If you want to learn a methodology, there may be an email list you should be on. The two big network analysis packages in R Statnet and igraph each have one (sign up: Statnet, igraph, Mixed Models). If you join them, you can ask questions when you get stuck. But you may end up learning even more from other people’s questions. Jorge M Rocha stimulated Carter Butts to write a mini-essay on exponential random graph models which I received permission to repost. Dave Hunter also adds some thoughts at the bottom.

## Krugman on Useful Macroeconomic Models

May 1, 2011Brad Delong reposts an essay by Paul Krugman, which I believe was written before the crisis. In this short piece, Krugman attempts to summarize useful macroeconomic models and laments that they have fallen out of fashion.

If you are interested primarily in modeling outside of economics, this Krugman is more useful, but both are definitely worthwhile.

## Hirschman on Rational Choice Theory

January 26, 2010Dan Hirschman, grad student at the University of Michigan, has a great post on rational choice theory. It is framed as a critique, but I consider it wholly compatible with my defense of RCT. Human behavior is complex and different aspects of it will be best understood with different theories/models/levels of analysis. See some of my previous posts on modeling here.

## Sethi on Insights from Ecology

December 8, 2009Economist Rajiv Sethi has a great blog. In this post, Sethi, and Thoma, whom he quotes, seem to acknowledge that the financial crisis should lead them to consider new ideas for economic models. Later on in the post, Sethi points out that behavioral economics has mined psychology for insights, but that economists would do well to look beyond the level of the individual:

If one is to look beyond economics for metaphors and models, why stop at psychology? For financial market behavior, a more appropriate discipline might be *evolutionary ecology*. This is not a new idea. Consider, for instance, this recent article in *Nature*. Or take a look at the chapter on “The Ecology of Markets” in Victor Niederhoffer’s extraordinary memoir. Or study Hyman Minsky’s financial instability hypothesis (discussed at some length in an earlier post), which depends explicitly on the assumption that aggressive financial practices are rapidly replicated during periods of stable growth, eventually becoming so widespread that systemic stability is put at risk. To my mind this reflects an ecological rather than psychological understanding of financial market behavior.

Reading people like Sethi, I’m confident economics will come around. Sociologists have never overemphasized rational actors, but we too can learn from approaches in other disciplines like ecology.

## Does P=NP?

December 5, 2009If P=NP, then the world would be a profoundly different place than we usually assume it to be. There would be no special value in “creative leaps,” no fundamental gap between solving a problem and recognizing the solution once it’s found. Everyone who could appreciate a symphony would be Mozart; everyone who could follow a step-by-step argument would be Gauss; everyone who could recognize a good investment strategy would be Warren Buffett. It’s possible to put the point in Darwinian terms: if this is the sort of universe we inhabited, why wouldn’t we already have evolved to take advantage of it? – Scott Aaronson (reason #9)

When you have some free time, watch this amazing lecture by Avi Wigderson about one of the great open problems in all of mathematics.

## Mistaking Beauty for Truth

November 13, 2009Peter Klein agrees with Paul Krugman that economists have mistaken beauty for truth, but disagrees that it has anything to do with the financial crisis so he won’t be signing the Hodgson petition.

Also at the Organizations and Markets blog, Nicolai Foss discusses a special journal issue entitled “Economic Models as Credible Worlds or as Isolating Tools?”

Speaking of models and truth and beauty, I found Murray Gell-Mann’s TED Talk fascinating. He argues that in physics, a beautiful theory is more likely to be true. This makes me a little nervous. I would be especially worried about using this heuristic in the social sciences because the objects we are studying are complex, and have so much meaning to us that our aesthetic sense is more likely to attach to theories for reasons other than truth. Truth may be beautiful, but so are our cognitive biases and ideologies.

## Forced to Defend Rational Choice Theory

November 10, 2009I’m finally responding to Eli Thorkelson, who asked for my comments on an article by feminist economist Julie Nelson. The article is a critique of rational choice theory (RCT) and I think it has some omissions and misleading claims.

I regularly come across particular instances of rational choice theorizing that I dislike, but non-economists, including sociologists, often dismiss rational choice theory without understanding it, so when the topic comes up among non-economists, I almost inevitably find myself defending it. My claim is that rational choice theory, broadly construed, is an important, though certainly not the only, useful framework for understanding human behavior. This should be considered an utterly boring claim. What is interesting is how any social scientist could deny it… Read the rest of this entry »

## Performativity and Models (barely scratching the surface)

November 1, 2009Andrei Boutyline mentions something important in the comments to the Krugman on Modeling post.

“…another line of criticism of formal models should be mentioned too: the performativity thesis. I am not sure I can do it justice, but as far as I understand the performativity thesis, it claims that, if powerful enough actors adopt certain simplifying models of understanding the world, the modeled actors will modify their behavior to better fit the model. The clearest example of thesis I’ve encountered is with the introduction of rankings of law schools (here, I may be wrecking an argument of Wendy Espland’s). The rankings intended to capture the criteria of law schools that the schools valued, but had to make simplifying assumptions to focus on common quantifiable elements. This had the effect of creating a strong incentive for schools to focus on specifically those areas–eventually at the cost of the unquantified ones. So, the introduction of simplifying (in this case, not into policy but into incentive structures) had the effect of transforming the world. I think this may be a better depiction of what Krugman’s “humanists” actually fear about these models.

The concept of performativity is a can of worms, but it needed to be brought up, even if I can’t say everything that needs to be said about it in one blog post. There is much to like about Espland’s article, academic rankings are fine example of how something “intended” to describe the world, can change it. Interestingly, widespread knowledge or use of a mathematical model, or an individual’s overconfidence in a model, can make the model more accurate, or make it less accurate, or both in different ways depending on the context. But all this is true of ideas that are less formal than mathematical models. In fact, academic rankings are not a mathematical model in the sense that Krugman or I am talking about. Perhaps people using mathematical or statistical models are more prone to overconfidence, but I’m not sure…

A discussion of this topic with economists requires mention of Keynesian beauty contests, and the Lucas Critique. The former is used to help explain bubbles. The latter is used to argue that macroeconomic models require microfoundations, in other words, more (not less) formal mathematical modeling, to complement and combine with statistical analysis.

Of course, sociologists have been thinking along these lines long before performativity became a popular buzzword. As W.I. Thomas said, “If men define situations as real, they are real in their consequences.”

## Paul Krugman on Metaphors and Models

October 27, 2009Paul Krugman has spent a lot of time recently criticizing economists associated with the Chicago School because he believes they are making horrible public policy recommendations and, importantly, misusing mathematical models, e.g. the oft criticized, dynamic stochastic general equilibrium models. But Krugman has written a lot that is equally interesting, and less political.

Today I’d like to draw your attention to an article he wrote in 1994 entitled, The Fall and Rise of Development Economics. Its absolutely worth reading the whole thing, but I’ll summarize and excerpt a huge chunk from the middle of it for those of you who are really pressed for time. Krugman tells us that rigorous modeling is very important for economics, but he also argues that the new (1950s and 1960s) emphasis on modeling led people to forget or ignore things people knew about development economics for years, until people figured out how to model them.

After the break I’m pasting the middle section of the essay, essential reading on metaphors and models: Read the rest of this entry »

## Mathematical models: why and what for?

October 21, 2009

An anthropologist friend of mine, Eli Thorkelson, recently asked for my comments on an article by feminist economist Julie Nelson. The article is a critique of rational choice theory (RCT) and I think it has some glaring omissions and misleading claims, but before I get to them I want to briefly offer the positive case for mathematical models, of which rational choice models are a subset.*

Markets and other social phenomena are complex. We’re never going to have a theory that perfectly describes everything we might want to know about them. Modeling is one way we can get some insight. In a model we make some simplifying assumptions and then work out their implications. Then, and this is key, we do empirical work; we analyze data to see how well our model captures various aspects of the phenomena we are interested in. Ideally a model will make predictions that are novel, in the sense that the researcher would not have made them before studying the model, and in the sense that they distinguish one model from another in a way that can be tested rigorously.

What about those simplifying assumptions? If they turn out to be false, doesn’t that mean the model is junk? Read the rest of this entry »