Monday, December 19, 2016

Prediction: Trump Presidency Part I

Is it reasonable to expect that the person who most attracted us when we were single will dazzle us as a wife and mother?  (Credit for Picture)
The short answer:  Trump's presidency will match the long-term averages for the erosion civil liberties as enumerated in the Bill of Rights, increasing complexity of regulations, an overall increasing in dependency and loss of personal agency, defining more "protected classes", immigration, technology and all other major metrics.  By long-term, I propose using the period between December 23, 1913 and the present.  Note that the Federal Reserve was founded on December 23, 1913.

From Judgement under Uncertainty: Heuristics and Biases by Amos Tversky and Daniel Kahneman

(A common cause of error in decisions is due to decision maker's...) Insensitivity to predictability.  People are sometimes called upon to make such numericaql predictions as the future value of a stock, the demand for a commodity, or the outcome of a football game.  Such predictions are often made by representativeness.  For example, suppose one is given a description of a company and is asked to predict its future profit.  If the description of the company is very favorable, a very high profit will appear most representative of that description;  if the description is mediocre, a mediocre performance will appear most representative.  The degree to which the description is favorable is unaffected by the reliability of that description or by the degree to which it permits accurate prediction.  Hence, if people predict solely in terms of the favorableness of the description, their predictions will be insensitive to the reliability of the evidence and to the expected accuracy of the prediction.
You can quibble about starting points and how steep the arrow should be...but it is clearly going up.
This mode of judgement violates the normative statistical theory in which the extremeness and range of predictions are controlled by considerations of predictability.  When predictability is nil, the same prediction should be made in all cases.  For example, if the descriptions of the companies provide no information relevant to profit (example, the competitive environment), then the same value (such as average profit) should be predicted for all companies.....

Several studies of numerical prediction have demonstrated that intuitive predictions violate this rule, and that subjects show little or no regard for considerations of predictability.  In one of the studies, subjects were presented with several paragraphs, each describing the performance of a student teacher during one particular practice session.  Some of the subjects were asked to evaluate the quality of the lesson described in the paragraph in percentile scores, relative to the specified population.  Other subjects were asked to predict, also as a percentile score, the standing of each student teacher five years after the practice session.  The judgments made under the two conditions were identical.  That is, the prediction of a remote criterion (success of a teacher after five years) was identical to the evaluations...The students who made these predictions were undoubtedly aware of the limited predictability of teaching competence on the basis of a single trial five years earlier; never-the-less, their predictions were as extreme as their evaluations.

Federal debt was so small that it was not even worth plotting before 1966.  I doubt that the generations not yet born and future immigrants will feel honor bound to service the debts we are incurring today.

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