Prelude to an Interview: Barbara van Schewick’s Internet Architecture and Innovation

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4 Responses

  1. “Her models actually predict the pattern accurately–unlike other academic models like the efficient market hypothesis and theories on valuing derivatives.”

    I lost you here.

    1) The efficient market hypothesis works spectacularly well in terms of predictions, *in domains where it can make predictions*. It does not predict there will be simple and stable valuations (people sometimes think it predicts this, but they are wrong, and why that is wrong is a deep topic).

    2) Valuing derivatives also works pretty well – lots of people are working a con-job here, basically, blame the model, because it can’t be fined or go to jail.

    I haven’t read the book, so I’m not taking a stand. But I can’t see what pattern there is to predict that’s not question-begging (i.e. boiling it down to something like innovators innovate when there is an environment that encourages innovation).

  2. A.J. Sutter says:

    I haven’t read the whole book, but I did check out the recommended Chapter 8 via Amazon, and some of your other links. Some observations:

    1. The retrospective fitting of a few salient historical cases into a theory is not creating “models [that] actually predict” anything. This kind of ‘postdictive’ exercise is the bread and butter of fatuous business books. As far as I could tell, van Schewick doesn’t present detailed data about the 90+% of start-ups that fail — perhaps lots of them had products/services with characteristics similar to those that succeeded.

    2. The book and the SSRN article to which you’ve provided a link assume that economic growth is good, and that it justifies the policies for which BvS is advocating. The assumptions that economic growth is beneficent, and an end in itself, are both conventional and contestable.

    3. Another conventional, neoclassical idea is that all user “needs” are put onto an equal footing. Just like economic theory, it ignores the question of whether all uses of the Internet are socially desirable.

    4. None of the above necessarily undermine a narrow policy argument BvS seems to be promoting, viz. that the private oligopolists who control the (US) network should not be allowed to optimize their respective networks for — nor, conversely, to “block or degrade” — specific applications. But it seems to me that when advocating for a more open network, the best mode of discourse on this issue should be political, not economic. BTW when I did a search on the term “public good” in the book, it shows up only in the footnotes.

  3. Marvin Ammori says:

    Hey, there are some thoughtful responses here.
    I’ll begin with Seth’s comments.
    His main point is that my off-hand remarks about about efficient market hypothesis (EMH) and derivative models are wrong. It’s sort of off-topic to the review
    (1)Seth says derivative models work well, but people want to blame them. The models pricing housing derivatives had very wrong assumptions about the expected rate of default. Means the model was wrong. At a more abstract level, Michael Lewis’s The Big Short explains how some investors were able to exploit a flawed assumption in the usual Black-Scholes derivative pricing model–to make billions. (Pages 113-116). I’m assuming these mistakes have been corrected; but they were clearly mistakes.

    2. EMH, Seth says, is good at predictions *in domains where it can make predictions*. i don’t feel like debating this in comments, but I’ll just point out a lot about EMH is contestable, comes in several forms, and has been criticized for its wrongness by many sources. http://en.wikipedia.org/wiki/Efficient-market_hypothesis

    3. Seth’s comment going to the book which he has NOT read is one that loses me. He speculates that the argument must be circular: “boiling it down to something like innovators innovate when there is an environment that encourages innovation).”
    She specifying what kind of environment encourages innovation. If someone wrote a book saying “educators can educate in conditions that encourage education” that’d be circular; but if they specify those conditions encouraging education, it’s a major contribution.

    I don’t really have time to go back and forth on such things if Seth doesn’t have the time to read the book.

    As for A.J.’s comments, I think #2 is interesting (the desirability of economic growth is contestable; i think the consensus is “for”); and #3 is also interesting (some uses of the Internet are more valuable than others). But #1 I think is interesting but not super useful–it’d be hard to look at all the companies that failed, and I’m not sure that’s necessary. She’s contrasting open platforms and controlled platforms; she shows many of the biggest successes are very unlikely in a controlled platform because they were accidental etc. It’s true that some companies that failed, of the 99%, may have succeeded in a controlled environment. (Is that your point? She should show the benefits of a closed platform by looking at the 99% that failed and determine which were likely to succeed in a closed platform?) Maybe, with a closed platform Friendster would still reign. Google Wave would have succeeded, Pets.com would the world’s most popular website.

    And, though I’m referencing Pets.com, I don’t mean to be snarky–some of your points are very interesting, and am curious what you think the better way to address that chapter would be. That chapter isn’t conclusive, but it’s helpful evidence I think.

  4. A.J. Sutter says:

    Marvin, thanks for your response. My point in #1 is simpler: coming up with an ex-post narrative that purports to explain the success of a few well-known companies isn’t coming up with a predictive model. For one thing, one can often find a set of characteristics Q common to all members of some set of famous successful companies S; the issue is whether some other companies with characteristics Q failed. If so, that would at least negate Q as a sufficient explanation of the success of S, in which case one wouldn’t be able to “predict” success. For another, even if one could show a strong correlation in a huge sample of start-ups between success and Q, that wouldn’t necessarily show that Q explained the success. BvS’s book, like most business books and all too many PowerPoint pitches (I speak as a former Silicon Valley corporate VC), (i) tend to reason only from the most salient and easily visible characteristics of the most salient and famous cases, and (ii) have a vested interest to find some “common factor” to explain success. That often leads to fallacious attributions of causation.

    On point #2, you’re right about the consensus, which is why I call her position conventional. My point being that, at least for rich countries like the US, most arguments in favor of continuing GDP growth into the future fail when examined critically, which they rarely are. So too, BTW, do arguments linking innovation and growth. Here are some GDP growth rates for a few countries, expressed as pairs (20-year average, 10-year average) for periods through 2009: Qatar (8.6%, 11.2%), China (8.6%, 10.6%), Ethiopia (5.0%, 7.0%), Uzbekistan (3.0%, 6.3%), Bangladesh (5.3%, 5.9%), Israel (4.3%, 3.4%), USA (2.6%, 2.2%), Japan (1.3%, 0.69%). (Source of underlying data: Groningen Total Economy Database TEDI_2010).

    On the question of a better way to frame the chapter, I appreciate your asking, but I confess I’m not at all expert in this field. My comments are based simply on thinking critically about whether BvS’s arguments (or the claims made therefor in the review) were supported, and I can’t pretend to suggest an alternative constructive argument, other than my point about a political rather than an economics POV.