Apologies for intruding with this question, but I can't think
of any group that might have more concrete information relevant
to my current research.
Enclosed below is an announcement of a paper on technology bubbles.
It is based largely on the Internet bubble of a decade ago, and
concentrates on the "Internet traffic doubling every 100 days" tale.
As the paper shows, this myth was perceived in very different ways
by different people, and this by itself helps undermine the foundations
of much of modern economics and economic policy making.
To get a better understanding of the dynamics of that bubble, to assist
in the preparation of a book about that incident, I am soliciting information from anyone who was active in telecom during that period. I would particularly like to know what you and your colleagues estimated Internet traffic growth to be, and what your reaction was to the O'Dell/Sidgmore/WorldCom/UUNet myth. If you were involved in the industry,
and never heard of it, that would be extremely useful to know, too.
Ideally, I would like concrete information, backed up by dates, and possibly
even emails, and a permission to quote this information. However, I will
settle for more informal comments, and promise confidentiality to anyone
who requests it.
Bubbles, gullibility, and other challenges for economics,
psychology, sociology, and information sciences
School of Mathematics
and Digital Technology Center
University of Minnesota
Preliminary version, August 5, 2010
Gullibility is the principal cause of bubbles. Investors and the general public get snared by a "beautiful illusion" and throw caution to the wind. Attempts to identify and control bubbles are complicated by the fact that the authorities who might naturally be expected to take action have often (especially in recent years) been among the most gullible, and were cheerleaders for the exuberant behavior. Hence what is needed is an objective measure of gullibility.
This paper argues that it should be possible to develop such a measure. Examples demonstrate, contrary to the efficient market dogma, that in some manias, even top-level business and technology leaders do fall prey to collective hallucinations and become irrational in objective terms. During the Internet bubble, for example, large classes of them first became unable to comprehend compound interest, and then lost even the ability to do simple arithmetic, to the point of not being able to distinguish 2 from 10. This phenomenon, together with advances in analysis of social networks and related areas, points to possible ways to develop objective and quantitative tools for measuring gullibility and other aspects of human behavior implicated in bubbles. It cannot be expected to infallibly detect all destructive bubbles, and may trigger false alarms, but it ought to alert observers to periods where collective investment behavior is becoming irrational.
The proposed gullibility index might help in developing realistic economic models. It should also assist in illuminating and guiding decision making.