Enchantment Grows With Distance (But That’s the Point)

Yesterday, I had the pleasure of finishing Desrosières’ The Politics of Large Numbers: A History of Statistical Reasoning. I say the pleasure of finishing, because the book is a bit of a slog but it picks up nicely in the last couple chapters. The first part of the book is an often jumpy history of certain ideas and debates in statistics (both the administrative data collection procedures known as statistics in the 18th and 19th century, and the mathematical statistics and probability we now associate with that word), jump-y because the examples come from four or five countries and 2 or 3 centuries. But the payoff is in excellent quotes like this one, describing the purpose of statistics and, I will argue, enchantment growing with distance*:

“The aim of statistical work is to make a priori separate things hold together, thus lending reality and consistency to larger, more complex objects. Purged of the unlimited abundance of the tangible manifestations of individual cases, these objects can then find a place in other constructs, be they cognitive or political.” (236)

Desrosières is arguing here that the job of statistics is to make certain kinds of black boxes by purging cases of their particularities and making portable objects (usually numbers) that hold together previously disparate information. This process cannot work if it is constantly interrogated, if enchantment does not grow with distance. The national income can’t be an input into the mathematical Keynesianism of the post-WWII era if national income statistics aren’t portable and black boxed. If they are continually interrogated, if we must always ask how they were made and what they mean, they cannot serve as input to other processes. In other words, enchantment is a feature, not a bug. That doesn’t imply we can’t fight it when the results are ones we don’t like, but rather that we should not expect to make every user of statistical data a completely reflexive sociologist – nothing could hold together if we spent all of our time critiquing the underlying concepts and methodologies. So, pick your battles (unless you really think all of these constructions are less than worthless).

* Enchantment grows with distance is a phrase that often gets invoked to describe how the users of statistical data and datasets who were not involved in their creation often have inflated views of the reliability and meaningfulness of the data as compared to those who helped create the data.

Reality is… (Econometrics Edition)

A quotable lesson from my first-year graduate econometrics course:

“Reality is the data-generating process.”

We social scientists have amusing ontological priorities.

Efficiency vs. Robustness in the Private and Public Sectors

Way back, many years ago in college, I attended a local nerd event Penguicon, a sci-fi/Linux/gaming mash-up convention*. By far the most interesting speaker was the science guest of honor, Jack Cohen, a British complex systems Biologist who has done a lot of consulting work with science-fiction and fantasy authors (e.g. The Science of Discworld). In one of Cohen’s talks, he recalled a time when a journalist called him and asked him to explain two seemingly unrelated events: an outbreak of infections from bad milk and a recent railway collision. He was puzzled at first but then responded, “Efficiency is the opposite of robustness.” This idea is probably not so novel to most people reading this blog, but to young me it sounded very profound, and I often think back to Cohen’s phrasing of the trade-offs between the two.

For example, this morning I read two articles from the Economist about the financial crisis and its fall-out: “All you need is cash” and “To spend or not to spend”. The first story reanalyzes pre-crisis debates on the importance of leverage, and critiques of overly-thrifty corporations which kept large reserves of cash on hand:

Ever since the 1980s the fashion had been to make companies as lean as possible, outsourcing all but your core competencies, expanding your just-in-time supplier system around the globe, loading up with debt to “leverage” your balance-sheet. Old-style defensive conglomerates, such as Arnold Weinstock’s General Electric Company, were dismantled. Companies that hoarded cash—even ones as good as Toyota and Microsoft—were viewed with suspicion.

The financial crisis, and particularly the sudden disappearance of liquidity in the commercial paper market, led to a lot of rethinking about the importance of cash-on-hand. In general though, the problem has the form of an efficiency vs. robustness trade-off. High leverage ratios make sense in normal times, and until something goes wrong will produce higher returns. But that seemingly efficient distribution of resources is not robust to shocks of any size. And when everyone is similarly leveraged, small shocks become large ones.

At the other end of the economy, “To spend or not to spend” argues that the US federal government needs to start spending like mad. Wouldn’t it be nice if the government had some sort of reserve of money, saved up from good times? But in good times, saving was seen as inefficient – it would have dampened growth. Consumers and the government spent, spent, spent. Now we think if only we’d tamped down that rampant spending, and not propped up the markets with a housing bubble to replace a dot.com bubble, this crisis could have been averted. Classic Keynesianism sounds pretty good right now, even if it sounds like a fire alarm.

Ok, that didn’t tie together quite as neatly as I might have liked. So it goes. Here’s the provocative close though: Following Cohen, does an “efficient market hypothesis” have a “fragile market corollary”?

* King Jeremy, I have my eyes on your crown. Give me a decade or two, and tenure, and I’ll find a way to top your spectacularly successful academic infocom masterpiece.

Can a sociology major make 6 figures? (Or, hello Google searchers!)

I don’t know about you, but I am always fascinated by the search terms that lead websurfers to my blog. For example, my post about Freakonomics gets a lot of hits (by my 50 hits on a decent day metric) from the search term “Freakonomics critique”, as that’s in the title of the post. Similarly, my indexed remix of Polanyi gets some traffic from “Polanyi embeddedness”. But sometimes surfers find my site through search terms that are really just sad… like “Can a sociology major make 6 figures?” (which somehow hits my blog on the second link. even before I post this).

So, in case this comes up again: Sure, it’s possible. Michelle Obama seems to have done well for herself, what with Harvard law and all. And Ronald Reagan never got a higher degree than his Bachelor’s in Economics and Sociology, and he made a fair bit of dough. But, I wouldn’t really recommend Sociology if you are trying to make 6 figures.

That is, unless the 6 figures you want to make are regression coefficients, descriptive statistics, 2×2 tables, Venn diagrams, path diagrams, and scatterplots. Then Sociology just might be the right place for you!

Is Economic Sociology Institutional Economics Mark II?

So, last weekend I had the distinct pleasure of reading Yuval Yonay’s (1998) The Struggle Over the Soul of Economics: Institutional and Neoclassical Economists in America between the Wars. Yonay attempts an Actor-Network/Latourian history of the debates within economics in the U.S. around 1920-1940. The book is a fun read, and I think does an excellent job of portraying the positions taken by the neoclassicists and institutionalists respectively. One of Yonay’s central goals is an intervention in the historiography of economics to argue that institutionalism was not a minor dead-end that never had much importance. Yonay shows that institutionalism was a vibrant research program/paradigm/whatnot during this period and that institutionalism eventually lost out not to the neoclassicists but rather to the mathematical economists that arose in the immediate post-War period. While the mathematical economists claimed the neoclassicists more strongly than the institutionalists, Yonay argues fairly convincingly that the post-war mathematical econ/Keynesian consensus represents quite a break from both camps.

Accounts! Hot off the virtual presses!

So, the Fall 2008 issue of the Economic Sociology Section Newsletter, Accounts was just released today. You can get it here, at the Michigan Economic Sociology website. A team of Michigan graduate students are editing Accounts this year, including myself, so I’m pretty excited to actually get the thing out the door.

This issue contains an interview with Donald MacKenzie, science studies professor and performativity expert, no the current financial crisis, as well as an excerpt from a forthcoming book by Jerry Davis entitled Managed by the Markets: How Finance Reshaped America.

Let me know what you think!

Macro and Micro Economic Counterfactuals and Performativity

I am really interested in the idea of counterfactuals and their place in social scientific knowledge. Mapping out the space of possibilities* plays an important, explicit role in many kinds of modeling, and an implicit role in many historical accounts (such as an excellent history of economics by Yuval Yonay that I finished today and will likely write up for here soon). Today I started thinking about the connection between counterfactuals and the performativity of economics. Two examples.

In Harrison White’s famous and semi-whacky model of markets (e.g. White 1981), producers make decisions based on the observed production schedules of other firms and their own known cost functions. Producers do not, in any sense, rely on models of demand curves. Mark Mizruchi explains this modeling decision as a recognition that demand curves are “completely counterfactual” and thus not a solid basis for decision-making. A producer cannot know what the demand for a product would look like given a change in quality, cost, etc. So White’s producers don’t do that. They make decisions on observables.

I accept that demand curves are counterfacturals, but perhaps not all counterfactuals are unobservable. Perhaps the technologies (concepts, ideas, formulae, data, etc.) of modern economics allow producers to “see” demand in a curvy fashion?

Here’s a more concrete example. Right now, congress is considering another fiscal stimulus package (Brad DeLong’s “Keynesian fire alarm“). Today, Paul Krugman wrote up a justification for such a move and a suggestion for how to calculate its magnitude. Some quotes:

Wait, there’s more. Ben Bernanke can’t push on a string – but he can pull, if necessary. Suppose fiscal policy ends up being too expansionary, so that real GDP “wants” to come in 2 percent above potential. In that case the Fed can tighten a bit, and no harm is done. But if fiscal policy is too contractionary, and real GDP comes in below potential, there’s no potential monetary offset. That means that fiscal policy should take risks in the direction of boldness.

Krugman explicitly models a counterfactual – what real GDP “wants” to be, but can’t attain due to unemployment above the “natural rate”. Okun’s law tells Krugman that “every excess point of unemployment above 5 means a 2% output gap.” So, econometric data + economic theory = visible counterfactual on which to make policy. GDP “should” be a few percent higher than it will be next year, so government should make up the gap – and if it overshoots, the Fed can fix things by raising interest rates.

So, is this an example of performativity? Will economics have performed the “natural rate of unemployment” and the idea that GDP “wants” to be higher than it will be if, using justifications along Krugman’s lines, a large fiscal stimulus is passed that lowers unemployment?

*A term suggested to me by new UoM Prof. Elizabeth Bruch when we were talking about performativity, and the general problem of models that create things.

Truer Words Have Ever Been Spoken

Name the economist from the quote:
“Undoubtedly, our age will be credited with having seen the end of the self-regulating market.”

Post-Structuralist, Steampunk SAT Question

Market :: Economy as:

A) Phlogiston:: Oxygen

B) Aphrodite :: Venus

C) Dionysian :: Id

D) Quarks :: Atoms

E) Ether :: Wave-Particle Duality

List your answer (or, even better, your alternate answer choices) in the comments!

Notes from ICOS – Espeland “A Different Kind of Quantitative Sociology”

At the request of Ann Arbor’s OrgTheory-ist in residence, I’m going to write up last Friday’s excellent ICOS lecture by Wendy Espeland. ICOS has a hilarious lecture series riddled with traditions, and they bring excellent speakers. For example, before Wendy spoke, Jerry Davis (business school prof and ICOS coordinator) introduced Greta Krippner (sociology prof and guest curator) who introduced Natalie Cotton (business and soc PhD student) who finally introduced Espeland. ICOS also has its own espresso machine, and delicious cookies. I highly recommend it. Onto the talk itself.