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Econometric disillusionment

from Lars Syll

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Because I was there when the economics department of my university got an IBM 360, I was very much caught up in the excitement of combining powerful computers with economic research. Unfortunately, I lost interest in econometrics almost as soon as I understood how it was done. My thinking went through four stages:

1. Holy shit! Do you see what you can do with a computer’s help.
2. Learning computer modeling puts you in a small class where only other members of the caste can truly understand you. This opens up huge avenues for fraud:
3. The main reason to learn stats is to prevent someone else from committing fraud against you.
4. More and more people will gain access to the power of statistical analysis. When that happens, the stratification of importance within the profession should be a matter of who asks the best questions.

Disillusionment began to set in. I began to suspect that all the really interesting economic questions were FAR beyond the ability to reduce them to mathematical formulas. Watching computers being applied to other pursuits than academic economic investigations over time only confirmed those suspicions.

1. Precision manufacture is an obvious application for computing. And for many applications, this worked magnificently. Any design that combined straight line and circles could be easily described for computerized manufacture. Unfortunately, the really interesting design problems can NOT be reduced to formulas. A car’s fender, for example, cannot be described​ using formulas—it can only be described by specifying an assemblage of multiple points. If math formulas cannot describe something as common and uncomplicated as a car fender, how can it hope to describe human behavior?
2. When people started using computers for animation, it soon became apparent that human motion was almost impossible to model correctly. After a great deal of effort, the animators eventually put tracing balls on real humans and recorded that motion before transferring it to the animated character. Formulas failed to describe simple human behavior—like a toddler trying to walk.

Lately, I have discovered a Swedish economist who did NOT give up econometrics merely because it sounded so impossible. In fact, he still teaches the stuff. But for the rest of us, he systematically destroys the pretensions of those who think they can describe human behavior with some basic Formulas.

Jonathan Larson


  1. Benjamin Morgentau
    March 10, 2018 at 7:48 am

    … really how enlightening this is to read and the list of failures this irresponsibility of packing all our existence into bits and bites and passing control we once had over our lifes not only into algorithms, no we managed to but them into free markets as well, no we are forced to accept the output without question, not yet understood by most, brought over all of us in the mist of a cloud of even less understood dimensions… there is always some thing standing out in the sorting of a spreadsheet we can base our decisions on.

    …i tried everything possible to go forward and take back the last remains of a still wonderful analog life… for example the joy of analog designs, architecture, environment, forms for like everything once drawn and done by hand and emotions. Here in Switzerland the debate is still ongoing at which age our children should be forced to learn with tablets instead of pencil and paper.

    Will we let them understand what it means to design a fender by hand or do we force them into the (in)efficiencies of liberalised markets?

  2. March 10, 2018 at 1:51 pm

    It seems to me that both the analogue and the digital can be important for developing many manufactured items; they need not be mutually exclusive. There’s a kind of joy in doing something by hand (literally) that does not occur in the digital (which has its own joys). When I found out that algorithms were used by banks to gain advantage over other users of stock market transactions, I too became disillusioned. Algorithms do not bode well for the development of artificial intelligence unless human intelligence is given its due at one and the same time.

  3. March 10, 2018 at 7:02 pm

    Mystical dualism. It’s not that economics depends on some magical “soul” or “essence” that is beyond this world. It’s rather that economists applied a crude first order approximation and claimed, plainly falsely, to have modeled the phenomenon. Like food scientists who make a substance with the first harmonic of strawberry or orange juice and then pass it off as the real thing. Economics is not beyond modeling, you just did it badly.

    • Frank Salter
      March 10, 2018 at 7:38 pm

      Absolutely true!

      I feel that “first order approximation” may be overly kind. Generally, it is a mere equation, fitted to some data, for which the author claims “it is theory” — despite the equations failing every test of scientific validity.

      That elementary errors, in science and mathematics are allowed, not merely to stand, but to be promulgated repeatedly, may be seen as wilful ignorance. However, I do not know how to describe what the terms are, for repeatedly continuing with the same wrong analysis despite its having been 𝘱𝘳𝘰𝘷e𝘯 wrong — that is 𝘯𝘰𝘵 doing it badly! It is several orders of magnitude worse.

  4. March 12, 2018 at 3:08 am

    The disillusionment experiences described seem, in my view about balance and boundaries. Lars’ website notes, “Observation and experiment: an introduction to causal inference— is a well-written introduction to some of the most important and far-reaching ideas in modern statistics. With only a minimum of mathematics, the author manages to give a lively and interesting account of how statisticians try to use statistics to make causal inferences from observational studies and experiments.” The book never pretends that economics or other aspects of human culture can be reduced to formulas. It recognizes this is not possible. But it is possible to make inferences from observational studies and experiment using statistics. This is one facet of human culture. A facet that fits within the borders of statistics. Other aspects of human culture fall beyond these borders. Knowing when its suitable to use statistics and when it is not, is one key to becoming a mature and effective social scientist.

    • Rob Reno
      March 12, 2018 at 3:47 am

      Well said Ken, I really appreciate your thoughtful comments such as this.

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