enjoyed the ride.

I’m also very hopeful in some of the ideas I saw at the conference that may help us inch closer to an understanding of the truth of an economic system (mathematically modeling changing preferences, using agent-based models, and even the idea of local currencies that was discussed among some at the conference).

In the more immediate future. It looks like there is some discussion afoot for building a platform for agent-based modeling that I hope Python plays prominently in. There is a real power in using an expressive and dynamic language like Python that allows for rapid development. It is a general-purpose language that scientists and engineers can actually get excited about. In addition, the work of Paul Borrill’s company (Replicus) in creating an agent-based storage solution looks immediately promising. Perhaps Enthought can provide some tools to assist in managing such a system. I’m enthused and anxious to continue to support the improvement of using computers to help solve some of the world’s most challenging problems. There is much more that could be said, but I’m sure this blog (with no photos) is long enough.

7 thoughts on “Enthought and Economic Science

  1. avatarEric Weinstein

    Well, no offense, but you guys are more modest than accurate. First of all, Enthought asked for nothing and came on their own nickel to help out with no financial arrangement whatsoever. That was pretty gutsy in my opinion.
    But, you were really invited because (as mentioned in the opening talk) design is a central ingredient in the success of any potential “Economic Manhattan Project”. As none other than Guido van Russom said when he came to the talk at Stanford


    before the conference, “Enthought is taking scientific computing to places I never thought possible.” That let me know that if I was making a mistake, I was at least making it in very good company.

    The other thing that needs to be said is that because Enthought can visualize scientific results using an agile development, the small team had an intrinsic advantage in being able to understand the science concretely. Truth be told, Robert, Peter, and Travis were invited as developers, but they contributed as first class scientists who just happen to code.

    And on a personal note, Robert Kern stayed up all night tweaking code to get the gauge theory visualization right for the opening talk because the disorganized presenter was tweaking the presentation at 5 am. Robert, youre a monster who deserves better clients. Or, at least paying ones.

    Thank you all for helping to create an exceptional conference,


  2. avatarKingofthePaupers

    “It was this question that led to me finally reading Mises and Rothbard and a whole hosts of other non main-stream economists. I cant say Ive figured anything out, but I have very much enjoyed the ride.”

    Jct: None of them explain the effect of demanding interest on the poker chips issued. 100% reserve banking is silly when LETS time-based community currencies and poker chips work on 0% reserves. If there is new collateral, the cashier issues new chips and the number of old chips saved (100% reserves) has nothing to do with the process.
    See my posts on money creation at my http://youtube.com/kingofthepaupers channel.

  3. avatarjosef

    This is an interesting discussion that I didn’t know about and it sounds like fun.

    However, for our understanding of an economy, the analogy from physics, biology and other “hard” sciences is missing the main point. Human decision makers use information, and make decisions based on the anticipation of future developments and consequences.

    Any theory or model that doesn’t take beliefs or expectations, and information transmission between economic agents into account, will capture only a small part of the relevant story, and will remain marginal in our economic understanding. The rational expectation revolution is 30 years old and is here to stay, because it provides a powerful concept of belief and expectation formation that is unique to humans.
    Equilibrium concepts help us think about the coordination of agents based on prices and global information. Evolutionary economics and other bottom-up approaches can help us understand micro behavior, but I don’t think they can capture the informational importance of financial markets.

    I still remember when chaos theory become “fashionable”, it helped us understand non-linear dynamics, but I haven’t heard it mentioned in a very, very long time. I also remember the Club of Rome.

    “Given that the economic experts have basically shown repeatedly they dont know what they are doing.”

    We know what we are doing, but we don’t have perfect information and a model is just a model and not a one-to-one map.


  4. Pingback: Economic Manhattan Project « MoreNotesToSelf

  5. Pingback: Economic Manhattan Project « MoreNotesToSelf

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