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Notes Eric Blair January 15, 2009

D EAR R EADER ,

Many, many people have pointed out that the average person’s attention span has been getting shorter with time. They recommend that you should keep your message short and punchy. Bullet points help; try not to have more than about four bullet points to a slide. To those people, I reply: bite me. You, my intended audience, are educated: you know how to skim for useful information, if a topic interests you then you want it discussed in detail, and you read English at above a ninth-grade level (or are a non-native speaker who wants not-watered-down prose). And so, I offer you too much information. As I write this, these notes are about 400 pages, and thus well beyond my own attention span and probably yours. Print it out, set it on the ledge in the bathroom, and read whatever parts of it interest you. If you skim, skip entire chapters, or just use your copy for note paper, I won’t know. The first essay, on page

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C ONTENTS

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CONTENTS

1 W RITING , THINKTANKING , AND THEORIZING

1.1

On writing 28 December 2007

Today’s artificial division of the world into two types: those who are productive because of constraints and those who are productive despite them. As with any ‘two kinds of people in this world’ distinction, it’s artificial, but I’m gonna run with it anyway. [My favorite distinction of this type is from Pink Flamingos: ‘There are two kinds of people in the world: my kind, and assholes.’ That just sums up the worldview of so very many people.]

Igor Stravinsky was decidedly on the side of constraints: My freedom thus consists in moving about within the narrow frame that I have assigned myself for each one of my undertakings. I shall go even further. My freedom will be so much the greater and more meaningful the more narrowly I limit my field of action and the more I surround myself with obstacles. Whatever diminishes constraint diminishes strength. The more constraints one imposes, the more one frees one’s self of the chains that shackle the spirit. [Stravinsky, 1942, p 65] So Mr. Stravinsky works within certain forms, though you won’t find many folks who would call him uncreative. On the other end, you’ve got the joke about how Michelangelo carved David: he started with a block of marble, then chipped away all the parts of the block that don’t look like David. You could argue that the constraints are just a question of degree: Michelangelo still had the constraint of the limited tools and techniques he had on hand, and marble has certain properties that preclude some techniques that would be fine on other slabs. But for the length of this column, I’m standing by my arbitrary distinction. 1

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CHAPTER 1. WRITING, THINKTANKING, AND THEORIZING

E.g., at the extremes, you start to see the differences in people’s reactions. When you list a hundred considerations before anybody can do anything, some people get engaged and start exploring the possibilities and combinations and some get frustrated; when you present a blank piece of paper and say go, some people get flustered and some attack. I used to play a lot of Chess—I won the junior division Chess championship at the Champaign Public Library—but quickly gave up on it, because playing the game stressed me out. When you set up a Chess board, 50% of the board is covered in pieces. The pawns are in front, which means that you have to get them out of the way before you can move the pieces you want to move. That is, Chess is a game of constraints. There are many shelves’ worth of books on Chess openings, and you could read them as a catalog of constraints: if you move here, this constraints loosens, but this other constraint binds more tightly, whereas if you do this the situation is reversed. So I still play Chess at about the level of a skilled fifth grader, and have since moved to playing Go. The full game is played on a 19-by-19 grid, which means that the first player can pick among 361 options, though there are only a hundred or two that are salient. The second player then has 360 choices for the response, and so on until a structure and its constraints emerge out of nothing. I won’t claim to be more than an OK Go player, but I feel better playing it. So I’m coming to a close on my second book. I have about a dozen pages that need a heap of research and rewriting, and then I can count the whole 450pp of it as done. That is, I’m in the endgame, where there is a structure and its attendant constraints—that I built for myself—and I have to work within them to solve problems. So I came over here and filled a blank screen with text. But that’s why I like writing, be it stupid columns like this, full books, or code. It’s the process of building something out of nothing—creating meaning. Just as a block of marble is not perfectly malleable, a blank screen is not entirely constraint-free, being that you need to fill it with some coherent sort of language (English, HTML, C, some combination thereof). Further, you need to accommodate the sort of constraints other humans impose. A theory of the audience’s mind is absolutely essential for good writing—and good sculpting, good coding, and any other sort of filling of the blank slate. Unless you put “Dear Diary” at the top of the page, you’d better have something that other people find coherent and useful. To formalize this, more or less every published work has a query letter attached, explaining who the audience will be for the book/article/whatever, and why the article will interest and serve that audience. When I’m in a bookstore, I often try to picture the query letter that was attached to any given book. “Dear Editor: I would like to propose to you a book entitled Dancing with Cats which will consist

1.2. WHY I BLOG

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Figure 1.1: Creating a blank slate.

of photos of people dancing with their cats. Although the cat photography market is crowded and demand is strong, I could not find a single book in which the cats were dancing.” But anyway, watching things form is fun. My commute passes several construction projects, and I always stop watching the road for a block to see how much more things are taking shape today than they were the last time I passed by. Then they finally finish, and it’s just another condo. OK, The Form says that this is where I’d put a conclusion, which would say something like, ‘In conclusion, I like writing stuff. I like watching things form’. But instead, here’s a picture of a row of Baltimore houses being torn down to build a hospital.

1.2

Why I blog 2 January 2004

[Or: a defense of non-clarity.]

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Here’s1 a rant entitled “Why I fucking hate web logs”. It’s a little confusing because the guy put 4,200 words online on the subject of ‘why I think it’s dumb that people write so much and put it out to a semi-anonymous audience’. Miss AMJ of Richmond, VA gave the author benefit of the doubt and took it as an attempt at irony and/or humor, but I’m inclined to think that our anti-blog author means everything he/she says [the author didn’t give a name, so I’ll herein refer to the person as a female named Stevanna].2 Anyway, it’s always nice to have a foil, so I’m going to write a response in earnest.

Communicating information Here’s Stevanna’s first coherent point: Communication mediums like IRC/chat, email, instant messaging, etc. all [. . . ] directly imitate, by design, communication channels used in the real world, such as telephones, direct in-person conversation, etc. They were designed this way because, over thousands of years, these are the methods of communication that have risen to the top of the usefulness list. People communicate and socialize much more effectively when communication happens in real-time. [. . . ] Weblogs take us away from that. The first time I saw that real-time communication is not really at the top of the usefulness list was my high school calculus class, where the teacher, in lieu of writing her own lessons, would read us sections from the textbook. I could directly compare the process of learning through reading and learning the exact same material through listening, and reading won by a mile [1.6 km]. There was a real problem that my teacher was overcoming by reading the book to us: nobody would bother to read the thing on their own. But outside of that social problem, words on paper win out. Reading is visual, and the majority of the world consists of visual learners; and I can spend as long as I want on the parts I care about or don’t get, instead of allocating time based on what the speaker thinks I should focus on. Academic conferences and presentations are the same thing: many people honestly mean to read the paper, but don’t get around to it; showing up in a public place and seeing the author face-to-faces forces the reader/listener to pay the author attention. But don’t confuse this attempt to overcome laziness as better communication. Academia is very much the sort of community that Stevanna describes, in that most academic papers are read by a small handful of people who understand the issues, 1

http://mama.indstate.edu/users/bones/WhyIHateWebLogs.html A year or so after I wrote this, the author placed his name, Donald Brook, at the top of the page, but I haven’t bothered revising this essay accordingly. 2

1.2. WHY I BLOG

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and there are only a couple of superstars whose papers will break out and become widely read. In that community, the best means of communication has shown itself to be the paper. The self-interested and sort of antisocial part comes not in writing the paper but in presenting the paper face-to-face, forcing people to aurally read your paper instead of getting to it when s/he decides to make time.

Communicating affect All this is in contrast to most face-to-face communication, wherein people don’t really select with whom they hang out based on content, but based on personality, affect, and cuteness. Some people, like Ian Frazier, are fun to read, and it doesn’t matter what they’re talking about. That’s a good definition of the celebrity: a whole lot of people want to spend time with that celebrity because they find their way of being agreeable, and it doesn’t matter whether they’re pontificating on the meaning of life or just reading lines the screenwriter wrote for them. My pals, to me, are like that. Your pals, to you, are like that. Affect-oriented communication does indeed work best in person and in real time. But I think blogs really do have a place in this. Most of my pals are over 4,500 kilometers away, and don’t get free evening minutes until right around my bedtime. When something interesting does happen in my life, I’ll repeat the anecdote to both of my friends ad nauseum, whereas I can’t do that if I’ve already written about it. No, the blog isn’t the ideal medium, but on a practical level, it solves some problems pretty darn well.

Blogs Blogs are a confusing idea because they fulfill both of the above roles on the same page. People chat online, watch movies, and read blogs by models because they want to spend time with a person that it feels good to spend time with, and the content is secondary. Meanwhile, people read academic papers, newspaper editorials, and blogs by programmers because they want to learn something that may be useful, and the personality of the author is secondary. Stevanna doesn’t understand blogs because they serve both purposes, without telling you. They don’t follow the model of a Power Point presentation3 , clearly stating at the top of the page what you’re about to read; they just tell you stuff and it’s your job as a literate human to actively filter the information. One of Stevanna’s complaints may be that the average blog author has the hubris of assuming that there are people who are both interested in what the author 3

http://www.norvig.com/Gettysburg/sld001.htm

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has to say and in the author him/herself. But any person who is reasonably welladjusted will have some friends who care about the person and want to spend time with them; and that well-adjusted person is also no doubt an authority on something, which he or she will be happy to expound upon. Well-adjustedness aside, even I am comfortable writing on this page about my lousy moods, my authoritative pontifications on economic theory, and SQLite, because I know that there’s some number of people who will read what I have to say about all of these topics with interest. I also know that there is no one person who is simultaneously interested in what I have to say about all three of these topics except myself. This is not a contradiction. I don’t know if she means to be doing this, but Stevana is pushing us to a lowest-common-denominator model of communication, where we throw style and fun out the window for the sake of not confusing the readers who aren’t totally paying attention. Yes, bullet-pointed presentations are efficient and have their place, but they’re also not very fun, which is why newspapers still print essays instead of bullet-pointed summaries of essays, and why we don’t send letters to each other in presentation-style format. Affect trickles into informational essays, and information pervades affect-oriented conversation, and the mixing is inefficient, sometimes annoying, and generally more fun and more human. Compare with Stevanna’s essay, itself a fun mix of affect and information, which says that blog authors should include a statement of purpose so the reader knows exactly what to expect.

1.3

Wikieverything 14 June 2006

You all know good ol’ Wikipedia, but there are also Wikibooks. As you browse through the books at that site, you’ll notice two things: they aren’t very complete (most are half an essay at best), and they aren’t very good. I’m not going to talk about the reliability and authority issue which seems to dominate most discussion of wikimedia. Personally, if I’m reading to get a lite intro to a subject of which I’m ignorant, I’ll take Wikipedia as gospel, because it doesn’t matter; if I’m working on an academic topic, then I’m not going to cite an encyclopædia of any sort, but will have my own external sources providing detail. You no doubt have your own sense of what is or is not reliable. Instead, I’m going to talk here about why the deck is stacked against wikibooks and other attempts to apply the open source idea to every field of endeavor.

1.3. WIKIEVERYTHING

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Narrative vs reference Mr. ZF of Nueva York, NY4 tried to get readers of his blog to write comic scripts. Yup, wikicomedy. From the linked article: “Quickly, the script began to get out of hand. Jokes became tediously long. There were arguments over the content of the material, and over who had the authority to approve or delete it, with some writers taking a dominant role and deleting the work of others at will.” The average entry on Wikipedia is between a single line and a few pages long. They have limited narrative depth at best, and generally just cover a simple list of facts. Although wikipedia would be thousands of pages if printed out in its entirety, nobody is expected to have edited anything beyond a sliver, and nobody expects it to have any structure beyond alphabetical order.

Figure 1.2: Wikiart from the surrealists Computer code is much like this: a person working on one subpart of a program doesn’t have to know anything about how the other subparts work. To write a translator, Jane can work on text parsing, Joe can work on a set of dictionaries, and 4

http://www.nytimes.com/2006/06/18/fashion/sundaystyles/ 18ze.html?ex=1308283200&en=4ea006130a1baabe&ei=5090&partner= rssuserland&emc=rss

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Jess can work on the clicky interface, and all can work with little regard to what the other parties are doing. Narrative works don’t have such wonderful compartmentalization. Sure, there are chapters, but if the chapters don’t tightly come together, we won’t like the darn story much. You ever make an Exquisite Corpse? You fold a paper in thirds, and draw a head, and then refold so the head isn’t visible and hand the paper to a pal who draws the torso, and then your pal hides the torso and another pal draws the waist and the legs. Then you unfold it all and laugh about how delightful such a disjointed figure could be. If you were lucky enough to be one of the founders of the Surrealist movement, then your drawing will wind up on the wall of the Art Institute of Chicago (see figure). But for the rest of us, the game is a fun brainstorm but ain’t a final work. Anthologies are common enough, but we often call them edited volumes and put the editor’s name on the cover to remind the reader that somebody sat down and made sure that the elements somehow cohered. We’re used to other aggregate works directed by one individual: pop songs that have a single producer and movies with one director. I leave to the reader the debate over the quality of songs written via jamming with the band versus songs written by a single composer. OK, there’s your survey of media. Painting, sculpture, movies, music, novels, all involve one or a small number of people directing a final product, which may have been touched by dozens of hands. This is not surprising, and I don’t think anybody seriously expects wikipainting to truly surpass the old method. But textbooks. There seems to be a serious belief that a textbook can be collaboratively written by a committee. This is not a new wikiconcept. In elementary school, we all had many a textbook with no author or editor on the cover, and a list of committee members on the title page. Those textbooks sucked. We often refer to a subject like math or biology as a field. Picture a big expanse of plain, in which you could take any direction. When we go to school, we take courses—carefully guided paths through an open expanse. In other words, a good textbook goes somewhere. It is a narrative. Conversely, some textbooks attempt to survey the entire field at once. Such books are frankly no longer textbooks, but are rightly called references. They have their place, but it ain’t teaching. I can see the appeal for the textbook writers, who want to maximize their market share. They provide as much material as possible in the hopes that the teacher will select a course through the material; some teachers do, covering only chapters 1.3, 3.8, 8.1, and 16.4, while others wind up ploughing through the entire field, column by column. [If you are reading this in book form, I’ve put

1.4. ANATOMY OF AN OP-ED

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effort in to cohering the essays into something of a few narrative threads. Really.]

The wikimethod is good for writing references but bad for writing narratives, so the deck is stacked against wikitextbooks. Again, like the encyclopædic texts, they have a valid and valuable place on the e-bookshelf, but they can’t replace narrative works, just as (conversely) we wouldn’t read a single narrative and claim that we understand the entire field.

Build it 6⇒ they will come Much open source propaganda goes into telling us that if you provide a good and useful basic structure, then diverse people will contribute little elements to it, until you eventually have a complete system. Mr. Eric Raymond has built his entire career on this premise, and I will admit to putting such claims in print myself. Of course, it’s not so simple. The real success stories in open source come from a single good idea, some good coding, and lots of good advertising and selfpromotion. Of course, it also helps if your program is about porn5 . Out of a thousand readers, over 990 won’t fix so much as a typo, and a handful will make little ten-second fixes on a single equation or such. If you’re lucky, maybe a single reader out of every few thousand will contribute the significant time investment to contribute a narrative. Open source provides a new alternative to finding and coordinating coauthors, but it’s not particularly a revolution over existing coauthoring tools (diff, revision control, those cute little change tracking features in word processors). But regardless of the technology, the process of building a narrative has seen no Internet revolution: it’s still about a small number of dedicated people in close communication.

1.4

Anatomy of an op-ed 26 March 2006

The editorial page of your favorite newspaper or magazine is primarily (but not 100%) push-driven. Editors typically don’t solicit editorials; editorials solicit editors. Here’s the timeline: I wrote a 700-word op-ed on Tuesday, and sent it to the think tank’s Communications department, where we have a few people who work full-time on placing op-ed pieces in the newspapers. Ms AM wrote up a polite cover, and emailed it to the editors of a paper or two (I don’t know how many). 5 http://sourceforge.net/search/?type_of_search=soft&words= porn&Search=Search

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The editor of the Wall Street Journal wrote back on Friday, saying that he’ll run the thing as a letter. He cut a few hundred words, sent it back to me and Ms AM for approval, I made two tweaks, the editor tacked on a sensational headline that I did not approve, and it ran in today’s paper. Among the columns pushed upon him or her, what will an editor pick? No surprises: the work will have to be apropos to current news, and will have to be sensational. Simmering-but-not-boiling issues will not run. Moderate opinions will not run. [Or at least, as in the case of my editorial, relatively moderate opinions will be revised to sound as sensational as possible.]

Topical The topical topics only rule produces a random draw somewhat biased toward pressing issues. On any given day, one out of fifty pressing problems breaks, and that one gets to be in the news that day. It ain’t the most efficient method, but I suppose there are worse. The trouble with patents has been building for a decade, but it hasn’t been in the mainstream press until the whole thing about the Blackberry hit. Now, it’s easy for me to get op-eds printed, because disaster is already starting to strike. But wouldn’t it be great if people could have gotten press five years ago about how trouble like the Blackberry case is on its way? But punchiness really does force the press to be reactive instead of proactive. The guys on Capitol Hill want desperately to be proactive. They’re smart folks, and many of them care about good policy. That means that the press, to the extent that it goes after what happened yesterday, is of limited relevance to policymakers. Conversely, to the extent that rule making is about obscure details of legal code, policymakers are assured that general media will not molest them.

Brief The other problem is in writing for tiny attention spans. As I have demonstrated often enough, I could easily write a 7,000 word article on the problem of defining patentable subject matter, and that would still be omitting loads of details. But news media are much more interested in covering lots of topics in minimal detail rather than one topic in depth. And so, I get to cut that article down into a 700word op-ed, from which the editors will delete a few hundred words. Especially with online media, this isn’t necessary, because readers can be brought to the well and drink as much as they choose to. But there’s a 700-word standard out there that everybody seems to stick to anyway.

1.4. ANATOMY OF AN OP-ED

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TV and radio are only worse. They have a hard-and-fast time constraint, meaning that they have no choice but to be on the low-detail end of the spectrum. A five-minute piece can not have much more content than a one-page op-ed, which is not much. I’ve done a few interviews for the nice people at NPR. One went for half an hour, and my final on-air time in the three-minute piece was a single sentence—I didn’t even get a semicolon. Last week, I got a call where I was explaining the situation to a radio reporter, and she said, exasperated, “We’ve been talking for thirteen minutes now and I still don’t have a good ten-second clip.” I wound up getting cut from that one entirely. You don’t need me to tell you this, but details are anathemic to punchiness, and so are going to be lost. If your idea is too complex for a single sentence, it’s evidently not worth the listener’s time.

The odd relationship Nothing in this little column is new to you. You know the generalist media chase ambulances and have no attention span. I’m mostly whining because before I started dealing with media folk on a regular basis, I didn’t think that it would all be so true. Every time I deal with generalist media people, I feel pressure (often explicit) to round off details and say caustic and sensationalist things. When I get off the telephone or hit the send button, I fret about how the journalist at the other end is going to spin and simplify me until I disagree with myself. So, am I going to stop talking to media folks and stop submitting oversimplified op-eds? Of course not. If I want Congress to do anything, or if I want to get grants or continue writing, I need media appearances. It’s how we keep score. For many people, the mental shortcut to answer the question is this person worth talking to? is to reduce it to has this person been published in/by something I’ve heard of? The first question is about whether the person knows the topic in depth, while the second is about whether the person can convince an editor that he or she can summarize information for a general audience. But it is an ingrained heuristic, rooted in observation biases that one could characterize as basic human nature, and I can’t imagine a future where such tendencies magically disappear. So it’s not going to go away. There will always be a need for generalist media, and generalist media will always be better-recognized and more widely read than specialized media, and to maximize audiences they will chase ambulances and oversimplify. Further, people like me have a strong incentive to play along even though we really hate to, because so many people equate widely-read with authoritative.

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1.5


Anti-intellectual 11 April 2006

Pundit is a term from Hindi meaning “wise and learned man”, but it is usually used sarcastically in modern parlance. But, y’know, I don’t feel so sarcastic about it. You can decide the “wise” part for yourself, but having spent a couple of years studying the narrow topic of subject matter expansion in patent law, I am confident describing myself as an authority. It’s been months since I’ve heard a new argument on either side of the debate, and the new facts I’m learning are increasingly fine details. I don’t feel any hubris when I say that nobody is going to blindside me on the tiny, narrow bit of subject that I have chosen for myself. And ya know, most of the arguments that I have presented in various media and to various bigwigs over the last few months are arguments that numerous nonexperts have also made. I often run into people who divide academic results into two categories: (1) things anybody could have come up with after a bit of thought, and (2) things that are too esoteric to be worth anything. Some exceptions are made for chemists and engineers, whose work the commonsense folk have some sense is esoteric but will somehow eventually lead to new toys or a cure for something, but everybody else— the mathematicians who study tensors in R14 , the biologists who study odd tropical flora, and most importantly, the anthropologists and sociologists and economists who study people, whom we all study every day—are wasting their time and our money.

Findings Nor is the righteous ‘my common sense trumps their PhDs’ attitude restricted to the stereotypical hick. The back page of Harper’s magazine, the page most magazines reserve for the humorous finale, is the Findings section, that lists a series of out-of-context study results. From the March 2006 issue: “. . . It was discovered that guppies experience menopause and that toxic waste in the Arctic was turning polar bears into hermaphrodites. . . . A survey found that Americans are becoming less repulsed by the sight of obese people. Scientists launched a study to determine what sorts of clothing make a woman’s bottom look too big. A study found that Americans are more miserable today than they were in 1991, and British researchers discovered that many young girls enjoy mutilating their Barbie dolls.” OK, what are we to make of this? What message is being sent? Mashing together the studies means that the findings do not add up to any real image of the world, even if the page does categorize the findings for some sense of flow. Readers can’t drop these tidbits into cocktail party conversation, because they only have one

1.5. ANTI-INTELLECTUAL

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piece of information and so aren’t armed for even the simplest follow-up. Interested readers can’t learn more, because there are no citations. More importantly, there is no context: we are not given the reason for studying guppy reproductive systems, so we don’t know why a scientist would care to do such a thing. Being the back page, we know that it’s supposed to be humorous, and with everything taken out of context, it can be, the way that so many statements out of context or in a different context are funny. But there’s also the sense of laughing at the scientists. The subject of every sentence (but the passive-voice ones) is a researcher or a study or a survey. If the editors just wanted to list facts, they’d say “Americans are becoming less repulsed. . . ” but instead they waste ink pointing out that “A study found that Americans are becoming less repulsed. . . ”. If there were an American Association Against Science, they would probably reprint the Findings page verbatim. The AAAS would ask, in big red letters, ”Why are we spending money on this?” and the answer to why would not be anywhere to be found. But you know that I spend all day studying obscure features of people’s behavior and reading math books, so it’s no surprise that I’m anti-anti-intellectual. It’s no secret that if I had an anti-intellectual in the room here, I’d tell him or her (reading from Harper’s again) “New data suggested that Uranus is more chaotic than was previously thought.” [[See, statements in a different context are downright hilarious!]]

But it goes further than my kind of academic. The anti-intellectual sentiment— the insistence that it’s either common sense or it’s not worth the trouble—is a belief that there is no such thing as an expert. It is the myopic belief that if I don’t know it, then there’s nothing to know. As such, the anti-intellectual sentiment is often aimed at targets well far afield from intellectuals. At the Baltimore Museum of Art, the same establishment that houses Picasso’s Mother and Child, are such aggressively simple works of art as two silkscreen reprints of the Last Supper, and a curtain of blue and silver beads. Some readers will recognize the first as a work by Andy Warhol, and thus know the context: Mr. Warhol felt that the repetition and mutation of familiar images created new perspectives. For the second, as for a great deal of art that was clearly easy to execute, we don’t know the context at all.6 But even though we don’t know it, there is a context. The guy went to art school, has had a few focal ideas that drove all his work, and has done years of pieces that led to this simple bead curtain. So what is an expert to do? One approach is to always stick to things that are obscure and look hard. Make sure that every study, every work of art, every essay 6 Sorry, I can’t help the art snobs in the audience with the guy’s name. Enjoy being in the dark with me here.

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says fuc* you, I’m an expert and you can’t do what I do. But we value people who make it look effortless, whether they’re figure skating, producing a painting, or running regressions. We always value simplicity, so if all it takes to get across the message is a curtain of beads, then why overcomplicate things to remind the viewer that it took years of work to get there? Some of the best guitarists out there never really ventured past four chords, while the guys who can play intricate solos are often dubbed wankers. I’m glad I wrote my PhD thesis, and more generally love the idea of a thesis in general, including for high school seniors, BAs, or anywhere in between. A good thesis means that the author has become an expert in some tiny, irrelevant little corner of the world. Research ability by itself is valuable, and it’s good practice for when the student needs to be an authority in something of more practical value, but it also gives the student an idea of what the other experts of the world have gone through to get to their simple ends. Remember that part in Zoo Story where the guy says that “sometimes it’s necessary to go a long distance out of the way in order to come back a short distance correctly”? A student who has gone a long way in becoming an expert, and must then reduce that to the sort of ten second summaries that we all give to friends and family, will have a better understanding of the long distance that other experts have gone before they could string together simple words or beads or chords.

1.6

Paid to think 26 April 2006

When I ask people what they do, the most interesting answers are verbs. I don’t care that you’re an assistant executive manager for BungleCo. What have you been doing for the last eight hours? Have you been talking to people? Organizing papers? What conflicts do you need to resolve? Conversely, when I tell people that I work at a think tank, many of them are entirely unconcerned with what I actually do during the day, because they already have the correct image of me staring at a computer screen until my eyeballs hurt. The real mystery: where does the money come from? How does somebody make money at a place where people just sit around and, um, think? Writing doesn’t pay the bills. If you get a few hundred bucks for an op-ed, you should be delighted. If you put out a magazine article a month, you can make a living, but then you’re a full-time journalist and don’t have time for anything else. The book? I’ve made more on Amazon referral commissions than royalties for writing the thing. From a business perspective, the press placements are all just

1.6. PAID TO THINK

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advertising. Not everybody thinks they know all there is to know about knowing things. There are people who appreciate an expert. They realize that the most efficient means of doing things is a division of labor where they produce widgets and when they need a policy expert, they hire one, rather than thinking they can study up on the subject in their spare time. So when does somebody need an expert in a given policy? When they have a deeply-held opinion, and need somebody to espouse it. By finding an expert who happens to agree with them, the expert gets funded and the interested party gets support on its beliefs. And that is where all those studies funded by the most obvious donor come from. Since I know the software patent debate well, I can point to a pro-software patent study or two that says “We are grateful to Microsoft for their support” on the cover. Some read this and presume that MSFT found somebody to speak for them, and then purchased their opinion. But the flow probably went the other way: the expert formed his opinion (I have in mind two guys, one of whom I know), and then approached Microsoft about maybe providing funding for the research. This is how the funding for many a study happens: first, the expert does research until he knows the subject well. He has formed his honest best opinion about the subject. He starts writing up a few pages. Then, he shops it around. Dear philanthropic organization/corporation/wealthy individual: I have an opinion, and can state it eloquently and with authority. Further, that opinion happens to match yours perfectly! What a wonderful coincidence. If you’d like me to continue fleshing out this idea which I personally hold, then please send cash. The expert is independently deriving his opinion, but the funding certainly has great potential to corrupt the expert’s research. First, there are the details to be negotiated, wherein funder and researcher agree on the broad concept, but there may be details on which they differ. Second, there is the problem of the nonunitary actor. You know that guy that MSFT funded because they agree with him? We’re coworkers, to the extent that you’d call this work. When I plug in my laptop to write articles opposing MSFT’s IP position, MSFT chips in for the juice. There are a few approaches to the conflict. I’m happy to say that in my case, the administrators at my think tank are well aware that my writing disagrees with the position of one of its funders, and at no point have they asked me to tone down my bitching. They care more about doing independent research than any one donor, and know that the only way to please all the donors all the time is to never say anything.

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Another approach is to take such a firm opinion that there’s no way to budge. Are there orthodox economic motivations for government regulation? Absolutely. Will you hear about any of them from the Cato Institute? Funders know the answer to that one, and know not to bother asking. The final approach, of course, is to fold to pressure. I could only guess at how often this happens. To keep a parallel essay form, I should give an example here, but that would be rude. The other way that the ‘formulate hypothesis, then find funding’ approach can create bias is in the suppression of certain ideas. This is no conspiracy theory suppression, but the simple fact that publicizing an idea needs both an expert to formulate it and a funder to pay for it. You can find an expert somewhere that espouses any given idea, but the business side has a whole lot more money than the rest of us. So why doesn’t the policy world turn into a gigantic pro-business alliance? First, the funding for the pure social benefit is surprisingly large. There are general funds like MacArthur, Ford, Soros, Hewlett, and while we’re talking MSFT, the Gates Foundation, that have little or no interest in supporting moneyed interests. Any one of these funds could keep several think tanks running for a long time to come. Second, there’s two sides to every issue. Say Company A has a labor-intensive process to produce pollutants, while Company B has a giant machine that was built in Japan to produce the same pollutants. Company A will be happy to support bills that espouse anti-business import tariffs because they would hurt Company B more; Company B will be happy to support higher minimum wage laws, because doing so is handing a charge to its competitor. As for the overall issues of the pollutant’s environmental effects, you won’t see much disagreement. Thus, the problem of getting funding for policy research (and the problem of policy design in general) is finding the mega-rich interests that happen to agree with your belief. For any sufficiently detailed question, there will be some balance between the funders.

Other This was going to be a general essay about how a think tank pays the bills, but the question of how corporate funding can support objective and honest policy research is the interesting part. Keeping to my original intent, there are a few other folks who are interested in experts and willing to pay for it. There is consulting in the traditional sense of companies hiring an expert for the day. The guys who study international trade policy happen to know a lot about international trade that a business may be interested in. Others are interested in access for the sake of keeping engaged. People want

1.7. BEING A TOOL OF THE MAN

17

to be surrounded by folks who are beautiful and smart; the think tank ain’t doing much for the beautiful part, but has its share of smart folks who can say an interesting thing or two. There are people who will contribute to be a part of that. The administrators describe these folks as individuals who “get it”, where “it” is the value of good research, regardless of the bias of that research. If this were Broadway, I suppose we’d call these guys angels. There’s also the funding from the pure research supporters, such as the National Institute of Assorted, which is not nearly as exciting. Though, it’s a chance to mention an interesting paradox that applies to academic work in general: nobody will fund a study that doesn’t have a good idea of the expected conclusion. You can’t do the research until you’ve got the funding; you can’t write a good funding proposal until you’ve done the research. The academics who can unravel that knot live in big houses.

1.7

Being a tool of the Man 2 June 2005

I’ve been working exclusively at places with .edu in their addresses for the last seven years or so; The .edus have their own hierarchies, codes, and bureaucracies, but as you know, they are an order of magnitude smaller than those in the Real World. Now that I’m working for the third largest employer in DC, it’s taken a bit of adjustment. The usual trappings of tooldom are banal but ignorable. The office takes up a full city block, so the walk to the water cooler or the underpowered microwave is a long one, an expanse of speckled grey carpet. The tie is irrelevant. I have so many other pieces of individuality that matter (biking to work, running my own IT system outside of theirs, rearranging the furniture) that the problem of wearing nice clothes seems an aside. Yeah, I’d rather not wear it, and I have to change in the bathroom downstairs every morning, but I never understood why the tie became the symbol of oppression when there are so many other dumb, silly customs that are truly onerous. We’re working on a report on migration (i.e., immigration and emigration), and it’s an entirely different world from the academic. My boss stresses the fact that economists are storytellers; avid readers of this site will recognize this as a word choice away from my own insistence that all academic papers are a persuasive essay. The difference is in the story that one chooses to tell. One of those standard jokes about the Scientific Method: • 1. Form hypothesis.

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CHAPTER 1. WRITING, THINKTANKING, AND THEORIZING • 2. Conduct experiment to test hypothesis • 3. Change hypothesis to correspond with test results

And ya know, it’s kinda true for the theoretician. It is not unheard of for a researcher to write down a model hoping to derive a result, and then finding that the result needs a half-dozen caveats to work, or that the exact opposite is actually true. This is an honest means of deriving good theory, in which reality advises the math and then both advise the results. The same is true for a qualitative survey or any other sort of study whose primary intent is not apophenia-crushing. But the revised scientific method will not work for a two-volume report covering a dozen aspects of the migration process. If the report is to work out to a coherent story, then the broad outline of the story needs to be written before the research is anywhere near completed. So, what happens when the data disagree with the story? Strategy one: prevent this outcome by devising a hypothesis so bland that it can’t possibly be false. This already probably explains the format for most of these big overview reports, which are a great resource for tables and figures, but which manage to say approximately nothing. The base hypothesis of our report is that cooperation among countries instead of snippy bickering will be beneficial to all involved. If you’re somehow not convinced, you can read the supporting evidence in volume II. [OK, there’s a little bit more to it...] Strategy two: maintain enough flexibility. Before writing this, I had often complained that my Boss’s story kept changing. He’d ask me to write up a model to show that the black market for labor can be dried up by various changes one week, but the next he’s all about the demography of an aging Europe–but then the next he’s lost interest in that and wants me to look at remittance rates. From the perspective of the story here, his vacillation is trying to manage the fundamental conflict between telling a coherent story before the data is gathered and the story reality wants to tell. Although I’m often frustrated, I guess he’s doing as well as one could. Strategy three: spin! I’ve been doing a good amount of this, since my model produces a lot of null results. I usually put a header in front in the way of: the model shows that all the people who think an incremental change will lead to the sky falling are wrong. Instead, nothing ever happens. While we’re on the subject of spin, it’s worth distinguishing between the sort of report here and reports from people like FAIR (Federation for American Immigration Reform). FAIR will never publish a report that supports any loosening of immigration laws of any sort. Of course, this is not their official policy, but I’ve read much of their stuff for the last few years, and that’s certainly what turns up.

1.8. IN PRAISE OF NOT KNOWING

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There are other comparable fanatic organizations in any field and on both sides, and their story is rigidly fixed and will not change to accommodate data. What does such a group do when data appears which directly opposes their position? Strategies one and two (be bland or flexible) are out, which leaves strategy three (spin!), and perhaps another: Strategy four: Suppress! Strategy four will be used by both the bland megastudy and the fanatics. After all, one run of my model will give me about 15MB of data, which could potentially say something about any of the above topics; but in the interest of telling a coherent story, I’ll be suppressing 14.98MB of that data. The same holds of the surveys and regressions and other parts of the study: they’re all flexible enough to tell a story in any field, but will be used for only one. In that respect, this suppression is sort of like not talking about the paint job on the car that hit you—some detail is not really apropos to the story. Suppression doesn’t get insidious until one finds data that isn’t just not-apropos, but actually contradicts the story. Hopefully, strategies one and two kick in, and a good researcher finds some sort of compromise between the data and the story; for the extreme organizations for whom strategies one and two aren’t available, their only resort is to lie by omission, which we see more than often enough in such reports.

1.8

In praise of not knowing 18 September 2005

The big ol’ business report I’d already commented on the process of producing one of those megasurveys that multinational institutions like to put out. The summary: you need to have some definite hypotheses before you start writing, and if your analysis gets a null result, you’re screwed. This actually happened elsewhere in the report I’ve been dealing with: they spent about a month trying to run a regression that would find that remittance rates are positively correlated to growth. They had about ten years of data from a handful of countries, the data wasn’t great, and there are causality problems—if your country is about to suffer a downturn, going abroad and sending money home is a great strategy, so a surge in remittances may predict an economic downturn. In short, we don’t know. We’ll see what turns up in the actual report. But there’s a clear and evident incentive to make claims toward what the report is sup-

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posed to say—and no matter what happens with the numbers, the report will not say ‘we don’t know the relationship between remittances and growth.’

The Realtor(R) I have a pal who is interested in buying a house in Baltimore, so we went on a tour of Baltimore yesterday morning with a real estate agent (a Realtor(R) even). Saw lots of houses, asked lots of questions. Me: Hey, so these appliances with stainless steel front panels; what do you think that adds to the sale price of the house? Her: $5,000. We pass through my neighborhood, and there’s a big ol’ structure going up across from the university. Another person: Hey, what are those gonna be? Realtor(R): They’ll be condos. Me: Um, since I’m involved with the university, I can tell you they’re gonna be student housing, with a Borders & Noble on the first floor. My pal was impressed by the Realtor(R), who never emitted so much as an ’Um’ before answering every question. Me, I was entirely turned off. For our Realtor(R), the correct answer to question (1) is: ‘I don’t know.’, and the correct answer to (2) is: ‘I don’t know.’ If you don’t like these examples, it was a two hour tour, during which she had a precise answer for every question, so other examples are available on request. Our b-schoolers learn early on that confidence is essential, and derive a direct corollary that you should therefore never say you don’t know. Let this type of comportment be ‘business school confidence’. [The reader will note that this sort of faux confidence is often observed in our President, who is the first President of the U.S.A. with a b-school degree.]

“If we knew what we were doing, it wouldn’t be called research, would it?” It’s a cliché that academics are more precise and methodical than their businessworld counterparts, but there are enough businessmen who are precise and methodical. I believe that what actually separates the two worlds is that academics are allowed to say that they don’t know. In fact, even when academics say something, they’re really just lowering the level with which they don’t know. ‘Before, I knew nothing, but now I know nothing in only about 5% of the states of the world.’ The way we’ve been writing aforementioned report for multinational institution is that I’ve been sending in re-

1.8. IN PRAISE OF NOT KNOWING

21

ports with the usual caveats and confidence intervals, and then they delete all of that and leave the results. This would be grounds for disciplinary action at any research institution in the world, but is evidently just another day’s work for our business-oriented institution. The good academic exudes confidence as well, but does so in a manner very different from business-school confidence. The good academic heads the seminar with a list of items which he or she knows with confidence. Then, when a participant raises his hand and asks about something else, the academic simply says ‘I’m sorry, that’s not on the list of things I know.’ The audience walks out not thinking that the speaker is some sort of messiah, but with much more confidence in the short list of things that the speaker claims to know. The form of academic confidence explains a great deal of the academic world; e.g., why paper topics are so hopelessly narrow: it’s the author’s way of confessing ignorance about the whole world, save for a tiny sliver about which he or she can speak authoritatively. In the borderline world between academia and the b-world, different people go in different directions. For example, the World Bank’s World Development Report 2006 doesn’t include a single confidence interval that I could find (given a decent skim—I’ll say 95% confidence), even though it includes a number of regressions run in MSFT Excel by the authors. [And this addresses my commentary on the Bank in Section

Compare with this Urban Institute report which I chose because it happened to be on their home page right now. The executive summary makes no mention of statistical significance, and if you’re a policymaker who slept through stats, you will have no problem reading the report. But if you look at the half of the report labeled ”Notes on methods and terminology”, those pesky little stars start to turn up. It’s still not academic publication-level detail, but these guys took seriously the problem of describing where the numbers came from, instead of presenting a façade that the numbers and regression results are indisputable and certain. By giving b-school confidence and academic confidence parallel names, I’m maybe implying that they’re both sort of OK in their context, but I don’t believe this is so. B-school confidence is disingenuous, and is a form of misleading without technically lying. As you can see, b-school confidence has lately grated upon me. Why not just throw in that extra column of numbers indicating that we could be wrong? People have great alibis for it, typically based on a Lake Woebegone story: oh, you understand the concept of statistical uncertainty, and I understand it, but our readers don’t, or don’t have time for it. True, many people don’t get the minutæ of how one would apply a central limit theorem to produce a confidence interval, but they do understand what it means to be not-100%-certain. This may also be a social norm issue: if b-school confidence is the norm, academic confidence looks out of place, and vice versa. But if it’s a social norm issue, then we can do our part to change the norm: If you’ve been hanging out with your

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Realtor(R) for two hours and she has a confident answer to all your impossible questions, don’t entrust her with your business. If you do cite a report that doesn’t confess to ignorance on any topic, point out that you looked for confidence intervals, but found none. Just as you would normally let the reader decide what level of confidence is acceptable(*), you should let the reader decide how to interpret a complete lack of such information. [(*)By which I mean, don’t just report that this number has two stars attached and this other one has one star; give a significance level like 91.3%, and let the reader decide whether he or she is comfortable with that. Maybe print stars to suggest or guide, but not as the sole piece of info. But you knew this.]

1.9

Definition of a crackpot 20 October 2007

A crackpot is somebody who does not respect the prior literature. The easy way to not respect the prior lit is to ignore it. For example, a few months ago, a pal of mine asked me to review a paper from a physicist about an exciting new statistical mechanics approach to economic decisionmaking. Several pages of symbols later, I realized that he was describing the logit model, which had been written up by economists somewhere around the 1960s. In fact, the author even cited the standard citation for the logit model (from the mid-70s), but failed to make the connection. He just assumed that what he had was new, and did only a cursory browse throughout the economics literature before proclaiming as much. A great many blog comments, and comments while made over booze, are of exactly this form. You’ve got what may be a generally smart person, commenting on somebody else’s field. But when chatting with pals, it’s OK to not have the existing literature on hand, because everybody in the room is aware that nobody has any authority, and that nobody’s comments on global warming or what-haveyou really makes any difference. In that context, you’re no fun unless you’re at least a bit of a crackpot. In a sense, every grad student is a crackpot because they just haven’t had time to really read up. However, most but not all are able to recognize this and act accordingly. They inquire of others, ‘I have this nifty idea; how would you propose I fit it into the existing setup?’ Those who say things like ‘I have this nifty idea, and it is new and wonderful’ are readily (and most of the time, rightly) accused of hubris.

1.9. DEFINITION OF A CRACKPOT

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Root causes Beyond just ignoring the literature, there are the self-proclaimed revolutionaries who go out of their way to disdain the prior literature (e.g., FT Marinetti7 ). History talks a lot about people who brought about fundamental change, and doesn’t say much about people who made incremental changes. But the biographies often fail to mention how much time the revolutionaries spent reading the literature. I may have mentioned these guys before, but Thomas Edison didn’t invent the light bulb, and never claimed to; he just made (significant) improvements on the filament materials. Albert Einstein’s general theory of relativity was pretty darn original, but it was based on the Lorenz Equations, which are not named the Einstein equations. Einstein was famously an outsider—he was a patent examiner, not a physicist—but he enlisted the help of other prominent physicists in hammering out his theories. The individualistic mythos is allegedly a U.S.A. thing, but the world over has people who strive to be as self-sufficient as possible—meaning that they go out of their way to not read the literature. Further, we all have the tendency to think we’re smarter than everybody else, which often translates to either not bothering to check the literature, ‘cause it’s all dumb, or dismissing it quickly as not on track. All of this borders on crackpot. Those individualists in the Upper Peninsula are like this, as are the people who write lengthy tracts criticizing the status quo. Every class of grad students has one or two of ‘em, who reject the literature out of hand. I think I used to be like that, once upon a time, when I was less cynical than I am now. So the other means of being a crackpot is knowing that there has been prior work done on a subject, but just assuming that it’s all stupid. Those other people just don’t ‘get it’ the way you do. I.e., everybody else is dumber than you are. The root of such a belief is a massive failure of theory of mind—the ability of non-autistic and non-asshole people to develop a model of what is going on in other people’s heads. Which is why crackpot is not a compliment. [Most patent holders are very level-headed types, but crackpots also flock to the patenting world, because the concept of a patent is built on the idea that the recipient of the patent is smarter than everybody else and deserves to be paid for being a revolutionary. Folks like that are why I stopped reading the comments on patent blogs.]

The academic response So you could read the literature review of the typical paper as the ‘prove you’re not a crackpot’ section. Indicate a modest familiarity with the literature and a respect for those who came before. Then, when you say crap that’s completely off the wall, at least the reader knows that you are aware of 7

http://www.cscs.umich.edu/˜crshalizi/T4PM/futurist-manifesto. html

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the context in which you’re saying it. Academics have a crackpot sensor, and it is often very sensitive. But the requirement that you be at least modestly versed in the literature can easily create the sort of inner-circle feel that many academic organizations have. It does go too far sometimes: some people like to characterize an academic journal as an ‘ongoing dialogue,’ meaning that your contribution is irrelevant unless it centrally focuses on problems presented in the prior lit. This is where that sense of cliquishness starts to appear—especially when the lit you’re supposed to be respecting is considered to consist of the writing of a handful of star academics. All that talk about the value of interdisciplinary research goes out the window if the key criterion for credibility is being well-versed with the existing literature by a few people. Being that I’m kinda multidisciplinary, what with articles in genetics journals and law reviews, I get the crackpot glare all the time, even though I definitely know not to claim that my ideas are not in the lit. Anyway, there’s a balance to be struck. There are people who show up to economics seminars from their work as a know-it-all to just present their single piece of intuition as fact. They are annoying. But there’s a long ways between those guys and the people who have an active interest but are not entirely up on the inner circle’s writing. But the policy implications are easy for those of you dealing with academics on a regular basis, because it can be easy to not set off their hypersensitive crackpot sensors: just respect the literature.

1.10

Academia doesn’t scale 14 December 2007

The current academic model is based on the academic societies of the 18th and 19th centuries, e.g., The Royal Society of London for Promoting Natural Knowledge8 , est 1660. These societies were everything you’d imagine: a bunch of wealthy white guys, all best of pals, generally brilliant, debating and experimenting. Many wore powdered wigs. Journals were often filled with cleaned-up letters or speeches given by members. This is the root of the modern academic journal. Unfortunately, the model doesn’t scale from a gentleman’s club of up to a thousand members to the global mass that is modern academia. It reveals a specific worldview about where value comes from, which is not as advertised. 8 http://www.wired.com/science/discoveries/news/2007/11/ dayintech_1128

1.10. ACADEMIA DOESN’T SCALE

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Ad hominem caveats This little column was hard to write because I don’t want you to think I’m ranting about how all academics are evil. No, the simple thesis is that the current peer-reviewed journal system is ill-suited to the modern world. It works well for the small academic societies of the 1800s, and needs to be dropped now that the academic community is global and decentralized. After the initial statement of problem, I’ll get to some suggestions of how modern academia could evolve past the 1800s. As for my own experience, I’ve got my share of rejections from academic journals on the one hand, and a couple of papers published (or on their way to being published) on the other. I’ve also written two peer-reviewed books, partly because the peer-review process for books overcomes some of the small-circle problems that journal peer-review suffers. So I don’t comfortably float around the peerreviewed world, but I’m not a total outsider either. That said, we can get to the key conflict, which is basically the eternal fight between the small-circle meritocracy and egalitarian democracy, except sometimes those with the most merit aren’t in the small circle. The conversation The academic literature is frequently described as an ongoing conversation. This is a fundamentally different concept from being a repository of the best current work. The ongoing conversation story neatly follows the tradition of the society journals, which were sometimes literally the record of ongoing discussions held by the individuals in person or via letters. As we’ve all experienced at parties, it’s hard to walk in on an ongoing conversation, especially walking in on a conversation with people who don’t know you. The typical first response is not my, what an interesting new perspective but who the fuck are you?. The same holds with a submission to an academic journal: the first question is who you are, where you’re coming from, what perspective you have on the ongoing conversation, and then finally what you actually have to say. Law reviews, which are not really peer-reviewed in the traditional sense, take the direct approach and typically require a résumé with submission. For a small society, the who-are-you stage of things goes pretty quickly, because if the society’s members are willing to talk to you then you’ve already passed a crackpot test. But now that we’re an egalitarian world and journals accept paper submissions from anybody, the editor needs to start with filtering crackpots, and then move on to evaluating the merits of the work. Fear of crackpots The ‘ongoing conversation’ model is inherently conservative. After all, sometimes the topic of conversation really needs to change. To give a concrete example, there is a thread in the voter turnout literature over the claim

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that people turn out based on purely self-interested means: they find the likelihood that they’d be the pivotal voter, multiply by the expected personal gains from one candidate over another, and then choose to vote accordingly. The ongoing conversation is over reconciling this claim with the data, which contradicts it every step of the way. Gee, maybe the theory, which is countered by both intuition and empirical data, is just wrong. But it remains the baseline model, and if you want to write a paper about why people turn out to vote, you need to spend some portion of your time engaging in this ongoing conversation that really should have died a decade ago. The conservativeness is rooted in a fear of crackpots, as I’d discussed above (p Speaking a New Word I submitted a model of network formation to Economics Letters, which gave me a one-paragraph rejection, the gist of which was: a model of network formation isn’t Economics. I suppose this fact would be news to the editors of the Review of Network Economics. The intent of this example is to point out that the humans editing the journals evaluate the work based upon what they’re comfortable with, not based upon some sort of objective criterion that they as humans aren’t capable of achieving. We can go back to my favorite question: where does value come from? It doesn’t come from new knowledge about the world, but from the belief by other humans that such knowledge is important and relevant. That is, the peer review system establishes science as firmly subjectivist and relativist, no matter how much it pays lip-service to objectivity. Or, we can go back to what I consider to be the fundamental rule of nonfiction writing: the work should make the reader feel smarter. The reader should know how to do something s/he didn’t know how to do before, or learn facts and a means of structuring them that the reader hadn’t known before, or otherwise make the reader feel more secure about his or her existing knowledge. In the political context, people are much more likely to read articles and books that agree with them than works that oppose them (and yes, this phenomenon has been extensively documented in peer-reviewed journals). In the specific case of a peer-reviewed journal, it’s not just anybody you’re trying to make feel smarter, but the referee, who already has an established worldview and an established set of tools that he or she learned in graduate school. The process of presenting a new method, like presenting a network model to an old school economist, is exceptionally difficult, because new things are threatening and make the reader feel stupid until the reader has had time to absorb the full implications. Meanwhile, the rift between ‘useful’ and ‘useful to the current members of the ongoing conversation’ grows.


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Let me again clarify that this isn’t about being evil, it’s about a well-known fact of human nature: we are more comfortable embracing the familiar than the foreign. Travis and Collins [1991] explain that this is not cronyism or an ‘old boy’ network, but the tendency to pick people from your intellectual school of thought over outsiders—which can often look a lot like cronyism and an old boy network. Anonymity Anonymous review may make sense in a small society, where you may have to reject your best pal. In cases like these, you always know who wrote the rejection anyway. But when the author and reviewer may be continents away, anonymity just produces low-quality reviews. Anonymous peer review doesn’t scale, but it is necessary to perpetuate the system as it exists today. Pretty much every academic has a story about a rejection they got that was rude to the point of humorous. My own rejections have just been boring and typically indicated that the review didn’t read the paper. E.g., I once received a rejection—after a year and a half wait—based on how I numbered my theorems. A rejection I received after I started writing this essay chided me for failing to discuss the multiple possible modes in a probit model—except the probit likelihood function is globally concave, and therefore always has exactly one mode. But hey, there are no peer review reviewers to check the facts or merits of the anonymous review.9 This one has at least a partial solution, because anonymity is an endogenous social norm: we can sign our reviews. I do, and make a point of never saying anything in a rejection letter that I wouldn’t say to the author’s face. The problem with this, and why it’s not the norm, is that I can’t be lazy. I can’t reject based on ad hominem excuses or theorem numbering or a vague sense of dislike. In short, I can’t pretend that I’m being egalitarian and working from the merits of the paper while actually working to maintain a closed society. Competition In both small society and the globe at large, there’s always a conflict between striving for the greater good and for individual advancement. For a system where peers review your work, this is a central conflict, because the people most qualified to evaluate your work are your direct competitors. In a small society, your direct competitors are probably also your pals. Any business organization is naturally something of a social organization as well, and 9 A not-anonymous peer points out that the editor should be checking the reviews for quality and acting accordingly. However, part of the referee’s job is to save time and effort for the editor, and editors are generally inclined to trust the referee, so human laziness and trust generally prevent editors from overturning all but the truly worst reviews. I did once have an editor who told me that a referee report was so bad that it indicated more that the referee was a crackpot than that there were problems with the submission, so the editors are not entirely asleep.

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apart from some famous disputes (e.g., Liebenitz v Newton), we find that all those letters between famous colleagues were generally collegial. So when somebody accepted an article from a competitor, it was at least from a competing pal, who would be able to give a leg up next time in return. In a global society, the author and the person reviewing a paper are just competitors. The one who is doing the review was selected because s/he is considered to be part of the established system, and has something to lose, like real live funding, by expanding the membership of the established system. I went to a delightful conference the other day regarding a new paradigm for demography. When the question of getting funding from the NIH came up, a couple of people suggested just not bothering. The people who read the grant applications are the people who were most successful in the last decade, and therefore are the ones who most stand to lose from a change in paradigm, and are in some ways the least qualified to evaluate a change of topic from their own life’s work. The alternatives Now and then, people tell me that the peer review system is a revered part of science. This is even political—the PRISM coalition10 is a group of academic publishers who oppose open access journals under the presumption that it is the private, traditional peer review system that ensures high quality in publishing. The claim as I stated it here implies that peer review has evolved into what it is based on centuries of refinement and improvement. Rather, it’s a throwback: it’s a system that primarily emerged among small academic societies and has entirely failed to adapt as modern academia stopped being about a few inner circles and became an open, global meritocracy. So, what can we do? There are already many online repositories to be had. My favorites are the Arxiv11 for math/stat/physics and the self-descriptive Social Science Research Network12 . The SSRN is especially important because of the absolutely pathetic speed of peer review in the social sciences. That paper above that got rejected over nonexistent nonconvexities in the probit (it’s December): I submitted that paper in January. Amusingly enough, the reviewer criticized my literature review for not citing papers published in May. So if we relied solely on the formal journals for social science research, the entire system would quickly grind down, as everybody would be a year behind all the time. Instead, we spend more time at places like the SSRN. So the SSRN is already eating the journals’ lunch with regards to the work of archiving and dissemination. But the SSRN lacks peer review, and an endorsement 10

http://www.prismcoalition.org/ http://arxiv.org 12 http://ssrn.org 11


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system is still valuable and important. It’s still the case that 90% of everything is crap, and some papers are more important, better written, or otherwise of higher quality than others. We humans with limited time on this Earth need some sort of guidance toward what is worth our time. Could Arxiv and the SSRN implement peer review? Sure, in a heartbeat. Especially if we give up on the gentleman’s society rule of anonymity, a paper’s web page could include endorsements or comments from others. Readers will then have more than enough to evaluate whether the paper is useful, accurate, and so on. Depending on how reviewers are assigned, authors who write about relatively new methods may be more likely to find another party who doesn’t feel dumber when confronted with that specific method. [The Arxiv already has a very weak endorsement system, but it doesn’t yet provide as much information as users need.]

We’d like authors to revise based upon comments and improve things accordingly; which means that there’d need to be some sort of revision control system in place. The author may have the right to publicly respond to public peer review, in which case the ongoing conversation would happen right there on the page. Since a peer review is now an invitation from the editor to publish a short article, colleagues now have a half-decent incentive to actually do peer review beyond the vague sense of responsibility that is the sole, insufficient motivator now. [And yes, people suck, and there are bad academic apples who would say mean things and try to ruin the system for everyone. But this is still a system that restricts commenting access to named and identified peer reviewers, not YouTube. All of these details are a low-grade kind of problem which SSRN and Arxiv could easily surmount with a few days of coding and some vigilance on the part of the editors.]

A system like this would also take the semi-sacred significance off of peer review, which is a good thing. The popular media often refer to peer-reviewed papers as if they are unquestionably valid, and not-peer-reviewed papers as necessarily pseudoscience, but with all the problems underlying the system above, the signal is not so clear. A public endorsement system would guide the reader toward good papers but not imply that the paper is the gospel truth—just that two or three knowledgeable but fallible humans found it to be of high quality. I expect that the concept of a paper—a single unit of scholarship that others can read and refer to—will continue to exist, but its delivery and evaluation will have to change. Delivery has already changed: nobody goes to the library to pick up dusty bound volumes from the 1800s, since they’re in PDF format on Jstor. Nobody in the current ongoing conversation of social science even bothers with new journals as they are mailed out parcel post, because they’re just the archiving of research from a year or two ago. The archiving process will be online no matter what. The endorsement system as it stands will live a lot longer, because it clearly benefits the incumbents, provides a means for the small inner circle to keep itself

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small, and provides a shield of anonymity that many reviewers continue to use as a crutch. Especially in social sciences, this is a sad state of affairs: we have a dozen journals devoted to mechanism design and making sure that people’s incentives are aligned with our overall social goals, and yet we still base decisions on anonymous comments from those who are most likely to lose funding and relevance to something new.

1.11

Moderate economists unite! 26 April 2004

Yesterday, I handed out copies of the main essay of Chapter For example, here is a flier for the World Bank Bonds Boycott. As a form of protest, the boycott is on par with not voting. Yeah, not buying bonds and not voting sends a signal, but one which is entirely indistinguishable from apathy. Back to the pamphlet: “The World Bank’s voting structure is based on a system of one dollar, one vote. The G-7 governments control 43% of the voting rights”, it reads. But no, that’s the IMF, a linked but very distinct organization. [The WB gets its money from bonds; the IMF directly from governments (mostly the G-7 govts, as described above). If the World Bank were one dollar=one vote, wouldn’t it make sense to buy all the bonds you could to gain that much more control over the organization?] One person gave me a t-shirt in exchange for my essay. Thanks, I wore it all weekend. It has the WB logo on the front, with ‘Billions served?’ underneath; on the back, it lists some facts (wait, I have to take off the t-shirt—topless blogging, ladies): Of the 4.7 billion ‘satisfied’ World Bank Customers: • 3 Billion live on less than $2 a day • 1.5 billion do not have clean water to drink • Nearly 3 million die each year from vaccine-preventable diseases Yup, that’s right: the World Bank works in the most impoverished places on Earth. Those bastards—we have to stop their evildoing now! The shirt also has a URL for A World Connected, a site I haven’t looked at enough to comment. Its cover stories at the moment include one about protecting U.S. jobs and one about a guy who won awards from libertarians, so I dunno.

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These protests leave me feeling lonely and isolated. The preparatory rally is necessarily short, and short on facts. There’s a lot of repetition, in which the leader prepares the crowd with a few vaguely witty chants (which I won’t bother repeating here). Chanting leaves me so cold. When I was living in Chicago, and the Bulls had won, I went up to Clark & Belmont, knowing that a crowd would be there, and indeed, a crowd was there, and everyone was happily whooping. A poor guy in a pickup happened by the intersection, and while he was idling at the red light, a bunch of us jumped in the back. It was fun. We whooped. The guy, bemused, drove for a while. Meanwhile, we whooped. Eventually, we got tired of whooping, and all fell silent, facing each other in close quarters, as if to say, ‘OK, um, now what?’ Bemused driver eventually turned around and dropped us off, and we half-enthusiastically got out. So I have a lot to write about the IMF, but couldn’t chant much. In fact, as a firm believer in shades of grey and qualifying all sound bites, I don’t think I’ll ever find myself in a crowd I can totally believe in, which is somewhat disheartening. When you’re in the majority—at least among the people in the room—you don’t have to defend much of anything. In a world where there are only two sides, you’ve got a better than fifty-fifty chance of being in the majority among your pals. But in a world where there are a hundred different beliefs about a hundred subquestions, there is no solidarity to be had. [[Poole and Rosenthal [1984] helped with this, by the way. They found that two dimensions, economic and social, explain about 90% of the variation in voting patterns among Congressman. E.g., somebody who supports abortion rights is very likely to want to dissolve the World Bank and Israel. Whether there’s a consistent logical thread connecting these things is left as an exercise to the reader, but the Congressional stats and the turnout at the protests certainly back this correlation up. You could take this in two directions. One is that there are consistent points of view which lead those with those points of view to all agree on a dozen different issues at the same time. The other is to say that it’s all-but-haphazard, a question of what your pals wound up thinking. For example, at last night’s punk rock rally, some punks buzzed the event chanting ‘You can’t be vegan and prochoice!’, but I’m told that at today’s march, the ‘Vegans for choice’ contingent was in full force.]]

So it feels good to join the crowd and not have to think. I do not think that this is a bad thing. There are a three reasons for this: the first is that, for the most part, the protesters on the street probably won’t have much of a direct influence on things, so the rally is all about its side-benefits. Foremost, it’s fun. It also allows you to hear opinions on issues that are tangential to the issues at hand, such as the guy who was handing out fliers about halting the embargo on Cuba at the WB protest. It allows networking in the traditional sense, getting people connected to work on more effective campaigns involving cash, attempts to influence the non-converted, and attempts to influence people who write laws. Finally, it’s not all groupthink, so

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the rally allows people who meet there to debate a bit about the details of the issue. Second, consider the alternative to such mass, ideologically watered-down action, which was sort of revealed by the people who canceled their memberships at N.O.W. in a previous entry: “I agree with everything you say, except your endorsement of Carol Mosley Braun was inane. Cancel my membership and don’t ever talk to me again!” If everybody thought like this, micromanaging group ideology, no organization large enough to do anything would ever exist, and bickering would rule the day over actual action. The third reason why these crowds are a good thing is the effect of radicalism on others, a subject which I’m going to put off until next episode.

1.12

Moderate Economists II 4 May 2004

I had dinner at the home of Mr JR, of Chicago, Illinois a few times. J is a defense lawyer, and has argued more than his share of pro bono death penalty cases (before the IL Supreme Court realized the whole death penalty concept was just a bad idea and imposed the moratorium). More often, he’d defend alleged drug dealers, who somehow found the cash to pay Mr JR’s hefty hourly fees. My favorite story was about the guy that he defended with an alibi defense. It was so airtight because the prosecution had given the wrong date for the crime. Through procedural wrangling which technically broke the rules, the prosecutors corrected their errors, appealed the case, and had the guy convicted. Couldn’t you have used another defense, I asked him, and he replied, “Well, no. The fucker did it.” He explained why he was comfortable defending the guilty thus: the adversarial system works by two advocates making as forceful an argument as possible for his or her side, and a judge who selects from these the best of all possible arguments. The conditions under which this works are beyond the scope of this note (it was a chapter of my dissertation), but you can see that if everybody does their job perfectly, then this system will indeed work. [But do you break the procedural rules when the prosecutors give the wrong date?] Outside of the courtroom, there are more than enough people who believe in the adversarial system, or at least seem to. For example, there is the Federation for American Immigration Reform (FAIR), an organization which advocates tighter immigration restrictions. Although the name and stated purpose is just ”reform”, the reader will not find a single instance where FAIR advocates for a liberalization of immigration restrictions (not even for the highly skilled). FAIR is at the far end of the spectrum, and every single argument they make will pull toward that far end. The International Intellectual Property Institute (IIPI) advocates for stronger

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intellectual property laws, the world over. They will in no way entertain the possibility that IP in the U.S.A. is too restrictive, or that other countries in other situations may benefit from laxer laws. For example, Africans are dying by the millions from AIDS, but the IIPI has an explanation of why allowing generic AIDS drugs won’t do anything to stem the flood of death and misery. Their argument in a nutshell: malaria pills are generically available, and people still die from that. Going into more detail, they say that the infrastructure isn’t there, so that even if trade-related IP isn’t enforced, Africa still couldn’t produce the drugs it needs. This paper works fine if you have blinders on, adjusted just right so that you can see Africa and the U.S.A. but can’t see Brazil, which has had great success in saving people’s lives by ignoring US patents. The drugs produced there are as effective and safe as those from the U.S.A., and could potentially be exported to Africa and other countries, but for Brazil’s understanding that if it expands its program to helping people elsewhere in the world, it would jeopardize the entire project and thus Brazilian lives [see Wired news, a more liberal source13 ]. The IIPI’s failure to address the fact that other countries do have the infrastructure that Africa lacks, and failure to acknowledge that the market has already invented mechanisms whereby lives could be saved if IP restrictions were weakened, seems almost disingenuous to me. On the liberal side, you have your share of extremists as well. PETA comes to mind, or the dissolve-the-World-Bank contingent from last week. Here14 is an occasionally insightful thread from my favorite discussion group about Richard Stallman, a fanatic in direct opposition to the fanatics at IIPI. I have more sympathy for the far left, but am still annoyed by their shrillness, and inability to accept reasoned arguments or to produce reasoned arguments of their own. Part of this comes from the simple difficulty of telling a story which is both true and cuts absolutely no slack for the other side. Usually, the other side is populated by human beings, who have non-evil reasons for believing what they do. How do you demonize those people, deny their arguments, and tell a true story with a straight face? Mr. JR had a simple method: a firm conviction and faith in the adversarial system. Public discourse doesn’t have such an easy myth to fall back on, so fanatics need to resort to a simpler, tried-and-true method: being dumb and uninformed. Conservatives do this by using an oversimplified free-market model (unless it doesn’t fit their agenda); liberals do this through an oversimplified characterization of corporations and the wealthy (unless they want to buy a car). Both points-of-view entirely fall to pieces on analysis, so both sides avoid deep analysis 13 14

http://wired.com/news/politics/0,1283,44175,00.html http://www.plastic.com/article.html;sid=04/04/21/02445302

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at all costs, leaving things at a surface level. Which is why I handed out essays at the World Bank protest, and why I wrote the ‘how to argue with a conservative’ piece (which I swear I’ll finish next time, unless something comes up). I believe more informed discourse is better discourse. But sometimes I worry that I’m sabotaging the natural balance of things. Here I am, trying to pull the far left closer in, but the far right are kookier than ever. I have no dissertation chapters to back this up, but it seems evident that having more rabid leftists can indeed pull the final outcomes more toward the left. E.g., if Richard Stallman hadn’t been such an antisocial and annoying person, we wouldn’t have the wealth of free software today. And the IMF does still have a large population of rabid neoclassicists. Maybe a rabid left is more of an asset than an informed and carefully reasoned left. This brings me to the final hazard of being a moderate who acknowledges that both extremes have some validity: your essays always lack a forceful conclusion.

1.13

Teaching the debate 12 December 2005

I had a wonderfully educational day on Amazon.com today. Before getting to the main subject, let me suggest a fun Amazon chestnut: if you click on “show all customer reviews”, you can sort the reviews to show the lowest rating first. Then, you can read one-star reviews explaining why works like The Great Gatsby or All the King’s Men were terrible books. We had somehow gotten on to the topic of evolution, and I pulled up an evolution textbook, where all of the one-star reviews were about how misguided it is for a book to call evolution “science”. For balance, I pulled up Of Pandas and People: The Central Question of Biological Origins, which got many more flames than the Evolution textbook. After a few of the more entertaining reviews, one wonders whether any of the people on either side have actually read the books they are reviewing with such revulsion. So, I started reading Pandas. The book opened, as do many biology books, with a discussion of chemistry: how genetic information is stored in DNA, which is a sequence of amino acids, and how scientists have been able to take a mixture of basic elements and zap them with electricity and wind up with amino acids. Also, how scientists have not been able to take the next step to turn those amino acids into self-replicating strands of DNA. I skipped to the section on genetic mutation. It pointed out that the intelligent

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designers of old misinterpreted Plato to say that there are a set of ideal, immutable archetypes for each animal. This is absurd, because we observe evolution and change and even extinction. No, the correct interpretation is that there are a set of species, but those species change with time. That is, within a species there is genetic drift and variation. One presumes these species match Linnaeus’s use of the term, but I didn’t see this supported or refuted in what I’d skimmed. However, to say that there can be unlimited variation, wherein one species transforms into another, is just absurd. Modern scientists readily induce limited variation in test animals, causing offspring to vary either by Mendelev-style selective breeding or more direct manipulation of the gene, but modern scientists have never in the 62-year history of genetics been able to cause sustained, unlimited genetic variation. Yet they continue to pretend that such a thing is possible. The textbook is not at all what I’d expected. It makes every effort to not deny lab-based scientific evidence. No, it takes the pragmatic approach: what is the absolute minimum one needs to support the claim that there was a Divine intervention to create life and that people are not descended from monkeys? The text supports everything in modern science, except those few steps required for those premises. Sure, amino acids from random variation are OK, but that last step where they become an informational code is not. Genetic variation is OK, but only within species. On the one hand, I found this romp through creationism to be refreshing, because it was not nearly as crackpot as I’d feared. The authors know a whole lot more about genetics than I do. On the other hand, it’s that much more frustrating. They understand all of genetics, they understand genetic drift, but they just draw an arbitrary line that says that genetic drift has to stop at some point. No matter how cool they may be about the biology literature, that statement that there exists an arbitrary limit to genetic variation is the purest of dogma. The constructive means of handling the dispute would be to inquire as to the mechanisms that limit genetic variation to within-species changes, but I could not find anywhere in my short jaunt through the creationist literature the slightest suggestion of what the mechanism is that limits genetic drift to within species boundaries. We’re just supposed to take seriously the assertion that genetic variation is limited to what we’ve been able to observe in the last few decades, in nature or the lab, and no more. I want to shake these guys and make them learn statistics. If a million draws from a distribution all fall within five standard deviations of the mean, that doesn’t prove that there is a mechanism in place that forces the data to fall inside five standard deviations, it just means that you’ll need to make billions of draws to observe events seven or eight standard deviations off. Doing that could take millions of years, but one in a billion is substantively different from mechanically impossible. Finally, if I were to put a review on Amazon, I’d say that the book is defensive

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instead of constructive: it points out those parts of the standard evolutionary model that don’t work, but merely asserts the alternative model rather than providing a positive mechanism explaining why the alternative model is correct.

Teaching the debate Following the ultraliberal principle that all views—especially those that are contrary to the beliefs of the authorities—deserve to be aired, the intelligent-design team push for the debate to be taught in schools. I wholeheartedly agree with them. I think it is a salient debate that should be taught. The key lesson that teaching the debate would cover is the difference between faith and science. It is not the night-and-day difference that some would describe it as. Richard Feynmann has gone on record stating that faith is based on absolute certainty while science is based on never knowing, and therefore the two can never merge. To leave it at that misses some important details, so let me explain exactly how this is so. I prefer to describe the process via the Bayesian model of inquiry: people begin with a prior belief, gather data, and then update that data to arrive at a posterior belief. [[Note to statisticians: this is a model of thought and human beliefs that mirrors but does not match the data-processing method named Bayesian updating that competes with classical hypothesis testing and is intended to mirror this process of human belief formation. All of this is named after the Reverend Thomas Bayes, by the way.]]

There are other words one could use instead of beliefs. For example, one could use biases, in which case we’d say that the researcher begins with some biases, gathers data, and concludes with new biases which are closer to reality. But bias has a negative connotation that a belief doesn’t necessarily merit: my bias toward the theory of gravity is very well-founded in data. One could even use the word faith, but the important distinction between a faith and a belief or bias is that a faith, as per Mr. Feynmann’s definition, can not change. The researcher begins with the faith that something is true, gathers data, and ends with exactly the same faith. To teach the debate properly would require that we look to examples from history such as the repression of Copernican beliefs by the Church, and how, even though we have never made a star in the lab and the Copernican model of movement of the planets is still just a model, the preponderance of evidence was so great that the Church eventually had to concede, and that which it had taken as un-updateable dogma was updated. Has the Church’s claims about wheels within wheels been disproven? No, but there is so much data against it that we have a very strong bias against it, and most are willing to just round off the statement “I am 99.999% certain this is false” to the technically incorrect but much simpler

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statement “this is false.” Teaching the debate would involve a digression into the idea of falsifiability, and how it fits into the bias-updating model. We would begin with a moderate belief in a theory, gather data, and depending on the data either end with a stronger or weaker belief in the theory. By repeating this process a thousand times, we might wind up with a very strong belief in the theory. But if there is no downside to the process, so that there is no data that could possibly give us a weaker belief in the theory, then there can be no upside: no data that could possibly give us a stronger belief. We’d start with a moderate bias toward the theory, gather data, and since the data is irrelevant we’d end with the same moderate bias toward the theory. The cliché applies: nothing ventured, nothing gained. Applying this to the questions above, we see that the claim that there are set species and that they can not inter-evolve is not falsifiable. There is no set mechanism to define species besides “that which seems to inter-evolve”, so as we find wider and wider evolutionary changes, we can rewrite the definitions so the system continues to work. If there were a claimed mechanism that puts a fixed (as opposed to a statistical) limit on evolution, then we could design tests to determine whether to place stronger or weaker belief in those mechanisms, but lacking such a mechanism, all we can do is seek the widest evolutionary change we can find and then rewrite the definition of species to fit. This is what our authors did above when they pointed out that former creationists who’d believed in a Platonic ideal for each species were wrong. Notice that non-falsifiability does not mean that we can never reject the theory, because there is a sort of race among theories. Every year we get new data that the range of genetic drift is larger and no new evidence that the range of genetic drift has a fixed upper limit. As such, a formerly neutral belief in the falsifiable claims of mainstream evolutionary theory would get stronger every year, while a neutral belief in the non-falsifiable claims of intelligent design would remain lukewarm. Eventually we get to a point where there is so much more data supporting one over the other that we just throw out the weakly-supported theory. Teaching the debate would indeed show that science is a human process, not the perfectly objective mechanism that it is sometimes characterized as in the media. It would show how each individual paper or study takes the steps above— author begins with some belief, gathers data, and revises those beliefs—and how the preponderance of hundreds of thousands of papers allows us to do the same belief-updating process on a larger scale. This would show the student that although science is a human process and is about the updating of biases, some biases have more support and more validity than others. Teaching the debate would not reject the idea of faith. It would point out that there are limits to what scientific inquiry can gather data on, and these realms (such

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as ethics) are a fine place for faith to take over. The perspective and opinions that are put forth in literature and theology are all valid and deserve to be heard because there is no way to gather data to disprove a perspective, but beliefs in different theories are not equally valid, because there exists data that allows us to put more or less belief in some. One does not need to teach a debate in a science class the way that a debate would be taught in a literature or sociology class because there are some concepts so unsupported by data that we stop saying ‘we believe theory A has much, much more support than theory B’ and just round off to ‘we believe theory A’.

1.14

Is IBM evil? May 2003

In the 1940s, a number of IBM’s subsidiaries assisted the Nazi government in implementing the logistics of the Holocaust, to some extent being entrepreneurs who originated some of the ideas that made the whole thing possible. For example, every serial number tattooed to a victim’s arm corresponded to a punch card manufactured and processed by IBM. The involvement is so well documented that even IBM doesn’t deny it. When Edwin Black organized the facts and wrote the story for the lay-reader in a book entitled IBM and the Holocaust [Black, 2001] , IBM’s official response was to play down the book by pointing out that it didn’t say anything that a host of historians didn’t already know. But what does this piece of history say about the IBM of today? By way of discussion, and for the sake of not sounding like a crackpot (always a hazard when talking about the Holocaust), I offer a few social science approaches to the Holocaust before returning to the question of what IBM (and you) should do today. Game theory Game Theory begins with a situation in which people have an abundance of actions they could take, but those actions depend on the actions other people choose. John Nash proved that given a few simple technical conditions, there are always equilibria, wherein everybody implicitly agrees to behave in a certain manner and is OK with that behavior. This is why he won a Nobel prize and has books and movies about his life. The problem with Nash equilibria is that there are often many of them. One or the other may be more likely, but before the fact, they’re all possible. For example, everybody in England chooses to drive on the left, whereas in most other countries the equilibrium given the same situation is for everybody to drive on the right. Why’d it happen one way or another? Historians who have studied the question

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can amalgamate all the random events into some compelling stories, but here’s my own summary: it’s basically arbitrary. If we had asked people in the Germany of 1935 whether they would assist in mass killings, all but a handful would have said no; yet in the Germany of 1945 we found enough Germans who said yes that mass killings were efficiently and extensively conducted. Why’d Germany as a country choose this approach to getting out of the depression when other countries just chose to have people build extraneous public works? Why’d the society switch from a peaceful equilibrium to a violent one? Many thousands of pages have been written on the subject, the basic conclusion of which is: it’s basically arbitrary. To be literal about Game Theoretic examples, consider Chess. There is nothing inherent to the setup of the game that causes a given outcome. Sometimes white wins, sometimes black wins, depending on what the people playing the game do. Similarly in social situations: sometimes one side prevails, sometimes the other, and we never know which it will be until after the fact, and if we put similar people in a similar situation, the other outcome could easily prevail. Conversely, equilibria which occurred elsewhere in time or space can always crop up again; the best we can do is try to bias things in one direction or another, by taking away black’s knight, setting social norms about not killing Jews, or establishing rules explicitly outlawing hate crimes. What the historians say Hannah Arendt wrote the seminal book on the question, Eichmann in Jerusalem [Arendt, 1963]. This is the book which coined the phrase ‘the banality of evil’ to describe people like Eichmann, who was a dull bureaucrat who didn’t think twice about the implications of his paper shuffling. The moral (one of many): any organization is capable of evil, because the size of the organization allows an action to be broken down into bite-size, palatable pieces to be farmed out to people who would never approve of the whole. Their individual roles seem trivial and relatively blameless, and just as the officers at Nuremberg claimed that they were “just following orders,” everybody in an organization has somebody else they can point their finger at. Yet the end result is an equilibrium which nobody would have volunteered to bring about. Ronald Wintrobe, in the final chapter of The Political Economy of Dictatorship [Wintrobe, 1998], extends the story that any individual only makes a marginal contribution by describing the bureaucrats who are entrepreneurs within the system, working hard to have a more-than-marginal influence. They advance in the bureaucracy by taking the initiative and having ideas which will help the organization achieve its goals more effectively. They do not ‘just follow orders’ but take action to help the world along to the evil equilibrium. Wintrobe says Eichmann

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was a bureaucratic entrepreneur of this sort; Black shows that the heads of IBM’s German subsidiary were. Such entrepreneurs always exist, pressing the society to move toward the evil equilibrium, in a manner that creates business or influence for them. These authors show us the structure of the evil equilibria. There will always be people who are callous to moral considerations and will attempt to shift the organization to their benefit and the detriment of the rest of the world. Then, most of the people who have to take action to bring about a bad outcome can’t see the big picture and so have no idea where their actions are leading to. So the protest singers have the right idea: large organizations (IBM, the government) have a comparative advantage in implementing evil equilibria, and we need to maintain especial vigilance over them. Within this context, the big question is: what can these organizations do to ensure that the organization won’t fall into an evil equilibrium, either through manipulation by bureaucratic entrepreneurs or just by wandering into them? The IBM question Let’s return to present-day IBM, and the question of whether they’re evil. Yeah, their laptops are all an evil-looking black; they make a server called The Intimidator; they’re a big, blocky bureaucracy like every other big, blocky bureaucracy. But that’s mere cosmetic evilness. As should be clear to this point, evil does not hit anybody over the head, and those who say that IBM’s German subsidiary didn’t know what the Nazi regime was up to are to some extent correct [but see Edwin Black’s comments]. But today’s IBM chooses to take a simple, insidious course which exacerbates its past: it tries to forget. In a press release discussing Edwin Black’s book, IBM states that it “[...] looks forward to and will fully cooperate with appropriate scholarly assessments of the historical record.” This follows discussion of the logistics of which universities house IBM documents. The message is clear: nobody in Armonk, NY, would be willing to operate a gas chamber, so the matter is a “scholarly” and “historical” question. If the important moral question were “Should IBM be held accountable and pay reparations that would affect its balance sheet?” then IBM’s insistence on averting its collective eyes makes sense–the IBM of today doesn’t want to have to pay the debts incurred by the IBM of yesterday. But there is a far more important question: how do we keep such things as genocides or mass internments from ever happening again? This is the question which affects us today, and is the question that IBM can best help to contribute to, and yet seems to go out of its way to avoid. The above press release was written in February 2001, so IBM didn’t know any

1.14. IS IBM EVIL?

41

better, but the follow-up of March 2002 doesn’t seem to say anything to change the claim that this is a question for researchers, not the people who head today’s organizations and build today’s machines. IBM’s business conduct guides say nothing about refusing business from parties with suspect intentions or who aim to trample the rights of citizens [as of 2 May 2003]. As far as I could ascertain from their publicly available information and from correspondence with employees, IBM has made no changes that would ensure that its bureaucracy can not re-entangle itself in those past misdeeds which it “categorically condemns.” Generalization From IBM’s second press release discussing Edwin Black’s book: “A review in The New York Times concluded that the author’s ‘... case is long and heavily documented, and yet he does not demonstrate that I.B.M. bears some unique or decisive responsibility for the evil that was done.’” [Here is the full review.] I agree with the reviewer: IBM was not unique or decisive. IBM is the paragon for this essay because their work is dull and doesn’t seem related to anything we picture oppression on a mass scale to look like. Also, there is nothing hypothetical about their situation: a subsidiary did provide substantial assistance to Germany’s eugenically-oriented goals, and its official statements of today do make an effort to forget that. Yet everything we could say about IBM we could say about any other organization or person: each of us is capable of assisting in evil, there are situations which would tempt any one of us to do so, and all of us are more comfortable just not thinking about it. Many people with whom I have discussed this topic point out that governmentsponsored genocide is unlikely in the USA, so the game is fundamentally different. This would be to see white win a dozen games and to assume that this means black can never win. The game may be biased toward white, but that is by no means a proof of impossibility. Over the lifetimes of our elder citizens, the USA has gone through many periods which we collectively look back on and exclaim, ‘What were we thinking?’ How did Japanese citizens wind up spending years imprisoned in internment camps for no reason? How did McCarthy manage to ruin the lives of hundreds of political enemies? Forty years ago, lynchings weren’t prosecuted as crimes. No, this stuff wasn’t genocide, but it certainly wasn’t OK, either. Others I have met contend that the situation was much more ambiguous in the 1940s than it is now, and it wasn’t so clear-cut that IBM shouldn’t have been involved. This is entirely the point. If it happens again, it will be just as not-clearcut until after the fact, so we must plan for it before it happens. You So ask yourself, given that you have perfect retrospective knowledge of history, what you would have refused to do. Would you have supported and aided in

42


the registration of minorities? If not, then you should not support it now. Would you have accepted that other people around you were being imprisoned without habeas corpus? If not, then do not just assume that thing will turn out differently this time around. Would you be comfortable if your boss asked you to work toward ethically suspect activities? Rather than worrying about it if it happens, make sure that your organization has rules in place now to ensure that such a situation can’t happen in the future. There will always exist amoral bureaucratic entrepreneurs pushing us toward an evil equilibrium, but we can do a lot to lower the probability that they will succeed. The game is not different. All of the ingredients of the situation of Germany or the USA in the 1940s are around today: we have bureaucracies, different races and countries, a government, and people. I’m not proclaiming that the sky is falling, and am not predicting genocides. But conversely, many people look at the horrors of the past and see them as something which was committed by monsters who are incomparable to the noble souls who populate the world now. But it was subtle, and if it happens again, it will be subtle again. Some arbitrary sequence of events could push us toward an evil equilibrium just like before, and there are no new safeguards in place. The only difference between now and then is that we have the experience of history, marking red flags along the way. To see those flags and do nothing about them would be, well, evil. [About the author: I wrote this essay on an IBM Thinkpad–one of eight I have owned (mostly Thinkpad 560s and Thinkpad 570s). I recently refused a job interview solicited by a contractor for the Department of Homeland Security.]

1.15

Your genetic data 7 June 2007

[Or, The ethical implications of SQL.] Our paper on the genetic causes of bipolar disorder finally came out last week. The lead author has repeatedly said things like ‘we really couldn’t have done it without you,’ though, to tell ya the truth, I have only a limited grasp of the paper’s results, and have been unable to read it through, due to my lack of background in the world of genetics and biology in general. Fortunately, there have been press releases and a few articles to explain my paper to me. The figure explains how this is all possible. It is what a genetics lab looks like. That’s a work bench, like the ones upon which thousands of pipettes have squirted millions of liters of fluid in the past. But you can see that it is now taken up by a big blue box, which hooks up to a PC. Some of these big boxes use a parallel port

1.15. YOUR GENETIC DATA

43

Figure 1.3: The tools of the data processing field known as Biology

(like an old printer) and some run via USB (like your ventilator or toothbrush). The researcher puts processed genetic material in on the side facing you in the photo, onto a tray that was clearly a CD-ROM drive in a past life. Then the internal LASER scans the material and outputs about half a million genetic markers to a plain text file on the PC. I know I’m not the first to point this out, but the study of human health is increasingly a data processing problem. My complete ignorance regarding all things biological wasn’t an issue, as long as I knew how to read a text file into a database and run statistical tests therefrom. Implication one: Research methods We are in the midst of a jump in how research is done. Historically, the problem has been to find enough data to say something. One guy had to sail to the Galapagos Islands, others used to wait for somebody to die so they could do dissections, and endless clinical researchers today post ads on bulletin boards offering a few bucks if you’ll swallow the blue pill. But now we have exactly the opposite problem: I’ve got 18 million data points, and the research consists of paring that down to one confident statement. In a decade or so, we went from grasping at straws to having a haystack to sift through. As I understand it, the technology is not quite there yet. There’s a specific protocol for drawing blood that every nurse practitioner knows by heart, and another protocol for breaking that blood down to every little subpart. We have protocols for gathering genetic data, but don’t yet have reliable and standardized schemes for

44


extracting information from it. When we do have such a protocol—and it’s plausible that we soon will—that’s when the party starts. Implication two: Pathways If you remember as much high school biology as I do, then you know that a gene is translated in human cells into a set of proteins that then go off and do some specific something (sometimes several specific somethings). So if you know that a certain gene is linked to a certain disorder, then you know that there is an entire pathway linked to that disorder, and you now have several points where you could potentially break the chain. [Or at least, that’s how it’d work in theory. Again, there’s no set protocol.] There are many ways to discover the mechanism of a disorder, but the genetic root is the big fat hint that can make it all come together right quick. Then the drug companies go off and develop a chemical that breaks that chain, and perhaps make a few million per year in the process. Implication three: Free will versus determinism One person I talked to about the search for genetic causes thought it was all a conspiracy. If there’s a genetic cause for mental illness, then that means that it’s not the sufferer’s fault or responsibility. Instead of striving to improve themselves, they should just take a drug. And so, these genetic studies are elaborate drug-company advertising. From my casual experience talking to folks about it, I find that this sort of attitude is especially common regarding psychological disorders. See, every organ in the human body is susceptible to misfiring and defects—except the brain, which is created in the image of ’’, and is always perfect. Annoyed sarcasm aside, psychological disorders are hard to diagnose, and there’s a history of truly appalling abuse, such as lobotomies for ill behavior, giving women hysterectomies to cure their hysteria, the sort of stories that made One Flew over the Cuckoo’s Nest plausible, &c. Further, there are often people who have no physiological defect in their brains, but still suffer depression or other mood disorders. They get some sun, do some yoga, and everything works out for them. But none of that means that the brain can not have defects, and that those defects can not be treated. The problem is that our ability to diagnose is falling behind our ability to cure. We know that certain depressives respond positively to lithium carbonate, Prozac, Lexapro, Wellbutrin, Ritalin, Synthroid, and I don’t know today’s chemical of the month. But we still don’t have a system to determine which are the need-of-drugs


45

depressives and which are the get-some-sun depressives. Or to give a physical example, we don’t know which obese individuals have problems because of genetic barriers and which just need to eat less and exercise. It’s only harder because, like the brain, the metabolism is an adaptive system that can be conditioned for the better or for the worse, confounding diagnosis. Frequently, it’s both behavior and genetics, albeit sometimes 90% behavior and sometimes 90% genes. A genetic cause provides genetic tests. If we have a drug based on a genetic pathway, as opposed to a drug like Prozac that just seemed to perk people up, we can look for the presence or absence of that genetic configuration in a given individual. This ain’t a silver bullet that will sort people perfectly (if that’s possible at all), but having a partial test corresponding to each treatment is already well beyond the DSM checklists we’re stuck with now. Implication four: Eugenics We can test for genetics not only among adults and children, but even fetuses. On one small survey, five out of 76 British ethics committee members (6.6%) “thought that screening for red hair and freckles (with a view to termination) was acceptable.”15 Fœtal gene screens to determine Down syndrome or other life-changing conditions are common, and 92% of fetuses that return positive for the test for Down Syndrome are aborted [Mansfield et al.]. Biology has an embarrassing past in eugenics. And we’re not just talking about the Nazis—the USA has a proud history of eugenics to go along with its proud history of hating immigrants (I mean recent immigrants, not the ones from fifty years ago, who are all swell). [My above-mentioned lead author refers me to this article on eugenics16 , and having read it I too recommend the first 80%.]

If I may resort to a dictionary definition, the OED tells us that eugenics is the science “pertaining or adapted to the production of fine offspring, esp. in the human race.” In the past, that meant killing parents who turned out badly in life or had big noses, but hi-tech now allows us to go straight to getting rid of the offspring before anybody has put in too heavy an investment. Anyway, I won’t go further with this, but to point out that what we’ll do with all this fœtal genetic info is an open question—and a loaded one, since the only choices with a fœtus are basically carry to term or abort. The consensus seems to be that aborting due to Down syndrome is OK and aborting due to red hair is not, but there’s a whole range in between. If you know your child has a nearcertain chance of getting Alzheimer’s 80 years after birth, would you abort? [This 15 16

http://adc.bmj.com/cgi/content/full/88/7/607 http://www.logosjournal.com/issue_6.1-2/jacobsen.htm

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Congressional testimony17 approximately asks this question.]

Implication five: the ethics of information aggregation This is also well-trodden turf, so I’ll be brief: • It is annoying and stupid that every time you show up at the doctor’s office, the full-time paperwork person hands you a clipboard with eight papers, each of which asks your name, full address, and Social Security Number. By the seventh page, I sometimes write my address as “See previous pp” but they don’t take kindly to that, because each page goes in a different filing cabinet. You may recall Sebadoh’s song on data and database management: “You can never be too pure/ or too connected.” If all of your information is in one place, either on your magical RF-enabled telephone or somewhere in the amorphousness of the web, then that’s less time everybody wastes filling in papers and then refilling them in when the bureaucrat mis-keys everything. I have a FOAF whose immigration paperwork was delayed for a week or two because somebody spelled her name wrong on a form. • Having all of your information in one place makes it easier for people to violate your privacy and security. As advertisers put it, it makes it easier to offer you goods and services better attuned to your lifestyle, which is the nice way of saying ‘violate your privacy’. It means more things they can do to you on routine traffic stops. The data consolidation=efficiency side is directly opposed to the data disaggregation=privacy side. There is no solution to this one, and both sides have their arguments. A prior entry discussed how information aggregation can lead to disaster18 , but we should bear in mind that the same technology discussed there made the innocuous and essential U.S. Census possible. The current compromise is to consolidate more and put more locks on the data, but that doesn’t work very well in practice, as one breach anywhere can ruin the privacy side of the system. Back to genetics, when we have a few more snips of information about what all those genes do, your genetic info will certainly be in your medical records. This is a good thing because it means that those who need to will be able to diagnose you more quickly and efficiently; it is a bad thing because those who don’t need to know may also find a way to find out personal information about you. At the moment, you can rely on the anonymity of being a needle in a haystack, the way that some people who live at the top of high rise buildings are comfortable walking around naked and with the curtains open—who’s gonna bother to look? But as the tools and filters and databases become more sophisticated, the haystack 17 18

http://www.hhs.gov/asl/testify/t960917c.html http://fluff.info/blog/arch/00000199.htm


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may provide less and less cover. So we’re going to have a haystack of data about you (and your fœtus) right soon. Unfortunately, we don’t quite yet know how to analyze, protect, or act on that haystack. I guess we’ll work it out eventually.

2 H OW TO ARGUE WITH A CONSERVATIVE

Here are a few notes on what I feel are the best arguments to use when debating with a conservative. It covers that narrow slice of argumentation that is both a valid counterargument to the average conservative’s claims and is also comprehensible to a conservative. There are a multitude of other means of debate, but I feel that those discussed here are the most likely to succeed. I self-identify as an economist, meaning that most of the discussion here will be economic [even including a few technical notes from basic economic theory in square brackets]. For the social issues, however, have a look at Section As a final caveat, no two conservatives are the same, and it would be overblown to the point of silliness to claim that a 6,000 word essay covers everything every conservative believes. Having said that, I will spend the rest of the paper debating the imaginary conservative in my head and pretending he represents all conservatives, without plastering the essay with little ‘some conservatives believe that. . . ’ warnings. Uncle Milt It all began in the fifties or so, with a Mr. Milton Friedman, herein ‘Uncle Milt’, which is what U of Chicago professors really called him when I was a student there. Uncle Milt wrote this little book called Free to Choose, and the name basically describes everything there is to know about the theory. If you have to choose among a few options, an unconstrained choice is always better than a constrained choice. It’s almost a tautology. Therefore, government restrictions on the choices available to people, be they consumers or managers of businesses, are bad. [This is often called the Neoclassical school, since it’s a reinvention of Adam Smith’s work. You know Adam Smith: he wrote A Theory of Moral Sentiment, which explained how a market requires good will among its members in order to properly function. He also wrote something about an invisible hand moving the market to an optimal state.] Free to Choose is basically the Republican position on all economic (but not 48

2.1. EXTERNALITIES

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social) issues. It’s appealing because it’s so simple: restrictions bad. But economics since the dominance of Uncle Milt and the Chicago School has been all about the exceptional situations where the simple logic of constrained vs unconstrained choice is too oversimplified to do reality justice. Generally, regarding any issue where we in the modern day consider government to be potentially relevant, one of these exceptional cases will come up. Pointing out the appropriate exception is often enough to get a free marketeer to stop smirking.

2.1

Externalities

The biggest problem with the neoclassical view espoused by so many conservatives is that it forgets about externalities. This is huge. An externality is the effect you have on others that doesn’t directly affect you. When you drive, every pedestrian has a little more trouble breathing. When you eat a hamburger, a cow had to be killed. When you wear a low-cut dress, the boys who pass you on the street feel a little bit better. [I swear, every econ class I’ve ever had used an example about cute girls.] From the economist side of things, there is no real solution to the externality problem, in the sense that it’s supremely difficult to work out what the optimal behavior is, and how you should go about getting people to engage in that behavior. Basically, if an agent can do something that benefits it but causes a negative externality on others, then you’re guaranteed that the agent will do too much (a suboptimal amount) of that activity. If we could find a way to have people internalize their externalities, so that they simultaneously feel both the benefit they experience and the displeasure that others experience, then the market mechanism would work just fine. Too bad that’s impossible. Which is where government comes in. As a first approximation, there are taxes on activities which produce negative externalities: gas consumption pollutes, and so is taxed; alcohol consumption leads to some number of annoying drunkards, and so is taxed; cigarette consumption makes other people’s clothes stink and leads to a rise in public health expenditures.1 All of these taxes proxy for the displeasure that the buyer is causing everybody else. Barring a tax, the other means of internalizing the externality is making the activity illegal—think of the fine from breaking the law as another form of tax. A 1

Taxes don’t have a will, so ascribing a motivation to a tax is a fallacy, but notice how far we can go in justifying these taxes without describing any of them as ‘sin taxes’. After all, if taxes really were a puritanical attempt to change people’s behavior, the puritans would also be taxing condoms— but the externalities from condom usage are all positive, so you’ll only find no taxes or occasional subsidies on them.

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CHAPTER 2. HOW TO ARGUE WITH A CONSERVATIVE

good law curtails those activities which have negative externalities and thus makes the world a better place. Examples: don’t litter because it’s easy for you but makes other people’s lives worse; don’t drive drunk because it’s easy for you but makes other people’s lives worse; you can’t buy a car with certain types of dirty engine because it’s cheap for you but makes other people’s lives worse, et cetera. The problem comes in when working out how much curtailing to do. When people say that their lives are worse off because of somebody’s actions, they have absolutely no incentive to tone down the whining. I think you’ve all been there— especially if you’ve ever had a roommate. Back when I was a bike messenger, my roommate borrowed my bike for a stroll along the lakeshore, and got a flat tire. He didn’t quite patch it right, and it went flat a few more times over the course of the day. I lost work as a result, and by the time I got home, I had prepared an extensive bitchy commentary for him about how his actions had ruined my life. Yet he started yelling first, about how I’d left a nubbin of pasta at the bottom of a pot, and now it was really stuck, and how I had thus totally ruined his life. He made it very clear that losing business, patching an expanding hole, and walking part of the way home was nothing compared to what he’d suffered at the hands of that blob of pasta. It wasn’t the best roommate situation, but it mirrors legislative lobbying and debate pretty well. Imagine the whining when the problem is bigger than pasta stuck to the pot, like an issue of education and property taxes, or pollution. It basically becomes guesswork as to what damage one person suffers from somebody else’s actions. The conservatives of the world often latch on to this, and conclude that everybody is just lying all the time, and there really are no externalities, or if there are, they aren’t nearly as bad as everybody makes them out to be, so we should ignore them. ‘Buck up and stop whining,’ the conservative would politely explain. Anyway, behind a huge number of government activity and restrictions upon behavior, there is an externality involved. It’s a fun exercise to ask yourself, for any law that comes to mind, what harmful externalities that law is preventing; you’ll find something for almost all of ‘em. For example, laws curtailing pollution exist because pollution damages property which is either in the public trust or is intimately the property of a non-polluter (like the air in my lungs). When people don’t get an education, studies show, they’re more likely to wind up poor, annoying, and a criminal, which are all things that affect the other people that interact with the uneducated. On the positive side: when you take public transportation instead of driving, other people have clearer roads and lungs. When people tell you that government should get out of these fields and the market will provide the optimal levels of pollution, education, and public transport, tell them that they’re entirely wrong, because the market can not accommodate the effects of the externalities.

2.1. EXTERNALITIES

51

Also, when the privatization people tell you that the bus system is losing money, and therefore needs to be severely cut and/or privatized, you should tell that that because of the externalities, the system isn’t behaving optimally unless it is losing money. See also the section on cost minimization below. Law is often a blunt instrument, so if the optimal amount of an activity is less than current, the law often simply makes it entirely illegal. But the optimum is probably not at zero activity either. People often latch on to this, pointing to cases where somebody really needed to do something which had a negative externality attached, and couldn’t do it because of some law. But the question of degree is more subtle than that: zero is not optimal, but neither is the amount you’d get if everyone were free to do all they wanted; which is less suboptimal?

2.1.1

The choice of externalities

Both sides of the political fence complain about externalities, but different ones. For example, social conservatives have lately taken to griping about how their marriages will be less sanctimonious or something if gay marriages are allowed. Externality arguments are usually made by social conservatives and economic liberals. Conversely, social liberals and economic conservatives (both of these categories include libertarians) tend to ignore or belittle externalities. The asymmetry here is that economic externalities, which the liberals gripe about and the conservatives ignore, are about the things that actually affect people’s lives; the social externalities, which the conservatives are up in arms about, are typically aesthetic. In an ideal world, you could call a conservative on the relative triviality of the externalities s/he chooses to care about. E.g., why are you bothered about how your kids are harmed by gays, but aren’t bothered by how many kids are killed by guns every year? Why do you think the market should be free to decide on whether to drill for oil in Alaska, but don’t think the market can work out the optimal exposure of boobies on TV without government oversight? Another asymmetry is the exaggeration issue: when people suffer externalities such as job loss, crime, disease or death (or even environmental damage), there’s something physical that can be measured and compared to any hypothetical benefits, albeit imperfectly. But when somebody says that they suffer because gays are getting married or because they were subjected to the sight of female nipples, there is simply no way to measure the aesthetic damage that the person is internally suffering. I’m not exactly sure how you can use this for rebutting a fanatic conservative, but it gives some idea of how fanaticism can come about: there’s nothing keeping anyone from the extreme position, because there are never facts that get in the way of the claims of endless damage.

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2.1.2

How not to argue: equality and fairness arguments

Here are some things which are generally true and often important, but which are simply non-starters in debate with conservatives. They’ll never get it, so don’t waste your time trying. In some ways, this is the most important section. A bad argument is worse than no argument at all, and I’ve often been vicariously embarrassed by fellow liberals (Ralph Nader) who argue the points below as if they’re persuasive. Equality is, to many conservatives, just not important. There’s nothing much in the Bible about it, and humankind got along just fine without it for centuries and centuries. Similarly, many conservatives define fairness endogenously, so any outcome is always tautologically fair: if you can grab more for yourself, then you deserve more and that’s fair. A desire for fairness requires internalizing all externalities, which many people either have trouble doing or explicitly don’t want to do. As such, I don’t think there’s any way to convince somebody that equality in treatment or outcomes is a good thing. So don’t argue that a certain rule or structure is fair; instead, consider the ways that it appeals to the principles that our conservative pals find appealing, like efficiency (everybody likes efficiency) or pro-U.S. nationalism. For example, redistributive taxation. By keeping the poorer folks fed, the likelihood of crime is lower, and kids are better fed and are more likely to be healthy and smarter and more productive in the future. You could provide certain goods/services via inefficient social services, or via the market by undertaxing the poor who are most likely to use those social services. You can get pretty far without ever using the word ‘fairness’. To give another example, the Unified School Districts of various areas insist that all schools in a wide area (like LA) must get the same level of funding. Again, this improves efficiency: another dollar to a school which needs to buy textbooks will go a lot further than a dollar to a school which wants to fund one more field trip.2 And why is it so easy to talk about optimality when we want to talk about fairness? Because fairness is optimal. Another dollar given to a wealthier person just isn’t as useful as another dollar given to a starving person, so all else equal, the best allocation of a given dollar is to the starving guy. [Technical version: Although not universally true, people are generally risk averse, meaning that we can describe their preferences using a concave utility function. If everybody has equal weight in our objective function and has the same private utility function, then the optimal 2

So why do LA’s schools suck so badly? Because property taxes in California are so low that they’re effectively nil, so every school in LA is equally underfunded. It’s a paragon of where the conservative drive for lower taxes at all costs will get you: the fastest drop in school quality you’ve ever seen.

2.2. PUBLIC GOODS

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allocation is the perfectly equitable one.] To summarize the section, fairness is an idea you learn as a kid, and if somebody doesn’t get it by now, they never will. But you can argue for efficiency almost anywhere you’d prefer to discuss fairness, and you won’t have to ask the person you’re debating to make the mental leap of internalizing the situation of other people. The more hard-core libertarians take it all a step further, though, and believe that not only is the empathetic desire for fairness a weakness (as Ayn Rand teaches), but the world would be better off if we all went out of our way to eliminate empathy (i.e., the internalization of externalities, which are assumed away in the free market model). By this point, it becomes a religious issue (sometimes literally), so debating is useless; cut your losses and just don’t bother associating with the person.

2.2

Public goods

Another common divide along the liberal-conservative spectrum is that liberals want more goods provided by government and conservatives want fewer goods.

2.2.1

The fallacy of the self-made conservative

Many a conservative shoots for an individualistic character. Some take it to the extreme of insisting that they are entirely self-made: their family did all the work of raising them and sending them to a private school, then they paid for college themselves, never took a handout, et cetera. They conclude from these broad strokes that government was unnecessary in getting them to where they are today. Other conservatives don’t go this far, but are still willfully blind to their reliance on public goods. Direct benefits Part of the problem is that the government services that most people enjoy are so fundamental that they’re invisible. If the water is clean, and you don’t get sick when you go out to eat, and the gas lines under the street don’t erupt in flames too often, then you don’t notice the inspectors, engineers, and bureaucrats on the government payroll who made such a halcyon existence possible. The best government is one which is involved in dozens of fields and yet is entirely unnoticeable. Indirect benefits Leaving aside the person’s health and general well-being, there are also indirect benefits to government spending which our conservative friends

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enjoyed, whether by their choosing or not. They worked through school? There’s a good chance that they were able to find a job because the federal Work Study program provides subsidies to make sure that every campus has a larger supply of jobs. Even if our conservative friend eschewed such handouts, the non-handout jobs had much less competition. Our Conservative Hero doesn’t have any diseases, and is healthy and fit thanks to 100% private health insurance? It’s also because of massive public health campaigns, both direct (closing sewers and other basics that the U.S.A. worked out a century ago) and indirect, in the form of taking care of the impoverished ill and advising them on how to get better so they don’t cough up an infected lung on any conservatives. Our Conservative Hero isn’t mugged every day? This is partly thanks to the fact that the poor in the neighboring communities have government support that lowers their need to get resources by illicit means. The list goes on, but the gist is the same: by stabilizing and taking care of those parts of our surroundings that are most at risk, those parts stay invisible to those who can take care of themselves. But if those supports disappeared, then the at-risk may not remain so invisible.

2.2.2

Limited rationality and informational asymmetry

This is a bit of a digression, but it’s a good place to mention regulations requiring labeling, full disclosure, and licensing. Trademark laws are all about minimizing confusion in the marketplace: if your logo looks too much like the other guy’s logo, then dumb people will get confused and buy the wrong thing. There are loads of other truth-in-advertising laws, such as how stock brokers can not guarantee that a plan will make money. And indeed, there are enough dumb people and enough slimy stock brokers that laws like this have to exist. In LA county (among others), all restaurants are inspected and must post signs giving their inspection grade. Similarly, food manufacturers have to tell you basic nutritional info and what’s in their food. Publicly traded companies have immense reporting requirements, which keep many a lawyer and accountant employed full time. Generally, any sort of licensing requirement is a requirement for full disclosure of important information. All this seems fair enough to me: trade on equal grounds requires equal information. And yet, there are loads of conservatives (not all, but a few) who think these are invasive laws that condescend to the buyer. The emptor should caveat for his or her own darn self. Again, all of these rules are based on hope for a ‘fair market’, which differs from the concept of a ‘free market’. As above, you can’t

2.2. PUBLIC GOODS

55

argue fairness to a conservative who doesn’t already believe it’s worth striving for. Part of this is the Lake Woebegone effect, that everybody thinks ‘I’m smarter than average, so this law isn’t protecting me; it’s protecting the dumb people whom I don’t know.’ From my own experience, self-made conservatives are especially prone to this, which makes any argument about how information is not perfectly disseminated at all times supremely frustrating. I think your best bet is to either argue the extreme cases [should out-and-out scams be legal? When does hiding information become substantively different from lying?] or use the grandmother argument [Would you want your grandma to have to sift through this?]3 However, my experience is that the Lake Woebegone effect combined with a refusal or inability to internalize the difficulties of others makes this class of issues almost impossible to debate. The self-made conservative believes that he (and it is usually a boy) can fend for himself, so everyone else is obliged to as well. But the self-fending is a delusion, because he is already surrounded by a wealth of services which he directly and indirectly benefits. He doesn’t get lied to not because he’s so supremely savvy, but (at least in part) because those he deals with have laws they must comply with. The question, then, is how these services which the self-made conservative takes for granted should be provided, and the conservative always prefers private provision over public.

2.2.3

The fallacy that a profit motive means efficiency

Conservatives often work from the premise that if an organization has no profit motive, then it will be inefficient. A business has a simple directive—maximize sales minus costs—and a business which fails in that directive will lose out to other businesses which do a better job of it. This logic is false in two ways. Cost minimization The first part of the argument, that an organization which isn’t maximizing profits has no motivation to be efficient, is simply false. The reason is that profit maximization is equivalent to cost minimization. We could cast the problem of the business as finding the cheapest way of producing its product; similarly, we could characterize the goal of the bureaucracy’s manager as finding the cheapest way to achieve whatever its goals may be. If the manager isn’t minimizing costs, then there’s something s/he could do to save a few bucks and then apply that toward achieving the bureau’s goals. Why would the manager of a government department pass up such a savings, while a business manager wouldn’t? 3 I don’t know why grandparents are always considered to be so dumb, but this debate is probably not the time to work on dispelling stereotypes.

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Of course, there’s still the problem of defining the goals of the organization, and here government excels in the provision of things where the goal is ambiguous. The goal of a public energy utility is to provide citizens with reliable and cheap power, while the goal of a private company is to maximize profit for the owners of the company by providing citizens with power. It’d be nice if these incentives aligned perfectly, but they clearly don’t, which means that privatization often leads to disasters in the provision of public goods (e.g., everything associated with Enron). Externalities matter here too: the profit-maximizing fee schedule ignores externalities, and will therefore lead to a suboptimal level of service. This may seem easy and obvious, but the privatization harpies forget all the time, and need reminding: profit maximization and cost minimization both encourage efficiency, and neither magically produces efficiency. Zero profits The second part of the fallacy, the Darwinian part, assumes that if you’re not perfectly optimal, you’ll lose money and will go out of business. But anyone who has ever worked in a company’s office will attest that abject, persistent inefficiencies happen every day throughout the business world, and yet these companies continue to keep their heads above water. Liberals and conservatives alike agree that ‘big government’ in the sense of ‘over-bureaucratic’ government is a bad thing, and if there’s a more efficient way to achieve existing goals, then that’s a good thing. But the same could be said of IBM. Some folks used to tell me that zero-profits-plus-efficient-market means that racist hiring would eventually disappear, since a racist manager is imposing a restriction on his choices, which will therefore lead to suboptimal hiring on a regular basis, which will lead the company to go out of business. Maybe racist businesses go under more frequently than non-racist businesses, but a few centuries have shown us that no, having racist policies does not immediately condemn a company to bankruptcy. Similarly with any of a number of other mean, irrational, and destructive policies that the businesses of today engage in all the time. Conversely, laws that force people to not be racist also don’t lead to businesses closing down all over. Theoretical economists assume that all businesses are on the verge of bankruptcy at all times because they always assume that firms are all competing to produce widgets that are exactly alike in every way—and there are often an infinite number of firms. But the assumption of zero profits really doesn’t work in real life, as you can see by the fact that businesses exist, and this means that any reasonably healthy business can afford to operate in a manner that society deems acceptable, and can conform with laws about accounting, treatment of workers, or environmental care.

2.3. MONOPOLIES AND MARKET POWER

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Yet when a new regulation is put in place, the chorus of capitalists all shout out in unison, ‘I’m barely making ends meet and will go out of business.’ Sometimes the response is a bit more moderate: ‘I’ll have to lay a few people off and reduce production,’ or ‘If you pass regulations that I don’t like, I’ll just take my ball home and pout.’ After all, they’re right on the verge of bankruptcy, so any new costs will put them under. The reality of the situation is much more complicated. For example, New Jersey raised its minimum wage one year, while Pennsylvania didn’t. Card, Katz, and Krueger took this to be as good a natural experiment as you’ll ever get in the social sciences: the economies are closely linked, the passage of the new law was quick and sort of a surprise, and C, K & K managed to get a good picture of fast food joints on both sides before and after the law took effect. The end result: there were more jobs created in New Jersey after the law was passed than in Pennsylvania. It wasn’t much (and I don’t recall if it was statistically significant), but it was definitely not a loss of jobs [Card and Krueger, 1997].4 Why were there more jobs in NJ? Maybe people spent all their new minimum wage earnings on fast food, or maybe more people entered the labor market, or maybe all those truckers carting in goods which used to be produced in NJ factories needed a place to eat. Regardless, the moral is that a new rule can often change all sorts of things in the economy, some good some bad, so reducing it to a simplistic one-liner like ‘a higher minimum wage means less jobs’ is stating a falsehood. [For the theorists, here’s the moral: never trust a partial equilibrium model.] Regulations can be burdensome and annoying, just like not being able to pee in the street is often burdensome and annoying, but somehow, we all manage it. However, not all burdensome regulations are destructive regulations, and if a conservative forgets that there’s a distinction, be sure to remind him/her/it.

2.3

Monopolies and market power

With monopolies, two mantras of conservative economics collide. One says ‘competitive markets are good’ and the other says ‘government intervention is bad’. So what do you do when the only way to have a competitive market is through government intervention? One of the main money-makers for the working economist are anti-trust proceedings, in which one set of well-paid economists proves that a merger will allow 4

CK & K’s arch-nemeses, Neumark & Wascher, wrote a reply in which they got another data set for the NJ/Pennsylvania experiment, from the NRA—the National Restaurant Association. Their data set conclusively found that the passage of the minimum wage law caused New Jersey to fall into the ocean. C K & K asked to see the data so they could verify the results, and N & W refused, citing a non-disclosure agreement with the NRA.

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a company to ‘unfairly’ use its expanded market share, while another set of wellpaid economist proves that this won’t happen. Many a conservative I have met believes that this is all silly, and that if a monopolist can find a price at which people will buy their goods, then the monopolist is clearly still providing something valuable, so why is the government being all pissy about it? Leave the companies to merge to their hearts’ content. More generally, the idea of a monopoly gets to the concept of market power: the ability of a single player in the market to influence the market itself. Most of neoclassical economics assumes that every agent has zero market power, and is thus a price taker—they can’t influence prices at all, just take them from the market. First, there aren’t any theorems about the optimality and welfare-maximizing properties of monopolists (that I know of). If the company can set prices, instead of just take them, then all the Econ 101 proofs about optimality [not including Pareto optimality, which is not really optimality in any human sense] are out the window. You can have a government that doesn’t try to prevent monopolies, but then all the arguments about the virtues and automatic optimality of the market are thrown out of the debate. For example, say that there are only two or three media conglomerates, who offer cheap television, radio, and print to every person in the world. Since there are only a few, a documentary producer who wants his or her work to be seen has to get one or two of these conglomerates to distribute the documentary. If all three offer the producer too little money for the film, since they know the producer will have no one to make a lower bid, then the documentary will never be seen. With more competition among the buyers and distributors of media, there would be more variety in public debate, and content providers would make more money, instead of having to accept whatever sum the distributors see fit to offer. In short, the quantity and variety of content is larger in a competitive market than in a monopsonistic one. Another example of the sorts of problems market power produces: products often interoperate with other products, meaning that a company which is doing wonderful market-pleasing things in one field can exert its power to sell crappy goods in another market where it’s not necessarily the best. I am thinking, of course, of Microsoft. The company, at this point, is built entirely on the concept of lock-in, and spends most of its marketing budget trying to convince consumers of two things: you should upgrade your existing Microsoft product, and you shouldn’t switch to something else. Not much in the way of innovation going on here. This is not the place to go into the computer geek details, but there are a wealth of alternatives to the desktop-with-word-processor paradigm we all work in now. Sun Microsystems, for example, had the idea of letting users run their word pro-


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cessor via their web browser. But for this to work, everyone needed a web browser that would be technically compatible with such a setup. When it was being investigated for monopolistic practices, Microsoft’s argument to the Justice department was that anti-monopoly regulations hinder their ability to innovate by making incremental improvements and additions to Windows. But at the same time, Microsoft used its market power to ensure that innovation in the form of fundamental paradigm shifts wouldn’t happen. So what can you tell your conservative pals? That incremental innovation isn’t necessarily a problem when there are monopolists involved, but innovation on a larger scale are blocked when there are monopolists who can use their influence on standards and the basic operation of the market to prevent that innovation. With a few players, the market is no longer a clean, optimal environment, but a tangled mess where customers are not free to choose (outside of the ‘my way or the highway’ option) and those with market power can use that lack of choice to their advantage. Employers as monopsonists Large companies are clearly not price takers, and conservatives frequently need to be reminded of this. For example, Wal Mart negotiates the price it pays on most (maybe all) of the items it sells. There is one Wal Mart, and dozens of pretzel vendors, so Wal Mart can use this asymmetry to negotiate down the price it pays for pretzels. The most important price for Wal Mart it the price of labor, and the market is again clearly asymmetric: one Wal Mart, and millions of potential employees. Setting a price is a negotiation over how surplus should be divided. If an hour of work is worth $6 to Wal-Mart, and a person is willing to work for $4, then any wage between the two would work, in the sense that the person would work the hour and Wal Mart would pay the person and both would walk away better off. Uncle Milt stops here, content in the belief that even if Wal Mart stands firm at $4.01, the employee is still better off. The main problem with this is that the lowest wage a person will accept depends on the conditions. Notably, because of what I will call the ‘food constraint’, any job is better than no job at all. Our conservative pals forget the food constraint all the time, since it’s hard to work in to a simple model of agents [discontinuity and/or nondifferentiable kink in the utility function at zero], and it’s easy to forget that ‘agents’ means ‘people’. Also, the wage Wal Mart sets is interdependent with any of a number of other things, such as the wage the company next door sets. In the theory, there’s a menu of wages available, so if you don’t like Wal Mart’s wage, you go next door to Sam’s Club and take the wage they offer. But if Wal Mart and Sam’s Club set their wages

60


in concert, and Sears and K-Mart follow Wal Mart’s lead in price-setting, then the model falls apart again, because it is impossible for people to negotiate the price of their labor by threatening to go next door. This is not necessarily overt collusion; it is simply the ease with which a small group of actors can imitate each other and wind up at a very stable equilibrium. The minimum wage, ironically, helps immensely with this by providing a focal point for all employers to set their wages against. The solution to the asymmetry of the market, by the way, is unionization. One Wal Mart and one worker’s union is a symmetric market, which has some hope of working as it should. Conservatives often miss this, and only see that the union is a restriction on the behavior of its workers and the employer. [See p

2.3.1

How not to argue with conservatives: corporate conspiracies

Many liberals argue from the basic premise that small businesses are better than large corporations, and that companies which are big enough to be international are especially bad. The issue needs to be disaggregated into parts which can and can’t be argued with a conservative: Personalization and diversity Just as conservatives like smaller government which is more representative of the people, we want smaller businesses which don’t force corporate HQ’s worldview on its patrons. But conservatives will dismiss this by saying ‘if they don’t like the bigger store, they’ll shop at the smaller, spunkier store next door’ and will dismiss any further debate on this point. In other words, the cultural issue is a total non-starter. Market imperfections As above, there is a natural asymmetry between labor and capital (many workers, few employers), and this distorts the market in favor of the few, the monopsonists. As corporations grow and consolidate, the problem only gets worse. Some conservatives get this, and will acknowledge that reduced competition is bad. The more libertarian conservatives will abjectly refuse to accept this, and will cling to the idea that a firm that abuses its market power will be deposed by a spunky startup. The Spunky Startup argument is impossible to argue with, kind of like the ‘tomorrow will be sunnier’ argument: there are enough examples where it’s been true that people can say it with a straight face and be happy ignoring the fact that there are so many cases where it was entirely not true. On the perfectly level imaginary playing field, the spunky startup can definitely win—but in the real world, the profit-per-unit only goes up as a company gets larger, network effects and lockin make people more likely to buy the old thing instead of the new, and if all


61

else fails, the big and lumbering corporation can keep serving Spunky the Startup with lawsuits for trespassing on Lumbering Corporation’s intellectual property until Spunky’s supply of optimism is entirely depleted. To summarize, your best replies to arguments about Spunky the Startup are about the market imperfections discussed above, most of which help companies which survived at the start keep new competition out of play. But my personal experience is that it’s an uphill battle, and an irrational faith in Spunky the Startup’s abilities is hard to dispel. Competition with sovereigns A company which exists in multiple states will be able to find the state with the least restrictive laws and register there. When ‘state’ means portion of the U.S.A., this is Delaware; when ‘state’ means sovereign nation, this is any of a number of islands in the Caribbean. Whether this is a problem to the conservative you have before you depends on how much contempt the conservative has for the concept of a government. Some enthuse at the idea of a lawless world; others are a bit concerned by the prospect. As with any issue involving sovereigns, there are enough thorny philosophical issues that you have no chance of selling somebody if they disagree with you. But if you find that they do believe some laws are worth having, then take advantage of that and ask how that law is going to be maintained in a world where corporations get to pick the set of laws they are beholden to. In short, be sure to focus on the specific things that large firms can do that small firms can’t. ‘Bullying’ is too vague—stick with the specific mechanisms by which firms with market power can unfairly use that power. There are abundant options to choose from.

3 P EOPLE AND THEIR PATTERNS

3.1

Measuring attractiveness 12 May 2004

Ms AMJ of Richmond, VA, asked me, her personal economist, for a lit review of academic studies of attractiveness. So, Ms AMJ and whoever else may be around, I offer you this haphazard and arbitrary romp through the literature on beauty and its correlation to symmetry, BMI, WHR, VHR, and 2D:4D.

Innate attractiveness We’ll start with the infant studies, which try to get around the culture/innateness thing by using subjects too young to comprehend culture. Maurer and Barrera [1981] showed the images depicted in Figure ?? in front of 1- to 2-month old kids. For those using text browsers: one image has features arranged as a proper face, and on the others, the features are either random or symmetric but not a face. They found that the two month olds fixate more on the face than the others but the one month olds don’t, implying that face recognition comes in somewhere during that time. So some quantity of our processing of people’s faces comes either from hard-wiring or stimuli well before the kid can comprehend culture. [The sample is smaller than I’m comfortable with, 20 1-month and 15 2-months, but I guess these are a pain to conduct: “An additional six babies did not complete the experiment because they cried (N=3) or fell asleep (N=3).”] So it would not be a great leap to presume that beyond the basic shape of the face, there are other things that are hard-wired into the brain, but it’s not entirely obvious as to how fine-grained that hard-wiring is. For example, how about symmetry? The study above didn’t find much difference between the symmetric and the asymmetric non-faces, but those weren’t faces. Samuels et al. [1994] showed babies symmetric faces and attractive faces, and found that the babies paid more attention to the more attractive faces than the more symmetric. Noor and Evans [2003] found that perfectly symmetric faces were judged (by adults) to be more 62

3.1. MEASURING ATTRACTIVENESS

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Figure 3.1: Am I hot or not?

Neurotic, less Agreeable and less Conscientious than normal faces, but not more or less attractive. But there’s not just symmetry: there are hundreds of ways in which we can collate and dissect women’s faces and bodies. The standard, gleaned from back issues of Playboy, is that a .68 waist-to-hip ratio (WHR) is the ideal shape for a bunny. Katzmarzyk and Davis [2001] report this figure, and that “there has been no appreciable change in either BMI [body mass index] or WHR in centerfolds over the past 20y. Based on current recommendations for the classification of underweight (BMI < 18.5kg/m2 ), 70% of the centerfolds were underweight. Further, 77.5% of the centerfolds were < 85% of their ideal body weight.” But Fan et al. [2004] think that using WHR is all BS: the real measure of attractiveness is volume divided by the square of height. [I presume we measure a woman’s volume by dunking her in a giant test-tube and measuring the quantity of water she displaces.] They also propose (waist height)/(chin height) as a secondary measure, meaning that women that are all legs are more attractive. Sugiyama [2004] thinks that the waist-to-hip measure confounds some sort of innate waist-to-hipness with body fat, and that it doesn’t take into account cultural conditions. He finds that the forager-horticulturalist men of Ecuadorian Amazonia take both into account when judging women (and weight comes first). Connolly et al. [2004] showed female shillouettes to boys aged 6 to 17, and found that the younger boys thought the more underweight and lower WHR images were “nicer or more attractive”, and the preference shifted toward more average weight and the above .7 WHR as they aged. I only have the abstract, and so can’t go into further detail; also, we’ll never know whether the shift is due to hormones

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CHAPTER 3. PEOPLE AND THEIR PATTERNS

or culture. My overall personal impression is that yes, there are certain basic shapes that people are hard-wired to recognize as human or female, but after that baseline is established and we’ve determined what we’re looking at, a hundred other harderto-measure-and-standardize details become important.

Other things I learned Here are some things I stumbled over while putting together the above that I thought were fun/interesting. Beer goggles Undergrad subjects were asked to rate faces of the same sex, opposite sex, and “non-face objects”, then given booze and asked to do the same. Booze led to a positive increase only in the attractiveness ratings of the opposite sex, indicating that booze is not about loving the world more, it’s about wanting to sleep with people more. [Jones et al., 2003] Earnings Hammermesh and Biddle found that yes, cute people do make more money. There’s about a 7-9 percent penalty for being homely and about a 5 percent premium for being attractive. This is true for both boys and girls, and they even claim (unconvincingly) that the effect is larger for boys. One reason for the attractiveness premium could be things like self-esteem; self-esteem measures are indeed correlated to both earnings and cuteness, but the authors find that including these measures doesn’t affect the significance of the attractiveness coefficients. [But they don’t do the Right Thing, which would be a likelihood ratio test comparing the specifications with self-esteem and without. But that doesn’t affect the results reported here, though.] [Hammermesh and Biddle, 1994] Self-evaluation Boy and girl undergrads were asked to rate their own attractiveness and then photographed. Then, the photographs were rated by undergrads at another university. Note that, as in all the other studies I’ve looked at, there was a high degree of consensus among photo raters about who was attractive and who wasn’t, and this was regardless of both rater and ratee’s gender. This study found that girls’ ratings of their own attractiveness was significantly correlated to the ratings of their photo (i.e., girls know if they’re cute or not), while boys’ self-ratings were basically uncorrelated with the ratings of their photos (i.e., boys have no frigging clue). The authors conclude that girls spend all day fretting about these things, and therefore have good information, while boys just don’t think about it that much.[Rand and Hall, 1983]

3.1. MEASURING ATTRACTIVENESS

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Finger length The ratio of (length of index finger)/(length of ring finger) is larger for girls than for boys: [Fink et al., 2003] The length of the second digit (the index finger) relative to the length of the fourth digit (the ring finger) is sexually dimorphic as males have a lower second to fourth digit ratio (2D:4D). The sexual dimorphism is determined as early as the 14th week of fetal life, and remains unchanged at puberty. There is evidence that sex differences in 2D:4D arise from in utero concentrations of sex steroids, with a low 2D:4D (male typical ratio) being positively related to prenatal testosterone, while a high 2D:4D (female typical ratio) is positively associated with prenatal oestrogen. To go even further, it is claimed that there is a link between male homosexuality and high fetal testosterone, so the 2D:4D ratio, by extension, may be correlated to homosexuality. I don’t wanna mess this one up, so here’s the entire abstract from SJ Robinson [2000]: Sexual orientation may be influenced by prenatal levels of testosterone and oestrogen. There is evidence that the ratio of the length of 2nd and 4th digits (2D:4D) is negatively related to prenatal testosterone and positively to oestrogen. We report that (a) 2D:4D was lower in a sample of 88 homosexual men than in 88 sex- and age-matched controls recruited without regard to sexual orientation, (b) within the homosexual sample, there was a significant positive relationship between mean 2D:4D ratio and exclusive homosexuality, (c) overall, there was a decrease in 2D:4D from controls to homosexual men to bisexual men and (d) fraternal birth order, a positive predictor of male homosexuality, was not associated with 2D:4D in a sample of 240 Caucasian men recruited without regard to sexual orientation and 45 homosexual men. Further work is needed to confirm the relationships between 2D:4D and sexual orientation. However, these and other recent data tend to support an association between male homosexuality and high fetal testosterone. Very high testosterone levels may be associated with a sexual preference for both men and women. The subsequent lit seemed to back these guys up. E.g., I found this study, with a very descriptive title: “Are 2D : 4D finger-length ratios related to sexual orientation? Yes for men, no for women”.[Lippa, 2003] [[Before you start measuring all your friends’ fingers: since homosexuals are such a small sample of the population, the 2D:4D ratio is not a good predictor of homosexuality, even though there

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Type of rating

Investment type

Target sex

Participant sex

Opposite sex

Short-term

Female Male Female Male Female Male Male Female

Male Female Male Female Male Female Male Female

Long-term Affiliation Same sex

Affiliation

Dominance Assistant 6.8 ± 2.3 3.2±2.6 6.4±2.1 3.2±2.2 6.8±1.9 4.7±2.0 4.2±1.5 6.1±2.4

Coworker 6.3±3.2 3.1±2.6 4.9±2.2 3.2±2.3 6.5±1.6 4.2±1.9 3.7±1.6 5.7±2.0

Figure 3.2: Average (S.D.) males’ and females’ ratings of target person (nine-point Likert scale: not at all-very much) is evidently a strong correlation. You’ll get enough Type II errors to make your orientation-throughfinger-length project junk.]]

3.2

Maureen Dowd’s love life: a statistical analysis 2 February 2006

Ms MKW of Washington, DC, was the third reader to point out to me an article by Maureen Dowd of the New York Times, so it’s evidently time to give Ms Dowd’s thesis a closer look. She explains that educated women have a disadvantage on the marriage market because boys prefer girls who are nonthreatening, less smart, and less successful. She cites an article by John Schwartz, also of the NYT, that cites an article by Stephanie Brown of UMich. Ms Dowd explains that this study demonstrated that males have a genetic aversion to dominant females. You know I have no patience for ’they did a study’ hearsay, so here’s the data in figure The experiment is pretty simple: researcher shows to subject a photo with a story attached. The key point of interest in the story is that the person in the photo is a subordinate, a coworker, or a superior. The subject is then asked if the person in the photo is attractive for a one-time sexual encounter, for an activity partner (“would you like to exercise with this person”), or for a long-term relationship. Nine means absolutely and zero means absolutely not. Generally, you can see that when the boys rated girls, the mean floats around 6.5; when girls rate boys, the mean floats around 3.5. For the “would you exercise with him” question, the girls’ means went up about a point. So policy implication

Supervisor 6.2±2.6 3.44±2.9 4.2±2.7 3.1±2.2 5.2±2.5 4.5±1.8 4.5±2.4 6.1±1.5

3.2. MAUREEN DOWD’S LOVE LIFE: A STATISTICAL ANALYSIS

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number one: boys, ask her out for frisbee. Looking a little more closely, we see the anomaly that the paper and two New York Times articles are based on: boys rating an assistant for a long-term relationship rated her at the usual mean of 6.4; boys rating a boss rated her at a mean of 4.2. That’s it: a 2.2 point difference. The number after the ± sign is the standard deviation, and you can see that the difference is approximately one standard deviation for either side. The authors ran F-tests to determine that this is significant. A t-test, and I contend basic intuition about numbers one standard deviation apart, would find that they are not significantly different.1 Part of this may come from the experiment’s design. Ms Dowd is interested in the question ‘do boys like smart and successful girls’, but the narrative in the study was: Please imagine that you have just taken a job and that Jennifer/John is your immediate supervisor. She/he is the person you report to on a daily basis. She/he has the responsibility for disciplining absence or poor performance on your part, for rewarding reliable or creative performance. . . Firing power is a whole ’nother bundle of goods beyond generally successful. If you want to claim that the data above as showing a statistically significant difference, then you can just as easily take the results to mean that boys are more concerned about their careers, or that girls are more trusting of those who could help or hurt them. Finally, and this is the least of my issues here, this is a study of 120 male and 208 female UCLA undergrads. The sample size of a few hundred is normal to large for this sort of work; for example, this academic study of pick-up lines had only 142 F and 63 M subjects. But to say that UCLA undergrads speak for all of homo sapiens seems a bit much. The discussion links this to evolutionary theories about boys trying to work out who the father of a baby is. Our NY Times correspondents confidently cited the evolutionary results as proven by this paper. Me, I will refrain from commenting, 1

I was a little surprised by the use of the F-test here, because we’re comparing two means, which just screams of t-test to me. I checked some undergrad readings, and yes, this is the correct procedure for ANOVA on a multi-way hypothesis. Here’s the summary: the t-test is generally preferable, but it can only test for a difference between two numbers. To compare three means, or to test the hypothesis ‘all the numbers in this subset of the table are not equal’, you’ll need the F-test. So to check how males rate subordinate, equal, or boss females would need an F-test, but to compare males rating subordinate or boss females, you can take your pick. Evidently, you’ll get different results with the data they gathered. Which is all just to say that it is valid to apply a t-test and it fails to reject the hypothesis that the means of the two treatments are identical.

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since I’m unfamiliar with the evolutionary lit. But the structure of the paper itself is that nothing about how boys evolved is proven. Instead, the researchers ran a survey, and stated that it supports a certain existing hypothesis in the lit. Appropriately modest. Unfortunately, Ms Brown is not so understated in the press, and in another Dowd editorial, Ms Brown is directly quoted as stating “Powerful women are at a disadvantage in the marriage market”, and of course, the press eats it up. I have no clue how to find the study Ms Dowd attributes to “researchers at four British universities”, so I can’t comment on whether it correctly supports Ms Dowd’s claims or not. An SF Chronicle article says that that study only surveyed people born in 1921(!?).

Assortative matching Since the micro-level literature left us flat, let’s look at the demographic regularities. These are all based on education, which we take as a proxy for intelligence and success and what-have-you. Educational attainment means less marriage Well-educated women marry less. They’re too busy working at their high-paying careers. On a related note, motherhood also takes a dive with higher education. [[See the tables in Rose [2003], but bear in mind that most of them have a truncated Y-axis.]]

People in school often marry each other Yes, I know it’s obvious. When people in (or just out of) school randomly float around and bump into each other, they are more likely to show a high correlation in spouses’ education levels than older outof-schools bumping into and then marrying random people of broader educational attainment. [Mare, 1991] So Ms Dowd’s problem is not that she’s well-educated but that she didn’t get somebody during or just after grad school. Now that she’s in the real world, the number of boys she will meet in the upper tail of the educational distribution will take a nosedive relative to the number she was meeting in grad school. But notice again that one could explain this with statistical mechanics (particles bumping into each other) without any recourse to a ‘boys seek out dumb chicks’ story. Level of education given married Kremer [1997] looks at the aggregate scale: some quick math shows that the correlation between spouses’ educations was 0.649 in 1940 and 0.620 in 1990, indicating more disparity in spouses’ education levels. But I find this to be too broad to answer the question we have. Education rates are going up over this period, marriage rates are shifting, and our question is primarily

3.2. MAUREEN DOWD’S LOVE LIFE: A STATISTICAL ANALYSIS mate’s schooling 16

boys, 1940; >16 yrs 5.75 3.01 31.46 28.04 31.74

boys, 8587; >16 yrs 0.40 0.93 12.96 25.19 60.52

girls, 1940; >16 years 6.98 3.35 6.98 17.88 64.8

girls, 8587; >16 years 0.22 0.58 14.44 17.75 67.01

boys, 1940; 12 years 14.13 18.69 57.21 7.89 2.08

69 boys, 85-87; 12 years 3.03 8.17 63.14 17.74 7.91

Figure 3.3: Level of education given married

about the well-educated: do they show more or less assortative matching? For this, we look at page 21 of [Mare, 1991], who provides more direct, disaggregated numbers: Here’s what we’re looking at: I took the column for boys and girls with ¿16 years of education (i.e., a college education) and boys with 12 years of education (high school) in these periods, and calculated what percentage of them are matching with a spouse of the years of schooling at left. Each column sums to 100%. So in 1940, 31.74% of married college-educated boys were married to college-educated girls, while in the mid-80s, 60.52% of married boys were wed to college-educated girls. That is huge, and we see a corresponding drop in the college-educated who marry the high-school educated. The high school educated boys were still mostly marrying high school educated girls in the second period, but both of the categories about marrying better educated girls showed an increase, and both of the categories about marrying less educated girls showed a decline. So this data says that even those with a high school diploma showed a stronger preference for an educated wife. For college-educated girls, the rate at which the married among them is matching to a college-educated boy is not moving nearly as much—2.2 percent in forty years. [[I leave as an exercise to the reader the fun of designing a data set where all of the above facts are simultaneously true. Hint: the unmarrieds have not been mentioned in any of the data above.]]

Overall, in 1940, 55.6% of married women were sub-high school educated; in the mid-80s, 11.1% were—about five times fewer. In 1940, 3.85% of married women were college educated; in the mid-80s, 22.37% were—a proportion over five times larger. [Mare, 1991] But, you retort, the number of college-educated girls has gone up significantly. Which is true, and the post-college girl-boy ratio is closer to 1.0 than it was in the 1940s, but the shift in this ratio is not at the scale of the shifts above. Here’s the

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% boys w/college ed+ % girls w/college ed+ College girl/college boy ratio

1940 5.39 3.71 0.69

1985 23.14 16.00 0.77

2004 29.41 26.11 0.96

Figure 3.4: Educational attainment over time

data [(from historical tables A-1 of the Census Bureau’s educational attainment page)] You can see that the rate of college (plus postgrad) completion is way up all around, and the college-completed girl/boy ratio has gone from 69% to 96%. This is great, but is clearly only a fraction of the the doubling and quintupling of the percentages that we saw above.

Probability married given level of education Table two is from 20 years ago; I’m mostly using it because it’s so nicely broken down and says something about who boys are marrying. You are no doubt wondering about girls’ odds today. The answer: college educated girls are doing increasingly better relative to high-school educated girls. Rose [4, table 3, p 42] defines the “success gap” as the probability that a college educated or more gal is married minus the probability that an exactly high school educated gal is married. In 1980, the success gap was 10.0 percent for her sample (U.S. women 40-44); in 1990, the gap was 5.0 percent; and in 2000 it was -0.7 percent. That is, in 2000, a 40-44 year old college graduate girl was more likely to be married than a comparable high school graduate girl. So this measure also fails to indicate any retrogression to the old days of dumb girls. To summarize my story of Ms Dowd’s love life: educated women marry less. People who have been out of school a long time are less likely to marry those who match them, just as a matter of statistics. A person who only wants to date the top 5% on any scale is going to be rejecting 19 out of 20 comers by assumption. This sums up to mean that a single, graduate-educated gal over 40 will have a much tougher time marrying a graduate-educated boy than she did twenty years ago. Also, a single graduate-educated boy will have a tougher time marrying a graduateeducated girl than he did 20 years ago. However, none of this has to do with cultural trends regarding what boys want: the trend since the 1940s has been toward boys of all levels marrying increasingly well-educated girls, and any education penalty that may have existed for women in the past has evaporated. There will always be the arse at the bar who turns tail at the first sound of education—and I as an overeducated boy have at times had exactly the same experience—but that does not quite make for a national trend.

3.3. DOES ECONOMICS MAKE PEOPLE EVIL?

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PS Our educated liberal desire to find a mate of equal abilities directly contradicts our educated liberal desire to reduce inequality. Kremer [1997] argues against this one, but it’s so intuitive that the common economic wisdom takes it as all but given: assortative mating increases class inequality. Back in the day, the poor girl could marry the rich boy and thus become un-poor. But now, Ms Dowd thinks it is a condescending affront that the rich boy marry anyone but a rich girl, and that means that poor girl is going to stay poor. We lament the widening of class boundaries, but what could widen them more than a New York Times editorial excoriating upper class boys for associating with lower class girls? Reader comment: [1998].

3.3

Ms. DH of Ann Arbor, MI refers the reader to Kalmijn

Does Economics make people evil? 14 October 2004

Girls are less cooperative than boys. This has been demonstrated by literally over a hundred lab studies. (The first:Rapoport and Chammah [1965]. But there are hundreds more.) The setup is a prisoner’s dilemma game. For those who are unfamiliar, each player has two options, which are usually called ¡i¿cooperate¡/i¿ and defect. If both cooperate, both get a high payoff, but if one defects, then she gets a higher payoff but the other gets shafted. This is still true if the other player also defected: by switching to defection, her payoff rises and the other person’s falls. Since defection gives a higher payoff regardless of what the opponent does, the only equilibrium in the game is for everybody to defect. Here is an example in table form; the pairs are (row’s payoff, column’s payoff) given the actions listed: C D C 10,10 3,12 D 12,3 5,5 To give the stats from Rapoport & Chammah, in girl-on-girl play, girls play the cooperation strategy 34% of the time; in boy-on-boy play, boys play C 59% of the time, in girl-vs-boy play, C is played about 50% of the time. A hundred studies have been run, with subjects face-to-face (which increases cooperation, by the way) or behind screens, or with male administrators or female, or with different stories attached, or with every other variation you can think of, and the result is consistent enough that we can be comfortable with the first sentence up there: girls play the cooperative strategy less than boys. The 50/50 girl-vs-boy outcome is probably due to the fact that when different types play, their cooperation rates generally meet in

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the middle. Desperate to maintain gender stereotypes, some authors rewrote the results: it’s not that there’s a cooperate or a defect strategy—it’s a choice between a riskyhigh-payoff strategy and a safer-low-payoff strategy, and girls tend to take the safe option. So the studies, it turns out, safely save our gender roles without any boats being rocked. Phew.

B-schoolers A reader asked me about a study that They once did about business school students. (e.g,Frank et al. [1996]; I’m sure there are many more.) Here’s the typical setup: on the first day of class, the students play a few rounds of prisoner’s dilemma games, and we measure their cooperation rate. Then they learn economics and business and stuff like that. They read Dixit & Nalebuff’s Thinking Strategically. Then they play the P.D. again, and we find that the rate of playing C has fallen. We conclude that business school has made the students non-cooperative, defective, or just plain evil. If you want to accept that business schoolers play D more often because they’ve become evil, then you’ll have to also accept that girls play D more often because they too are evil. But clearly, both situations are much more complex.

My studyette Here’s the Beauty Contest game, cut and pasted from my game theory class’s homework #1: Write down a number between 1 and 1000 (inclusive). We will find the average of all responses (µ), and the person who writes down two thirds of this average (2/3 * µ) will receive ten bonus points on this homework. [If there are multiple winners, they will all get ten points.] It’s called a beauty contest because the original story is from Keynes, about printing the photos of some chycks in the newspaper. People bet on who the winner will be, so your task is not to pick the one whom you find cutest, but the one you think everybody else will think is cutest. This is relevant to Macro because money is like this: you don’t really care about the value of a dollar to you, you care about what everybody else thinks a dollar is worth, and they only think a dollar is worth something because they think you think it’s worth something. The game here has similar properties: you have to guess what everybody else thinks the mean will be, and outdo them. If it’s totally random, the mean will be 500, so you should bid 333—but everybody can think this, so you should bid

3.3. DOES ECONOMICS MAKE PEOPLE EVIL?

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two-thirds of that, which is 222—but everybody can think this, so you should bid two-thirds of 222, which is 148—but everybody can think this, so you should bid 98—but eventually, following this along, you should bid 1. This game was the first thing I did on the first day of class. I told them only the first step, that if bids were purely random that 333 would win. I got 99 responses, which looked like this:

Figure 3.5: The before picture

Three bids were the ‘correct’ value of 1, and you can see the others ranged pretty widely. I can only assume that those who bid over 700 just didn’t understand something. The mean from the game was 259, two-thirds of which is 173. This is in line with prior beauty-contest studies. The implication is that people can do this thinking about what other people are thinking about twice: they get to 222, so if you can think three steps down you’re a winner. On homework #1, I ran the experiment again, with the text above. This is after students had all seen what a Nash equilibrium is, and that the only one in this game is one, and I even mentioned the above studies that naive humans generally wind up around 222. They knew the outcome of the first game, but didn’t see the histogram. 63 responses were distributed as below:

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Figure 3.6: The after picture

There are still a couple of people at 1000, but the curve as a whole has definitely shifted downward. The mean from the game here is 100.08, two-thirds of which is 66.7. There were sixteen ones (and four bids less than one, and two around two). [Notice that the peak of the histogram is higher in the second chart; making better spreadsheet charts is not a skill I have much interest in investing in.] There is a clear difference between the two outcomes, but what does it mean? Are people better at thinking of what other people are thinking about what they’re thinking, now that they’ve had a game theory class? There are a whole lot of possibilities. One is that everybody saw me proclaim that one is the only equilibrium, and so they can expect that other people are much more likely to play one, because I created a common-knowledge focal point. Another is that people are just replying to the last game: just as they were able to think two steps past 500, they saw the last game was at 259 and thought two steps past that (which would be 115, which is close enough to 100 for me.) It could be that people are just more familiar with the game and less likely to screw up, as demonstrated by the fact that only two people bid over 700 the second time. But people didn’t all bid one, because everybody believed that the other people were somehow not brilliant enough to work out to play

3.4. THE WEB AS HUMAN NETWORK

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one, so they had to bid a little higher to accommodate those thousands out there. Maybe they just cared more, since the prize in the first game was a loaf of bread I’d baked the night before while the second prize is real live points. The reader can surely come up with a few more stories. Subjects are supposed to just respond to the payoff table, but then there’s an interpretation on top of the payoff table where C is good and societally beneficial and D is self-interested and bad. There’s an interplay between the story and the payoff table which we just don’t really understand, and until we do, we should be circumspect about saying that somebody who plays D often in the lab will be uncooperative here in the Lab of Life. But such problems of generalization are true of any experiment in any field. Unique to game theory is the difficulty of ferreting out what subjects’ actions indicate about what people are thinking. If a hyperrational person played the beauty contest on day one, s/he’d still not want to play one, because our hyperrational friend knows the others won’t play one; the graduate TA is in Figure 1 somewhere, and his bid was in the hundreds. The class changed nothing about him but did change his knowledge of what other people are thinking, so that if he’d bid again the second time around, he’d surely bid lower. Other students may just be better at math having churned through too many algebraesque problems. The whole point of game theory is to study the interactions of your beliefs with your beliefs about the beliefs of others with their beliefs about your beliefs about them, ad nauseum; one game can never disentangle simultaneous changes in all of these things. Barring a slip from time to time, the authors in the game theory literature know this. However, studies reported in the popular press always drop the subtlety of the field entirely, so we get the sort of conclusions above: business school makes you evil. Actually, it updates your information about other business schoolers, and makes you more familiar with cooperation, and helps you better disentangle payoffs from the stories told about payoffs, and maybe makes you evil—and does all of these things at once. All of these studies (gender, b-school, beauty contest) show that there’s definitely something going on that’s worth paying attention to, but it’ll be a few decades before we can ferret out exactly what.

3.4

The Web as human network 14 May 2005

I’d like to discuss the question of how technology has changed personal relations. That’ll come next time. For now, let’s look at a specific, vaguely related question:does the link structure of the Net mirror the link structure of human networks? Back when Alta Vista was the highest view in Internet search, a few IBM and

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Alta Vista researchers did a rather detailed study of the Web’s structure [Broder et al., 2000]. They, as with many others, found that the distribution of links on the Net looked a lot like the distribution of human links. There is a power law distribution where there are a few sites that are linked endlessly, and a long tail of sites that only have a few links.

9 Nominations by ranking 8

7

Nominations

6

5

4

3

2

1

0 5

10

15

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25

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35

Rank

Figure 3.7: Junior high class photo. That’s me on the far right.

To give an example of a power law, here is a graph based on data from junior high classes. The most popular student is on the X-axis at the far left (at X=0), and was nominated as a best friend by a mean of 9.75 other students (over 88 classrooms in the sample). Over on the other end of the X axis, the 25th through 35th ranked student in the classroom was nominated as a best friend by a mean of less than one other student. So you’ve got a few very well-connected students and a lot of students who have no connections at all. We see this pattern in social networks of all scales, and among Web pages. The nomination count graph is typically a little more curvy than this one, with even more of a steep slope down from the most popular members of the group and a longer tail at the other end. It sounds like the WWW as interpersonal network metaphor is working OK, but two caveats: first, there is much debate as to whether the best fit for the link

3.4. THE WEB AS HUMAN NETWORK

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distribution of the Web is a Negative Exponential, a Gamma, a Zipf, or a variety of other distributions that all look identical to a non-expert. Unless you hope to study this stuff seriously, you don’t have to care about this caveat and can just call it a power law. The best fit to the student data is a Gamma distribution, by the way. Second, human networks are pretty symmetric, in that there are few face-toface contacts where one party is ignorant of the other. This is true of celebrities, whom we know but don’t know us, but we can throw those out and have a reasonably symmetric set of acquaintance links. The popular kids may not want to hang out with the unpopular ones, but they know them nonetheless. But with Web pages, it happens all the time that a page makes no indication of what other pages are linking to it.

Figure 3.8: The Insidious Bowtie of Nyrothænim, aka The Internet.

Broder et al found that this asymmetry occurs on a grand scale. They divide the Web into a giant Strongly Connected Component (SCC) comprising about a quarter of the Web; these are sites that interlink with each other. Then there’s a quarter that only links in to the SCC but does not receive links. That would be blogs from losers like me. Then there’s a quarter that is linked from the SCC but does not link to anything in particular, comprising corporate sites that just go in internal circles and things like online books and manual pages that are informative

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but not filled with links. The final quarter, they called tendrils, indicating a trail of limited links that doesn’t readily fall into the first three categories. Thus, because a web page is not a person, the symmetry of human networks does not map to web links. Another important distinction is that the whole small world game, where we try to find a chain of people from a guy in Katmandu to a guy in Omaha, does not work for the Net, because if you start on the right side of the bowtie, you can not get to the left side. For humans, you can almost certainly find a chain, and it’ll be well under ten people in almost all cases; for the Net, you only have about a 25chance of being able to form a chain from any randomly selected site to any other randomly selected site. E.g., try getting from your favorite online manual to your favorite friend’s blog. When you can form a chain, say from the in-feeding region to the SCC region, then it can still be hundreds of nodes long if one element is well-buried in a subculture. Now, with human networks, we can distinguish between acquaintance, which is almost by definition symmetric, and friends, which is depressingly unidirectional, typically from low-status to high-status. I don’t believe this metaphor is particularly well-studied, but it doesn’t work very well. The net receivers of links for the Net are not high-status pages, but pages that just provide information (corporate, technical, whatever). But getting back to the part of the metaphor that does work, there are two characteristics to both networks. First, there’s a cost to linking both socially and online, because you need to find the subject of your interest and know them. Second, there is a cost to searching for new links. An immediate corollary to expensive search is a principle that the rich get richer: the easiest way to find new links for your own personal address book is to ask others for their contacts, so well-linked people/sites are more likely to get more links.

3.5

Invariants 26 May 2005

This is about two technological revolutions that didn’t happen, and aren’t going to happen any time soon. To some extent, this is also about a recent revolution in economics, where the study of how people interact has shown that there ain’t nearly as much variation as we’d thought before: what we thought was wide variety is actually just a combination of invariants. [More generally, it’s a result of computational progress that has allowed us to pay more attention to distributions that are not in the Gaussian family (binomial, Normal, t, F, chi-squared) like the exponential, Poisson, Zipf, &c.]

3.5. INVARIANTS

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The problem is that we humans have limits, and they have not in any way changed thanks to technology. The key limits are time and memory. [Who here bought R.E.M.’s Out of Time on vinyl or cassette?]

The first result of these limits is the size of our comprehensible network. That is, how many people do I know well enough that I could hold a friendly conversation with them? We can connect faster via cellular telephones, email, ntalk, or whatever pointand-talk technology has emerged since I wrote this, and so the time spent connecting is shorter, and we can cheaply connect to more distant people. But once the connection is made, we still have to resort to just talking or writing as before. This takes time, and the new toys don’t speed this up at all. Sure, you’ve got Friendster (or whatever the cool kids are using these days) allowing you to browse through photos of your pals, but back in the day, you had a paper address book, with scraps of everything hanging out of it, that let you do the same thing. de Sola Pool and Kochen [1978/79] made various attempts at estimating the number of acquaintances that a person has, and found that folks generally have about 1,500 immediate acquaintances whom they will see over the next two months once or twice and say hi to, and then about 4,500 less direct acquaintances, like the people from college whom they’ll only see every few years. Perhaps our online networks have sort of blurred the lines on the close-by acquaintances and distant acquaintances, but how many hundreds of your high school pals have emailed you lately? But that’s all scale: what about structure? Are our social hierarchies flatter and more egalitarian now that we’ve got the Net? Again, no. We still see the same sort of pattern we saw in last episode: a few people who are very well connected and a lot of people who are minimally connected. The debate (about which I am no authority) is whether this is because some people have a higher capacity to maintain pals, due to more time dedicated to it or an innate name-and-face memory; or because of a rich-get-richer story that people find new pals via their old pals, so those who are well-networked will only wind up better-networked in the future. The true story is no doubt a bit of both. Costly maintenance of links and costly search for new links have not changed for us humans. Generally, if you’ve got both of those characteristics, you’re going to have a network that looks like standard social networks, and if those limits are set by the human brain and our 24 hour day, then the scale of those networks is set.

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Content Moving on from social networks, the second limit is in what we can produce. If you spent every minute of the next year typing away at your keyboard, your computer’s hard drive would barely notice it all. [[1 word= about 6 bytes. Given 60 words per minute times 1440 minutes per day = 518,400 bytes/day; in a year that’s 180MB.]] For most of us, everything we ever wrote would easily fit onto a single CD. That is, the technology of text processing has blown past the human ability to produce text. For music and still pictures, we’re in about the same place. The roadblock is not in storage and transmission, but in the process of finding artistic inspiration and the time and skill needed to execute it. Moving pictures are not far behind, and twenty years from now, downloading a movie won’t take a moment’s thought by anybody. Nobody will worry about the price of film stock, but the process of writing and producing a movie will still be a massive effort. On the consumption side, it still takes 70 minutes to listen to Beethoven’s Ninth, though you no longer have to get up and flip the disc in the middle. It still takes 90 minutes to watch a ninety-minute movie. The articles that I have on my hard drive in the ‘read any day now’ pile has certainly grown, but the ‘articles I’ve read’ pile grows at the slow, steady pace it always has, and the ‘articles I remember reading’ pile continues to wither. So scale is again set. As for structure, we find that there is again the same power-law type distribution in consumption. If we plot sales and Amazon sales rank on a log-log scale, we find that it’s linear. In other words, the top ten bestselling books sell ten times as much as the bottom of the top 100, and those sell ten times as many as the bottom of the top 1,000, and so on down into the millions. [Below the top sellers, by the way, the ranking is basically the order of last sale, by the way.] That is, content is another power law, and that structure doesn’t change with onlineness: before millions of blogs only read by three people, there were ‘zines only read by three people, and before that, letters. So the distribution of book popularity happens to match the distribution of people popularity, which is no surprise, because the same two problems—costly search and costly linking/consumption—are an issue in both cases.

Policy implications We are all more-or-less as networked as we’re going to be by maybe age sixteen [socially; sexual networks follow different patterns from social networks, and tend to take more of a rich-get-richer form.[Lijeros et al., 2001]]. When you meet somebody new, they’re crowding out somebody else, as time spent cultivating your new pal is not time spent cultivating the old. The same works for entire networks: just

3.6. RISK V AMBIGUITY

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as advertisers must compete for your few dollars, networks must compete for your limited networking resources. Similarly, having a wealth of new content available just means that we have a wealth of things that we’ll never read because they’re crowded out by the other things we’re reading. I don’t mean to say that the Web as a whole is a stagnant waste or that our information processing abilities are irrelevant. But with regards to certain basic human desires, we arrived about fifteen years ago when everybody got a PC, and everything since then has just been adding more features, giving you one more place where you can start a blog and one more list of contacts to keep synced.

3.6

Risk v ambiguity 6 December 2004

So two prominent economist-types, Gary Becker and Richard Posner, have put together a blog. In their first post, they have already revealed one of the great failings of economics today: it has no means of handling ambiguity. Definitions: risk is a situation where there are a few known probabilities—like playing the lottery. People screw up the math sometimes (e.g., they tend to round ultra-small probabilities up until they’re just small probabilities), but generally do OK with it. Ambiguity is a situation where there are a number of possible outcomes, but you have only a vague idea of which will occur. The economist approach is to turn ambiguity into risk. Posner & Becker implicitly do this by talking about expected payoffs with regard to terrorist acts, implying that we can write down the probability that the U.S.A. will suffer a terrorist act in the next week, month, or year. But there’s no way to assign such probabilities. Terrorist acts are like earthquakes: there may be some fixed set of events that cause them to occur with a fixed probability, but we humans have no frigging clue what those events are, and how to turn them into probabilities. ‘Oh, B’, you’re thinking, ‘you’re just hairsplitting. We can’t come up with a perfect estimate of probabilities, but we can try to the best of our abilities.’ I used to think the same way, but there is an abundance of evidence that we humans process ambiguity and risk in truly distinct ways. The most oft-cited is the Ellsberg paradox. In urn A, we have 51 red balls and 49 white balls. In urn B, we have 100 red or white balls, but we’re not telling you how many of each. That is, A is a risky urn and B is an ambiguous urn. In experiment 1, we tell our subjects we’ll give them ten bucks if they draw a red ball; they consistently choose to draw from urn A. In experiment 2, we tell our subjects we’ll give them ten bucks if they draw a white ball; they still consistently choose to draw from urn A.

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The standard risk-as-ambiguity model says that people just assign a risk of white ball to urn B, probably using the Principle of Insufficient Reason, which says that if you don’t have any information, just call it a 50-50 chance. But there’s clearly no way to assign a single white ball count to urn B that would cause you to prefer urn A in both cases—either there are more than fifty red balls in urn A or there ain’t. [The terrorism issue shows parallels to this: we don’t know the probability of terrorism, so no matter the true circumstances, we assume the worst, in a manner that turns out to be inconsistent with any clear view of the world. We respond to ambiguity with irrational fear; then decisionmakers set policy based on this.] There is also some evidence (I can dig up citations on request, but brain scans are a bit questionable; if I gave the name I’d have to give critique) that our brains process risk and ambiguity differently. Ambiguity is processed in the reptilian part of the brain, some claim, where gut instinct gets formed; risk happens in the usual upper math-processing frontal lobe. Even without brain scans, this seems sensible to me: as innumerate monkeys we faced ambiguity all the time, and only in the last few millennia have we managed to come up with means of describing risk. It’s hard to come up with natural selection schemes that select only those who are most capable of matching their gut instinct with correct probabilities. If something has a small likelihood of occurring, a population may best evolve by ignoring that event entirely. This is textbook evolutionary stuff [especially if your textbook is Gintis’s Game theory evolving, which I’ve been teaching from. He repeatedly quips that “Nature abhors low-probability events.”]. The other cause of all of this is that there is no way to prove a probability wrong. When the weatherman says that there’s a 90% chance of rain, he can’t be proven wrong no matter what happens tomorrow. This is especially the case with sporadic catastrophic events like earthquakes or terrorism. There’s no consistent data to gather, and so no way to verifiably prove somebody right or wrong. All of the usual narrow-path yarns about how we could repeatedly trade with somebody who does the math wrong and bankrupt them, or that evolution will select them out of the population, don’t apply. Ambiguity is not risk, and there’s no reason to presume that one is a fair approximation of the other. So there is no way to fit ambiguity into an expected utility calculation, since we can’t just come up with our best risk estimate and call them equivalent. The result is that, frankly, economists have no way to describe an objectively correct decision procedure in the face of ambiguity. I’m not prepared to throw up my hands and say it’s impossible, but right now we don’t have the technology; there’s a Nobel in it for whomever finds a robust ambiguity-is-not-risk way to apply narrow-path economics to ambiguous situations.

3.7. THE MAIL BAG

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The mail bag 26 March 2004

90% of the mail to [national feminist organization] is renewal slips and assorted other forms that just have to be put in little piles and processed; for those, see yesterday’s rant about re-entering numbers off of printouts. The other ten percent has handwritten notes on it which may or may not require attention. These forms with handwritten notes are the embodiment of a conflict. The sender, off in Manhattan, KS, or LA, CA, is looking for a little voice, a momentary connection with somebody who agrees with them. The receiver, me, just wants to know what string of numbers to type in to the ‘source’ field in the database. I don’t want to imply that the entire process is purely impersonal—somebody in the organization looks at the big box o’ letters and gets some feel for public opinion therefrom. But the reply envelope is a lousy place for both human contact and political debate. Almost everything, whether a single line or three pages, is marked in the database with a single capital letter, so brevity, the soul of wit, is as encouraged as ever. Some of the things in the big box o’ letters: • Empty envelopes. By mailing back the business-reply envelope, the sender costs the organization something like fifteen cents and five seconds of labor. Way to stick it to ‘em, Mr. Puerile. [Thrown out.] • Apologies from people who sympathize but can’t afford to contribute. These vary between one line and three pages. The mode are pensioners, who write a paragraph about how they can’t contribute like they used to, sometimes with a little something about Bush ruining the economy. The typed letters go into great detail about the author’s life, how they make their money, and how things have been in recent times. [Flag Q.] • Political rants. These come on both sides of the debate. The opposition usually works in one liners: ‘GO BUSH’, or ‘Please take me off your list, because I don’t support murderer. [sic]’ The support goes into much more detail, often mailing in clippings or diatribes. ‘We must free our bodies from the laws males have oppressed us with. [...] This is our jihad! [writing in Arabic]’ From a man who enclosed a ten dollar check: ‘I am a Black man, and you White women have been bad to us in the past. You lied about being raped and had us lynched. You must never lie.’ This organization endorsed Carol Mosley Braun for President, and many people wrote in to express their displeasure with the endorsement. [Anti- rants are flag R.]

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CHAPTER 3. PEOPLE AND THEIR PATTERNS • Name corrections. Most are just polite fixes, but the amusing ones are the people who are totally pissed off about it, as if you’ve just peed on their family crest. ‘No person named “Eller” at this address. My name is Feller. Please correct and resubmit.’ Many people write in titles like Ph.D.; I am qualified to say that this is hopelessly gauche. I use my title of ‘Doctor’ for only two purposes: grant applications and reaching my pals at work when the boss picks up. I really don’t understand the benefit of informing somebody that they need to fix their database to indicate a successful thesis defense. I have yet to see anybody with an M.S. insist on being called ‘Master’. [Put in the ‘address corrections’ pile.] • Requests for less mail. Some are just a line, ‘Please, no more requests until next year,’ and some are very vehement. The vehement ones are typically a form letter on a separate page, which the person is sending to all the charities that send the person mail. They threaten to withdraw funding—or worse—if they get more than two pieces of mail per year. [Flag T.]

The requests for less mail make a lot of sense: this organization sends faithful members about a mailing a month. Any of you with a pulse have received mailings like these, and know that they have little informational content, and are basically just begging for more cash. As such, they are annoying, and sort of a waste of resources (paper, the receiver’s time). You can identify it from the outside, with the printed image of handwriting which doesn’t fool a single person on this Earth into thinking somebody handwrote something onto your form. The type is funny, because each letter has to be printed separately, to personalize the greeting and the amounts asked for. People who have contributed in the past get boxes with larger numbers than others. The majority of people check off the lowest box, regardless of the amount listed therein. [And the neoclassicists say people spend their money rationally...] I remember when I got my first letter like this from the LA County Bike Coalition. When I first joined, the LACBC was a small organization, with maybe a few hundred members. To me, that letter was sort of the end of the early era where Ron the president knew everybody in the organization, and the beginning of the earnest lobbying phase. The other thing worth noting about these mailings, by the way, is that they are immensely profitable. They really are an effective way for the organization to raise the funds it needs to keep lobbying and informing the public. From what I’ve seen poking around in the database where I shouldn’t, a typical mailing by this organization will cost $15,000 and bring in $25,000 in contributions, which probably makes

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impersonal and annoying mailings like these hard for an organization to resist. I mean, what else in this world almost guarantees a 70% return in two months?

3.8

Business model 2 July 2004

I hate the term. Better than this neologism is the term ‘fee structure’, which better gets across the idea. There are probably two reasons why ‘business model’ has replaced ‘fee structure’ or even ‘price list’: the word ‘model’ sounds much more scientific and thought-out than the alternatives (even though these are not models in the sense that I as a modeler would use the term); and the closely-related term ‘business methods’ refers to something that can now be patented, so that term has seen increasing play. Anyway, the fee structure goes a long way toward the affect one has toward a company. Generally, the less often I am reminded that I’m engaging in a business transaction, the better I feel. There are abundant examples of people who get this terribly, horribly wrong. The big winner are hotels. First, if I’m in a hotel, that means that I’m staying in a city where I have no friends, or at least no friends who like me enough to let me sleep on their floor. So I’m already a little depressed. The paintings are reminiscent of the starving artists sales that I used to see advertised on TV, selling couch-sized art in a wide variety of color schemes. Appropriately enough, these sales were always held at a Holiday Inn. Speaking of the color scheme, many of the hotels I stay in are stuck in a 70s-ish earth-tone theme, which now reminds me of a hotel every time I see somebody’s house in those colors. I imagine this is because the central tenet of all hotel design is: hide the stains. And then, sprinkled throughout the room, are things you can buy. It’s a bit like living in a convenience store with a bed. The bottles of water are $2.50 at the cheap hotels or $4 at the pricier ones. Hotels advertise that they have an in-room fridge, but then the fridge is crammed full of more snacks and drinks that you can inadvertently purchase. I always wonder if I should feel bad about taking all this crap out of the fridge so I can fit in my fifty-cent sandwich. Wireless net access used to be free, until the hoteliers of the world got together and all agreed that they could be charging for it. The places usually come with free coffee, but I never trust it—will someone take inventory and bill me? The only thing definitely free is the soap, which (except at W hotels) is guaranteed to be a lard byproduct.2 Thanks, guys. 2

Ms AMJ of Richmond, VA noted: “Most of the Kimpton hotels can also be counted upon to

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My checking account is like this. Free: write checks, deposit or withdraw money at an ATM. Everything else has a fee. Of course, none of these fees are of the ‘it costs us money to do this, so we pass the cost on to you’ variety. Receiving a wire transfer, a fully automated, no-humans involved, microsecond operation, costs me $15. The interesting thing about receiving a wire transfer is that it can happen without any action on your part. If somebody really wants to piss you off, they can wire you a nickel, and you’ll lose $14.95 in the process. [I verified this with a SunTrust employee. You really could ruin somebody you hate like this. He then tried to sell me things.] Sprint: another one of those companies which offers you a host of opportunities to get billed. Every time you call their customer service, they mention at the end (and the good ones make this sound ultra-casual and just-for-you) that Sprint has a wonderful for-fee service for which you qualify. Last time, I didn’t say no vehemently enough and the little service got added on. Two phone calls later—and therefore two sales-pitches later—I am promised that I will be able to get a refund for the fee next time I call. This is a horrible mistake because there are two things that determine the emotional recollection of an experience. [This is me generalizing from the recollection of pain described in Redelmeier et al. [2003], in the journal Pain. How can you not love a journal named “Pain”. Think of the poor Frenchmen looking for bread recipes.] The first influence on recollection is the emotional extreme (the lowest low), and the second is the state at the end of the experience. That is, if you argue on the phone for an hour and give a cursory ‘I love you anyway’ at the end of the conversation, the entire hour will be recalled as not so bad. Sprint totally screws this up. At that vital end of the conversation, where you’ve finally resolved your problem (hopefully for a positive resolution), the representative is obliged to remind you that you’re dealing with a corporation which is in a slightly adversarial relationship with you and wants your money. I’m not sure how many of these ‘by the way’ pitches actually succeed in making money for them, but it is a business method which leaves every person’s affective recollection of their interaction worse than it was. Gosh, if we humans are nothing but a series of recollections, then this business method literally makes its customers worse off.

stock Aveda soap stuff; they’re where I accumulate my stash of tiny bottles of rosemary mint hair stuff.”

3.9. ACCOUNTING FOR HUMANS

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Accounting for humans 18 May 2004

I’ve been using this accounting program, and have been having trouble wrapping my brain around its philosophical implications.

Figure 3.9: My name is Luca.

Your modern accounting programs are based on a system written down by Luca Pacioli in 1494. The underlying idea is that of a stock and flow model: you’ve got a few stocks of cash (your employer’s bank account, your savings account, your PayPal a/c, your expenditures on chocolate) and cash flows from one stock to the other. The accounting books record the flow of cash from one stock to another by recording a negative entry in the book for the ‘from’ account and a positive entry in the ‘to’ account (and thus the name, double-entry bookkeeping).

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Credit and debit The names for the two entries always sounded backward to me. When you take money out of an account, that’s a ‘credit’ and when you put it somewhere, that’s a ‘debit’. This makes sense at the ends of the system: when you take money out of your employer’s account, that’s definitely a credit to you, and when you buy chocolate, thus putting money into the chocolate account, that’s definitely a debit from you. The weird part is that there’s always an intermediate account in there somewhere, and that’s where it seems confusing. You get a credit halftransaction from your employer, and then counter it with a debit half-transaction to your savings account. Debiting money into your a/c sounds painfully backward, unless you think about putting cash into the savings account exactly as you think about putting cash in the chocolate account, except that instead of comestibles, you’re purchasing the right to future money. That is, the labels only make sense if you think of all accounts as being external and divorced from you. Money flows among accounts surrounding you, but never to you directly.

Converting things My biologist pals point out that they do similar things with the ocean. A region can have a carbon budget, for example, wherein there’s a water stock, an algae stock, a bacteria stock, a fish stock, and each of these stocks hold various levels of carbon, and when one blob eats another blob, then carbon gets transferred from one stock to another. There’s also a parallel nitrogen stock-and-flow model, and another oxygen model, et cetera. These elemental models are distinct, in that you don’t have to worry about a bunch of oxygen suddenly turning to carbon. Ms. JATMM of Mount Vernon, VA sent me some examples of things you can do once you’ve written down the budgets.3 The stuff humans account for is a bit different, so if you wanted to have a cash stock-and-flow system, and a parallel system for cotton, corn, chocolate, cars, and tea, then you’ll have to start converting things. When you buy chocolate, you do not alchemagically convert cash into chocolate: in the cash stock-and-flow model, you have a flow of cash from your account to 7-11’s, and in the parallel chocolate accounting system chocolate flows from 7-11’s account to yours (a very pleasant image, if you ask me). The price determines the relative velocity of the two parallel-but-opposing flows. But since we’re not dealing with elements, there are the actual conversions involved, which need equations in the way of (1 unit tea leaves) + (1 unit hot water) + (1 unit sugar) = (1 unit warm beverage). If you were organized enough, you could write down all the things we humans use, and then put together a big-ass conversion 3

http://fluff.info/blog/asst/seeding.html

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matrix representing every means of converting one thing to another. [This is a Markov-style transformation matrix, so if you start with a vector of commodities, you can repeat production until something breaks, or an equilibrium is achieved, or stuff like that.] Wassily Leontief did this for the entire U.S. economy, which won him a Nobel prize in economics (1973) for such an astonishing feat of accounting.

The one thing missing from the model People. You’ve got this whole set-up to put money into sinks such as ‘cash in my wallet’ or ‘cash I’ve spent on chocolate’, and could expand this to include nonmoney accounts like ‘chocolate I have purchased’. But in disaggregating you the person into a million little accounts, it is impossible to include you the person in the model directly. The closest you get is to make a note somewhere that certain accounts are somehow tied to you the person. Most notably, there is no place in the model for value or enjoyment or utility. The reason for this is that value is not conserved. For every dollar into one account, there’s exactly one dollar out of another—but for value, exchanges happen all the time such that both people are better off. Through some sort of magic, value is created by exchange. The mind of double-entry bookkeeping has been blown, and there’s nothing we can do about it. Books have been written about this. Notably, there’s Mirowski’s More Heat than Light, a book that traces the history of economic theory back to Physics. ‘Physics envy’ is pretty palpable among neoclassicists, but Mirowski does a pleasant job of documenting its evolution, including the evolution of conservation laws in Physics. Conservation laws are the archetypal bookkeeping laws—e.g., for every action, there is an equal and opposite reaction. Mirowski then condemns all of economics to failure because it has no conservation law for value, and never will. The conclusion really doesn’t follow, [and his critique of Varian is just mean,] but the trip is occasionally fun. The resolution, which hadn’t occurred to me until I wrote this, is to use the transformation matrix. After all, cars and cups of tea aren’t conserved: some days there are just more of these things than other days. So you could put into the inputoutput matrix rules like: (1 100g chocolate bar) + (1 2-liter Slurpee) = (200 utils of fun for me). But since everybody’s utility functions are different, you’d need another equation in the matrix to represent how Stevana or Joe turn Slurpees into value. You can see the model quickly becomes far too complex to write down, even for Mr. Leontief. Also, there are issues about how this value thing works: does it keep over time, and if not, where does it go? Can it be spontaneously generated? But Mr. Mirowski, once we’ve written down the rules of production for our imaginary commodity, the structure is consistent.

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But even after we include billions of value-creating equations, people still don’t appear in the model. The closest we come is to set up stocks for value, and attach one of these value stocks to each person. I think that’s as close to a representation of humans as accounting will be able to do.

3.10

Taxing value 14 December 2006

The question for the day: when should you count transfers among third parties as part of your taxable income? Here are two examples. • Your pal gives $1,000 to Amnesty International in your name. Gifts are counted as income; since this is a gift to you with a fair market value of $1,000, does this count as income to you? • Instead of giving you a rent check, your tenant sends the rent directly to CitiMortgage, who apply it to the mortage on the house where your tenant is living. You never see the cash, but pay a smaller mortgage. Does it count as income to you? To the intuition of most of the folks I’ve spoken with, the gift donation should not count as income, and the sidelong rent payment should be. So that’s an easy consensus, but the next question is why one third-party transfer should count and the other shouldn’t. Both are a transfer from one third party to another that benefits you, and at that level, are equivalent. The fact that one is a gift is irrelevant: if Grandma slipped a $1,000 check into your birthday card, you would have to claim it like any other income. Amnesty is a charity, but that just means that after you claim the $1,000 gift as income, you can deduct it as charitable giving. I mean no offense to the many people who have tried, but I have not yet seen a reasonable explanation as to why we should treat one of these cases as income but not the other. Defining income is hard. A great deal of title 26 of the US Code is about questions like these. When your employer pays your health insurance for you, is it income? What if they reimburse you for it after you pay for it? Since you sometimes declare your income tax over a year after you earned it, other problems can arise: ¿If you live in Maryland but work in DC, to whom do you pay state income taxes? [Hint: only one of these areas has Congressional representation.] We put the Service in Internal Revenue Service I called IRS’s customer help line, because this question actually has some relevance to my own tax situation. This was probably mean. I’m looking for a valid definition of income—a ques-

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tion which is fundamentally hard, as I’ll discuss below—and they’re armed with a couple of publications on the IRS website that I’ve already read. The first, IRS representative #2504624, decided that a mortgage counts as rental expenses. At this point I’m torn. Even I know this is false, but is it rude to call her on her made-up interpretation of tax law? Her: As you can see from this publication, tenants paying rental expenses count as income. Me: It also says here that you can deduct the full value of rental expenses, so would that mean that a person could deduct their full mortgage? Her: No. You can never deduct your full mortgage. Me: But you declared that it’s a rental expense, and those are deductible. Her: Mortgages can’t be deducted. They don’t count as rental expenses. Me: So if it’s not a rental expense, then it’s not income when a tenant pays. Her: Yes, it is income. When a tenant pays rental expenses, then it’s income. This went on for a while, as I politely pressed her for a consistent definition of rental expenses, or of income. She eventually hung up on me. Which is why I’m bucking my normal habit of using only initials and am printing her full name here. That’s right, IRS Representative #2504624, every time anybody searches for your name, the first hit will be this post about how you rudely treated a taxpayer after giving him blatantly false, made-up advice. The second try gave similar results, albeit much more politely: Him: This counts as income under the doctrine of constructive receipt. Let me transfer you to somebody else who will explain that to you so I don’t have to talk to you anymore. While on hold, I looked up this doctrine. Constructive receipt is about the timing of income. If you get a paycheck on 20 December, but don’t deposit it until 2 January, it still counts as income as of 20 December, because there was nothing keeping you from receiving it then. But this doesn’t apply to either of the above cases, because there’s a whole lot keeping you from receiving money from either Amnesty or CitiMortgage. The conversation with the third person went about the same, but he had the grace, wit, and courtesy to admit that he had neither the text of 26 CFR nor the wherewithal to interpret it, and wrote out an email inquiry that was to be replied to within 48 hours. [You can’t directly email the IRS’s service desk—you have to phone in and ask the operator to type out an email for you.] Naturally, I never got a response. I checked 26 CFR myself and learned an interesting factoid: it doesn’t actually define income, beyond the basic ‘income is money you receive’ definition that does not to justice to any of the above.

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The root of the problem My purpose in elaborating on the Service part of Internal Revenue Service is to show how even the full-time professionals have little idea of how to define income. It is a hard problem. On the one hand, there’s some intuition that when you gain value from an action, like when somebody pays your mortgage for you, then it is income. Many countries explicitly use this definition and call it a value-added tax (VAT). But on the other hand, we recognize that you sometimes gain value in ways that are not the government’s business, like when somebody gives you a nice backrub or gives money to Amnesty in your name. There are the no-brainer cases—if somebody hands you cash, then it’s income— but what if you loaned them fifty bucks that they paid back the next month? Is that $50 income for them in month one and $50 income for you in month two? Nothing is consumed and relatively little value is added, but it’s ambiguous whether there’s income. The law also considers things like large gifts to be income. Remember when Oprah Winfrey gave her audience members cars, and they then each got a $7,000 tax obligation with the gift? The idea here is that any item that you receive is equivalent to its fair market value. But this opens the door for massive ambiguity: that backrub has a fair market value, after all. The tax code is a mess because the problem of defining income is fundamentally unsolvable, because it starts with a fundamentally unsolvable question— ¿Where does value come from?—and then adds on top another fundamentally unsolvable classification—¿What portion of value should be taxed? The IRS only makes things more difficult by refusing to acknowledge that the income tax is a tax on value. But it remains in denial, both in order to sound smart and for political reasons (The VAT is unpopular because Europeans do it, and the IRS doesn’t want to admit that the income tax is a botched VAT). If we could use the word value, then the Amnesty-CitiMortgage conundrum is easy: the gift contribution adds a small amount of value to your life, while a $1,000 mortgage payment adds $1,000 in value. As the IRS’s service representatives demonstrated, when you can’t use the V word, you’re stuck making up ad hoc stories about rental expenses and constructive receipt that don’t quite work. Solutions First, let me quickly dismiss one faux solution to the conundrum. Under a flat tax, we retain an income tax but lower tax rates on the rich and raise tax rates on the poor so everybody is paying the same tax. The painfully disingenuous justification for this is that it simplifies the tangle of tax forms. But the root of the mess is not in the problem of working out whether to multiply taxable income by 0.3 or 0.18, it’s defining taxable income—a problem that the flat tax doesn’t touch. A tax form for the flat tax would be exactly as long as the current 1040. Another, much more effective alternative: the consumption tax. It has some

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æsthetic appeal: we aren’t bothered by the rich for making lots of money, we’re bothered by how they buy big yachts and overpriced shoes. We want to encourage savings, which is why there are so many exceptions in the income tax for savings like 401(k) plans (i.e., retirment plans conforming with 26 CFR 1.401(k).). By the simplified equation Income - Savings = Consumption, the current tax code makes you calculate income—already hard, as above—and then excruciatingly subtract every element that could somehow count as savings. The consumption tax just has you total up consumption, by billing you at point of sale like any other sales tax. The consumption tax also reconciles the Amnesty-CitiMortgage problem. First, we would decide whether either of the above counts as consumption or not right off the bat. Instead of the situation we have now, where we tax your income and then if you contribute to Amnesty then you get to deduct that portion of income (under a number of caveats), you would instead pay tax when you give money to CitiMortgage (depending on how you wanna count buying a house), and then not pay tax when giving to Amnesty. Second, all those issues about who who is the final recipient just evaporate: tax is paid by the person making the outlay. Oprah pays taxes on the car when she bought them. There’s the social problem of whether the tenants should pay the landlord’s taxes, but that isn’t complicated by the accounting issues. Sure, there are still questions of how one defines consumption—like whether your house is consumption or an investment. But once we have an arbitrary decision on that question, the accounting is much easier. We like progressive taxes, where poor folk pay a lower percentage than rich folk. There’s intuition behind this, that economists can readily formalize: a dollar to a poor person that buys a loaf of bread is worth much more—has much higher value—than a dollar to a rich kid who uses it to buy a portion of jewellery or other useless items. [In formal terms, there is a diminishing marginal value to income, which is evidenced by risk-averse behavior, especially as shown by those who are well past the survival level.

McCaffery [2002] proposes fixing this via a refund on the taxes paid on the first $20,000 in spending. If the tax rate is 5%, everybody just gets handed $1,000. Those who consumed less than $20,000 are now making a small profit on the tax system, and thus pay a negative rate; those who spent $20,000 last year are paying 0% taxes, and the yacht buyers are paying 4.999%. So, the consumption tax really is a simplification of the tax scheme, because it takes taxes at the door, replacing the problem of defining income minus savings with the simpler problem of defining cash purchases for consumption. It encourages savings and discourages yacht purchasing. The only problem is that there are several industries built from the ground up around avoiding income taxes. Lindblom explains in his Market as Prison essay [Lindblom, 1982] that the market is

A progressive tax on cash terms approximates a flat tax on value terms.]

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the perfect system for preventing change, because no matter the change, somebody will resist it because they are optimized to make money the way things are now. So when you have a massive system like the income tax, no matter how fundamentally screwed up it is, there will always be a chorus of defenders. So we’re stuck with the tax law we have, that attempts to codify the answer to two impossible-to-answer questions. We’ll get tax laws that simplify the situation a bit, and tax laws that complicate it a bit, but as long as the law requires a definition of value and a definition of what value is to be taxed or untaxed, the law will remain a mess.

4 E CONOMICS TODAY

4.1

Etiquette for economists 10 March 2006

Today’s recommendation, for my usual audience of mathematicians and social scientists: Miss manners. No, not because of the usual reasons that no doubt sprung to your head when you saw mathematician and manners in the same sentence. I recommend the etiquette column because it is a paragon of social science analysis. The first rule you need to bear in mind when reading on etiquette is that none of etiquette is arbitrary. Take this as axiomatic; if you believe that a rule violates this axiom, then you don’t understand the rule and should try again. The problem of etiquette is exactly the problem of law, economics, and the social sciences in general: given that people have competing objectives and perceptions which are often in conflict, what is the mechanism that minimizes conflict and maximizes social benefit? The problem is more difficult than most economic problems because etiquette is not law, and therefore not everyone is following it. [I.e., we need a mechanism which is a Nash equilibrium for an asymmetric game where one side is playing the rule of etiquette and the other side may or may not be. This can be orders of magnitude more difficult than the symmetric problems with which we economists satisfy ourselves.]

Etiquette columns are fun because each summarizes a conflict and its resolution, often in a clever-in-a-good-way manner. Miss Manners (aka Ms JM of Washington, Columbia) does an especially good job of keeping upbeat in the face of conflict after conflict. I picked up a copy of Miss Manners’ Guide to Excruciatingly Correct Behavior [Martin, 1982], wherein she explains her own frustration with the misunderstanding of etiquette: If Miss Manners hears any more contemptuous description of etiquette as being a matter of ’knowing which fork to use,’ she will run amok with a sharp weapon, and the people she attacks will all be left with 95

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CHAPTER 4. ECONOMICS TODAY four tiny holes in their throats as if they had been the victims of twin vampires. [p 119] [Of course, this doesn’t keep her from spending six pages on the question. We have to let that

slide, along with the occasional letter in the way of ‘I was reading a historical novel that described an odd item. What is it?’ We must allow Miss Manners her turn-of-the-last-century fetishes. And I find the third person tone amusing—some of our more trendy columnists below emulate it directly—but some tire of it1 .]

Many of her columns are about simple restraint. Don’t gossip, don’t go around pointing out other people’s errors of etiquette, don’t indulge in rudeness in response to rudeness. In the context of economic jargon, it’s a simple question of internalizing externalities, reminding the reader to time-discount appropriately, and establishing default norms to minimize cognitive effort regarding which fork to use so people can focus on the important things. Such principles seem simple enough, but like the principle of utility maximization, there are endless applications and variants. She also frequently receives and prints letters in the way of “Dear Miss Manners: I was an arse, but I have a justification. Back me up here—I was right, right?” Those columns rather literally write themselves. And then there’s the clever reply. Economists eat this stuff up: given a system of rules, how can one elegantly achieve some seemingly difficult goal? As for the rudeness of others, Miss Manners finds that is conquered by politeness. For example, a gentleman of Miss Manners’ acquaintance dislikes being honked at by impatient drivers for not starting his automobile quickly enough when a traffic signal turns to green. Instead of honking back, however, he puts on his emergency brake, emerges from his car, presents himself to the honker in the vehicle behind, and inquires gently, “Did you summon me?” [p 4] Many inquiries are of the form ’this used to be the standard form of etiquette, but it’s obsolete now, right?’ These letters are the most informative, because they are another way of saying ’I think this rule is arbitrary’, which, as above, is false for any sustainable rule of etiquette. There is a limited set of rules that are obsolete, primarily because we no longer have a fairer sex whose members do nothing but bear children and swoon from time to time. But determining whether a rule is indeed no longer valid requires an honest knowledge of why it was in place before, rather than a dismissive ’oh, how Victorian’. One or two pals of mine have pointed out that different societies have different manners. I’m no stranger to the idea of multiple equilibria, and there are always 1

http://www.5ives.com/archives/2005/11/15/five-people-of-whom-i-confess-to-being-a-

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surface issues like shaking with the left hand or showing the soles of one’s feet, but I can think of no cultures where fundamentals of interpersonal relations, general courtesy and some set of default social norms that people can fall back on, are not observed. The reader is invited to leave examples for discussion in the comments. Advice Why recommend Miss Manners over more sensational advisers? It is the difference between an etiquette column, focused on balancing competing goals to form a society, and an advice column, focused on helping people to think more clearly where irrationality sometimes prevails. ’Dear sex advice columnist: I was thinking with my crotch and now I’m miserable. What should I do?’ The advice column presents interesting stories and solutions, but is a different animal from the etiquette column. Further, many such columns work hard on maintaining the sensationalness by focusing on surface novelty of the ‘I recently became a man, and am seeking someone who recently became a woman, but I’m running into difficulty’ variety, instead of the never-changing basics of human relations. Miss Manners’ advice works for boys, girls, and everybody in between. E.g., “It is the essence of social flirting that no one—not even the participants—should be positive that anything more was intended than simple enjoyment and admiration.” [p 276] Such advice will work as well in the tea room as in the dungeon.

4.2

Neoclassicism watch 9 September 2004

I’ve spent a lot of time complaining about neoclassicists, as have many others— Mirowski comes to mind, but a huge amount of non-economist social scientists talk about this; a very active anti-Chicago-school club of political scientists called Perestroika also stand out. But despite the alarmists, I think the purist neoclassical worldview is on the wane, and the hardcore neoclassicist is becoming a rare breed. Academia [Some readers may want to skip to the policy section, below.] My impression of the last decade or so of economic theory is that it has been concerned with going beyond the standard ‘everybody perfectly maximizes a self-interested utility function’ framework. There are a few reasons for this, the first being that the framework is obviously too narrow. The pro from overnarrowness is that you can explain a lot of behavior using a few simple rules, which is generally a scientifically good thing and worth pursuing as far as it’ll go. The cons are that from a few axioms you only get a few results before you have to start trying too hard. After

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so many decades of pushing a handful of axioms, even the most driven and devout are basically running out of things to explain, and the explanations are becoming increasingly tenuous. Where to from here? The prevailing method is not to throw out the whole framework, but to expand things. People are still maximizing a utility function, but the utility function may be allowed to have other elements. E.g., I am a fan of including an axiomatic desire to emulate others. That plus the standard framework leads to more (and more plausible) results. Others, notably the Kahneman and Tversky school, are revising the ‘perfectly maximizing’ part to take into account that people commit systematic errors in perception and reasoning. From my perspective, these wide-path approaches are the prevailing standard in economics, and will be for a long time. There are other approaches as well, where people have rules of behavior that don’t use the word ‘maximize’ at all, but I think they remain on the fringes (which is not to imply that they are less valid or should remain on the fringes). There are still defenders. In my own limited experience, I think that people starting off life as an economist are very likely to be attracted to narrow-path neoclassicism, and in an ontogeny-recapitulates-phylogeny sort of way, they go through the process of finding out that the narrow path has basically found all it has to find, and that it has valid critiques. And, as below, politics influence methods. So to summarize this section: the narrow-path Chicago school has become a straw man that few if any academics fully believe in. I acknowledge that I myself am very guilty of beating this straw man at times, and narrow-path fans do certainly still exist, but the energy of the non-economist social scientist could probably be better spent just ignoring the narrow-path people and working on making the wide path work for everybody. Policy I met an IMF economist last night. To overgeneralize the overgeneralizations made in the past, IMF economists are famous for being obnoxiously narrowpath; this is in contrast to World Bank economists who are a bunch of hippies, most of whom have little faith in the narrow path, while others are off the path entirely. Ms PM of Washington, Columbia, has been an economist at the IMF for about a year now, but being young and hip and two degrees of social separation from me, she was not inclined to be a cold-hearted conservative. So I asked her about these critiques of the IMF. Her first response was that it’s the politicians. The Treasury and even the U.S. Congress have a say on what the IMF publishes, and can veto research. She bitterly cited examples of political censorship. The narrow-path Chicago school is as pro-

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business as a methodology can get, meaning that political influence (invariably by conservatives) filters out anything that isn’t narrow-path. I have hung out with many more WB people, and have never heard them mention political censorship of WB research. Her next argument was that the neoclassical methodology is the only one that’s relevant to the currency-type issues that the IMF studies, so all the wide-path stuff is just off track. I think this isn’t wholly true, but it is true that the macro literature is behind the curve on widening the path, meaning that the bulk of established literature is indeed hardcore neoclassical. On top of this, the IMF senior staff is another decade or two behind the curve, because that’s when they stopped learning new tricks (that’ll be us someday). This is also consistent with another of Ms PM’s explanations: that those who are interested in other methods (which are evidently still cutting-edge) tend to leave the IMF for academia. Maybe fifteen years from now, their wide-path research will become IMF orthodoxy. The other prevalent complaint about the IMF is that they are maximizing currency stability where they could be maximizing education, class or gender equality, or any of a number of touchy-feely things that we humans care about. P was moreor-less unapologetic about this: although economists come to the IMF because they care about the developing world and truly want to help, it’s the IMF’s mandate that they focus on money issues and leave development issues to the World Bank. But this is a truly problematic stance because IMF policy clearly, obviously affects development. Most directly (and P has the literature to prove this), if the IMF cuts off a country, then nobody will lend to them ever, regardless of the reasons for the IMF’s decison. When the WB tries to fund a project to build a sewer system in a few villages in that country, it won’t be able to get backing. As a result, the IMF pretty much never truly excommunicates a country. More indirectly, every IMF loan comes with conditions. All loans of any sort do, of course: it would take me all day to list the conditions on my mortgage. P gives the example that a loan to Ethiopia a few years back with the condition that the money be used to pay the wages of workers who were on the verge of revolt. The IMF started the funding, saw that it was all being stolen by kleptocratic governors, and cut off the loans. What are ya gonna do. Other conditionalities are a bigger deal, notably about size of government. This harks to the competing macroeconomic schools: the Keynsian school says that government spending can expand growth, while the narrow-path Chicago school says that big government is always bad. The Chicago school won at the IMF on this point, and cuts in government are often demanded, without regard to the development and distributional impact of these cuts. It is my opinion that the conditionalities can and should be development oriented. Why not demand that a country take steps to put more girls in schools before

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loaning them cash? Is this really more interventionist than a demand that a country cut government bureaucracy before lending cash? I’d like to write a whole lot more on this, but you get the picture: the IMF is an interventionist institution which places conditionalities on its loans, and those conditionalities need to be written in concert with the people who care about development, even if the narrow path dicates that accommodating these other issues may hinder the IMF’s core goals. But you knew that. All of these are probably factors in the overall story of why the WB is filled with wide-path hippies and yet there are no recycling bins in the IMF public spaces. There are probably other ineffable issues: Bob Lucas is said to have said: ”Once you start thinking about growth it is difficult to think about anything else”; the WB’s economists think about growth all day long nonstop, and that’s just not the job of the IMF’s economists. That plus political pressure can create a different mindset where the narrow-path isn’t unattractive. Generalizing beyond the IMF, the narrow path is convenient for a certain set of conservative beliefs (as I’ve discussed endlessly in this essay), and so the narrow path will always have a place in propping up the conservative side. I’d like to say that there’s a trickle-out effect where as academic research becomes more widepath, the discourse in the rest of the world will gradually take on the same direction, but this is probably too optimistic. So long as conservatives still walk the Earth, the narrow path will never die in public discourse and the policymaking community.

4.3

The future of economics 22 February 2005

Here is my terminology: Narrow Path economics is the Chicago school stuff that everybody loves to hate, in which people perfectly maximize a narrowlydefined utility function. The Wide Path expands upon this, with people who can’t do the reams of math necessary for perfect maximization and who include more squishy things in their utility function, like other-regarding preferences and personal identity.2 To date, my mental model of the future of economics has been the wide path. That is, at the current course, we’ll still be writing down utility functions twenty 2

Am waiting for you guys to pick up on the terminology. I remain the only hit on the planet for “wide path economics” in all the major search engines. I’m stealing the terminology from Buddhism, by the way: the Narrow Path is based strictly on the teachings of Siddhartha Gautama, and is cynical and individualistic. The Wide Path incorporates teachings from all over the place, and is generally what we think of when we think Buddhism.

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years from now and trying to somehow maximize them (or satisfice them, or whatever). I hate to name drop, but I had dinner with Lord RL of London, UK, the other day, and I asked him where he thought economics was going. Is there anything beyond utility functions?, and he says yes, there’s the problem of where those utility functions come from. And that, in turn, may best be explained by the groups and the environment in which a person lives. [Lord RL’s work, both on wages and on human happiness, is based heavily on the context in which a person finds him/her/itself. A wage which is miseryinducing in the U.S.A. would let you live an easy life in other parts of the world. So how do people get away with modeling preferences in absolute terms which wholly ignore the surroundings?] For the fanatical individualist, who sprung whole from his own head, this is controversial, but I think the rest of us are not surprised. Of course preferences come partly from some internal milling and partly from some external influences. The problem, though, is how we should model that. As noted, we have the machinery to write down and study existing preferences in a thousand different ways, but we’re basically lacking in describing ways by which preferences are formed. This is basically another rephrasing of my favorite economic question: where does value come from? The answer is a no-brainer for only the most rudimentary of goods—maybe sugar and water. Go past that, and it’s a mystery world which we assume away. Sociologists do not. There are two approaches in the psychology and sociology literature, which compete but dovetail. The first is identity theory, which posits that all of us have an identity, which is an arbitrary position invented via interaction with others. Notably, it comes from play. We assume certain roles—daughter, boss, economist, schlamazel. The magic occurs in that once we are assigned these roles, they start to matter. I could care less about knowing how to clear clogs in my sewer line, because I’m not a plumber, but I care deeply about my ability to calculate the ratio of a distribution’s kurtosis to its variance squared. It’s a long, hard road to explain why this has value to me in terms of getting fat and reproducing, but if we base my utility function upon my self-identification as a mathematical economist, and my desire to play that role well, then my unyielding interest in calculating the properties of probability distributions is obvious. So there’s one way that we can assume utility functions into existence: posit that people engage in social roles—they play—and that preferences come from those forms of play. This leaves us only to describe how these roles are formed. The other option, which sociologists call social identity theory, involves simple group membership: we join or are forced into certain groups, and the preferences of those groups become our preferences. Now we have only to model why we wind

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up in the groups we wind up in. In both cases, individuals derive value from some things and not others because of the social position they find themselves in. First the society defines their utility function, and then they shape society based on their utility function. The next step in economic theory, which has already begun in some circles, will be to eschew the Ayn Rand-like individualistic streak which runs through most of economic theory, which is providing us with diminishing theoretical returns anyway, and to describe people as both shaping their environment and being shaped by their environment.

4.4

The statistics style report 10 September 2006

It may sound like an oxymoron, but there is such a thing as fashionable statistical analysis. Where did this come from? How is it that our tests for Truth, upon which all of science relies, can vacillate from season to season like hemlines? Before answering that question, note that statistics as a whole is not arbitrary. The Central Limit Theorem is a mathematical theorem like any other, and if you believe the basic assumptions of mathematics, you have to believe the CLT. The CLT and developments therefrom were the basis of stats for a century or two there, from Gauss on up to the early 1900s when the whole system of distributions (Binomial, Bernoulli, Gaussian, t, chi-squared, Pareto) was pretty much tied up. Much of this, by the way, counts not as statistics but as probability. Next, there’s the problem of using these objective truths to describing reality. That is, there’s the problem of writing models. Models are a human invention to describe nature in a human-friendly manner, and so are at the mercy of human trends. Allow me to share with you my arbitrary, unsupported, citation-free personal observations. Number crunching The first thread of trendiness is technology-driven. In every generation, there’s a line you’ve got to draw and say ‘everything after this is computationally out of reach, so we’re assuming it away’, and the assume-it-away line drifts into the distance over time. Here’s a little something from a 1939 stats textbook on fitting time trends: To fit a trend by the freehand method draw a line through a graph of the data in such a way as to describe what appears to the eye to be the long period movement. . . . The drawing of this line need not be strictly

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freehand but may be accomplished with the aid of transparent straight edge or a “French” curve. As you can imagine, this advice does not appear in more recent stats texts. In this respect, a stats text can actually become obsolete. However, true and honest approximations like this are relatively rare. Instead, more computing power allows new paradigms that were before just written off as impossible. Computational ability has brought about two revolutions in statistics. The first is the linear projection (aka, regression). Running a regression requires inverting a matrix, with dimension equal to the number of variables in the regression. A two-by-two matrix is easy to invert (ad − bc, remember?) but it gets significantly more computationally difficult as the number of variables rises. If you want to run a ten-variable regression using a hand calculator, you’ll need to set aside a few days to do the matrix inversion. My laptop will do the work in 0.002 seconds. [It’s still in under a second up to about 500 by 500, but 1,000 by 1,000 took 8.9 seconds. That includes the time it took to generate a million random numbers.]

So revolution number one, when computers first came out, was a shift from simple correlations and analysis of variance and covariance to linear regression. This was the dominant paradigm from when computers became common until a few years ago. The second revolution was when computing power became adequate to do searches for optima. Say that you have a simple function to take in inputs and produce an output therefrom. Given your budget for inputs, what mix of inputs maximizes the output? If you have the function in a form that you can solve algebraically, then it’s easy, but let us say that it is somehow too complex to solve via Lagrange multipliers or what-have-you, and you need to search for the optimal mix. You’ve just walked in on one of the great unsolved problems of modern computing. All your computer can do is sample values from the function—if I try these inputs, then I’ll get this output—and if it takes a long time to evaluate one of these samples, then the computer will want to use as few samples as possible. So what is the method of sampling that will find the optimum in as few samples as possible? There are many methods to choose from, and the best depends on enough factors that we call it an art more than a science. In the statistical context, the paradigm is to look at the set of input parameters that will maximize the likelihood of the observed outcome. To do this, you need to check the likelihood of every observation, given your chosen parameters. For a linear regression, the dimension of your task was equal to the number of regression parameters, maybe five or ten; for a maximum likelihood calculation, the dimension is related to the number of data points, maybe a thousand or a million.

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Executive summary: the problem of searching for a likelihood function’s optimum is significantly more computationally intensive than running a linear regression. So it is no surprise that in the last twenty years, we’ve seen the emergence of statistical models built on the process of finding an optimum for some complex function. Most of the stuff below is a variant on the search-the-space method. But why is the most likely parameter favored over all others? There’s the Cramer-Rao Lower Bound and the Neyman-Pearson Lemma, but in the end it’s just arbitrary. Gauss had no theorems that this framework gives superior models relative to linear projection, but it does make better use of computing technology. Hemlines The second thread of statistical fashion is whim-driven like any other sort of fashion. Golly, the population collectively thinks, everybody wore hideously bright clothing for so long that it’d be a nice change to have some understated tones for a change. Or: now that music engineers all have ProTools, everything is a wall of sound; it’d be great to just hear a guy with a guitar for a while. Then, a few years later, we collectively agree that we need more fun colors and big bands. Repeat the cycle until civilization ends. Statistical modeling sees the same cycles, and the fluctuation here is between the parsimony of having models that have few moving parts and the descriptiveness of models that throw in parameters describing the kitchen sink. In the past, parsimony won out on statistical models because we had the technological constraint. If you pick up a stats textbook from the 1950s, you’ll see a huge number of methods for dissecting covariance. The modern textbook will have a few pages describing a Standard ANOVA (analysis of variance) Table, as if there’s only one. This is a full cycle from simplicity to complexity and back again. Everybody was just too overwhelmed by all those methods, and lost interest in them when linear regression became cheap. Along the linear projection thread, there’s a new method introduced every year to handle another variant of the standard model. E.g., last season, all the cool kids were using the Arellano-Bond method on their time series so they could assume away endogeneity problems. The list of variants and tricks has filled many volumes. If somebody used every applicable trick on a data set, the final work would be supremely accurate—and a terrible model. The list of tricks balloons, while the list of tricks used remains small or constant. Maximum likelihood tricks are still legion, but I expect that the working list will soon find itself pared down to a small set as optimum finding becomes standardized. In the search-for-optima world, the latest trend has been in ‘non-parametric’ models. First, there has never been a term that deserved air-quotes more than this. A ‘non-parametric’ model searches for a probability density that describes a

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data set. The set of densities is of infinite dimension. If all you’ve got a hundred data points, you ain’t gonna find a unique element of

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