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Many thoughts, all from podcasts

March 12, 2011

I’ve been catching up on some of NPR’s Planet Money podcasts as I get my weekend going. I forgot I enjoyed these so much. In one of my favorite papers of all time, Hal Varian (who wrote one of the foundational <a href="http://www.amazon.com/Microeconomic-Analysis-Third-Hal-Varian/dp/0393957357"micro textbooks that I’m told the “previous generation” of economists worked through) wrote that “you should look for your [research] ideas outside the academic journals—in newspapers, in magazines, in conversations, and in TV and radio programs.” These planet money podcasts reminded me why.

No time now for exposition on that, but I do want to quickly list the podcasts with “seeds of ideas:”

  • Discipline vs forgiveness in borrowing, and what that means for growth.
    • I haven’t finished listening to this yet. One quick stab — perhaps the “weight of results” of making very complex calculations should be laid on those most able to make those calculations. Super-quick version: they seem to say, “Spain lays the consequences of mis-understanding a complex calculation of a person/business’ potential insolvency primarily on the person, vs in the US, where a lot of that is laid on the lender.” Quick-reaction is: well, in any transaction, both bear responsibility. With these laws, either version, that responsibility is necessarily laid more on one party vs the other; policy-makers must simply choose which party bears the greater weight. We want to encourage the best calculations the be made, so perhaps they should lay that responsibility on those most able to actually make the calculation — not because it’s fair or not fair or whatever, but because that makes the system self-balancing and better-working. Thus in the US, the lenders, who ostensibly have it as their job to know creditworthiness of a business/person/etc, — because that’s their job, that’s what they do — perhaps they should bear the weight of the complex calculation of creditworthiness. And here “bearing the weight” means they are left holding the bag if it doesn’t work — they bear the risk. “And thus that system encourages more growth,” since you have people specialized in allocating resources actually allocating the resources. People may say, “well obviously that didn’t work in the US with Financial Crisis,” but that ignores that I think (big “I think” here) that Spain actually has it much, much worse, debt- and production-wise, and has for many years. On an unrelated note, when I started this podcast, I thought of the Rocky quote, “…I figured if I break the guy’s thumb, he gets laid off, right? Then he can’t make payments…” …never seemed like a good bookie strategy.
  • Inside the Great Depression
    • Great story. I was struck by the observation, halfway through, that fruit was going to rot on trees while kids in cities starved, because no one had money to spend. I listened to this right after the “Gold Standard, Part II” podcast, and it fit so well. Interesting that the fellow making that observation in this podcast was still strongly in favor of the gold standard, even as he recognized how it was affecting the Depression almost exactly how the “Gold Standard, Part II” folks talked about it happening.
  • Production vs rentier states, regarding Libya.
    • They talk, at the end about the difference between Haiti (not) recovering after revolution a while back, vs the potential for Libya to recover if Gaddafi is outed. One asks — what was happening in Haiti, after that governmental overturn a while back? One wants to dive into the details of what makes a modern city of any particular size run. One wants to try to trace out the details of what makes/goes into any particular persons job funcitoning. Ask this in some quantitative way — how many people go into producing the goods I use in my daily life? What is the “production chain” for an average good or service in my city? …certainly a lot of this is unknowable with current data. Network structures would figure into this, perhaps. More thoughts later.
    • Q2 is, could one model Norway’s approach?
  • The gold standard, Part 1 and Part 2 (there are more but I haven’t heard the rest)
    • Many thought-provoking conversations here. I’m tempted to go pick up my copy of The Great Contraction again. The thing that catches my attention here is that these arguments discussed are all essentially verbal models. One wonders what minimal requirements on agents and environments would be needed to support the verbal models laid out here. Part of me suspects that there are inevitably “things left unconnected” in the verbal models — that they aren’t a closed system. This, of course, is one of the reasons formal mathematical and computational models are built: thinking through the math or the computation forces you to face the “loose ends” of your system. (Of course the models must be built well…)

      This also reminds me that I think there may still be a lot of work to be done in building and exploring any sort of non-strictly-optimizing agents, as I suspect the fellow advocating the return to the gold standard might prefer. This is a future post.

I need to figure out how to write less, I think. This post didn’t turn out to be “quick thoughts,” whoops. And I still need a haircut today!

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Posts I would like to write

March 12, 2011

Hello all. I’ve been trying to decide how to handle the fact that I keep wanting to “link forward” to “posts I will someday write.” I have posts in my head, but not enough time to write them — what to do?

My quick solution is to just list them, here, and link to this page — and — link back to the page where I reference my non-existent posts 🙂 Thus hopefully not forgetting, in the future, where those links are. We will see how this work.

Future links:

  • “Being realistic” and “understanding your model”
    • I don’t think there is a tradeoff here — just more work. In modeling we face a dual problem: we are trying to understand true behavior of actual people, and we must also understand the artificial behavior of our artificial representations of people. Any agent is necessarily artificial. When we use them we must understand how they act in their own right — at least with respect to whatever activity we care about. (If I am modeling home purchases, maybe I don’t care if the person likes action movies or romantic comedies.)

Rational Expectations

March 7, 2011

I’ve found myself in multiple conversations lately about rational expectations. I decided I would add Rational Expectations to my long and growing reading list. I was given this by someone a long time ago, but never read it.

The first chapter already has very interesting tidbits. It mentions rational expectations as a “controversial set of ideas that many economists view as having little policy relevance” (to paraphrase somewhat). Interesting. Perhaps the first edition shows its age there a little? Also, I never knew that Muth developed his idea of rational expectations while collaborating with Herbert Simon, the “father of bounded rationality.” Apparently they were working on the same research model and both wrestling with how to model expectations, which could be a significantly important influencer of system dynamics. There’s an interesting quote by Simon related to the usefulness of something along the lines of rational expectations.

I’ve been going back and forth in my mind about what role rational expectations (RE) might play in agent modeling. I heard a great talk the other day, and the speaker noted that “you always need to remember that the simplest human is smarter than your most intelligent agent.” The best justification I’ve ever encountered for RE addresses this exact point: we can never hope to make an agent as broadly intelligent or clever or communicative as a real human, so instead of accidentally making an economic agent too dumb, and ending up with “model artifacts” from that, RE aims to make the agent as smart as he/she possibly can be, and see what results come from that. I think this is an incredibly good point, one that must be taken very seriously.

Of course, one might argue that some artifacts one might get from making an agent “dumber” than RE might be how the world actually is — that some people are less-then-RE, in some important and significant way. But as someone (whose name slips the mind at the moment) once said, one can get lost in the “wilderness of bounded rationality.” There’s only one way to have rational expectations, but infinite ways to be boundedly rational.

I have is two reactions to this, one immediate, and one that’s been emerging slowly. The immediate reaction is that, whenever a type of bounded rationality is introduced in a particular model, it could be very useful to start a model with full measure of “RE agents*,” and explore how the model dynamics change as the percentage of boundedly rational agents is slowly increased.
(* I’ll note that as soon as non-RE agents are introduced, it may become exceedingly difficult to have truely RE agents, and we may need to substitute something approximating that.)

The second reaction is really almost an offshoot of the footnote to the last paragraph. Perhaps a boundedly rational agent should really just be a small step away from a “truely RE” agent. This could be based on any number of things — largely, I imagine, the structure of the game or trading environment. I’m something of a fan, however, of still using “true”/objective probabilities, at least as a leaping-off point. Thus we would retain the “expectations” part of rational expectations. Perhaps this should be called “bounded rational expectations.”

I need to write an example of this. Perhaps that will be the subject of a future entry.

Hello world!

March 4, 2011

I really enjoy the default title to the first post. I’ll keep it.

It’s about time I start gathering and recording my thoughts and musings on agent-based modeling. I’ve been thinking about these things since my undergraduate days; it’s about time I begin recording them somewhere. No better time than now!

This will be home to a broad range of topics — current models I might be working, methodological questions, ideas I have about the future, thoughts on the current “state of the field,” notes on the tools of the trade, thoughts on academics background, thoughts on professional future, possible applications, possible non-applications — all sorts of things. All here for your enjoyment! And, really, as a place to store my thoughts.

Either way, I hope you enjoy your visit. Drop me a line if you have any thoughts, Qs, etc!