Mind Matters Natural and Artificial Intelligence News and Analysis

TagJohn Maynard Keynes

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Decreasing and increasing graph on chalkboard

The Cult of Statistical Significance — and the Neglect of Oomph

Statistical significance has little meaning when separated from practical importance

A central part of John Maynard Keynes’ explanation of the Great Depression was his assertion that household income affects household spending. When people lose their jobs and income, they cut back on their spending, which causes other people to lose their jobs and their income — propelling the economy downhill. Keynes’ theory was based on logic and common sense. It was later tested empirically with household survey data and with national income data compiled by the National Bureau of Economic Research. Figure 1 shows U.S. after-tax personal income and consumer spending for the years 1929 through 1940. Since income and spending both tend to grow over time along with the population, the data were converted to annual percentage changes. The observed statistical…

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man hand bitcoin

Using Benford’s Law to Detect Bitcoin Manipulation

Market prices are not invariably equal to intrinsic values

For a while, there was a popular belief among finance professors that the stock market is “efficient” in the sense that stock prices are always correct — the prices that an all-knowing God would set. Thus, investors can buy any stock, even a randomly selected stock, and be confident that they are paying a fair price. This belief was based on seemingly overwhelming evidence that changes in stock prices are difficult to predict. Efficient market enthusiasts argued that if stock prices are always correct, taking into account all currently available information, then any changes in stock prices must be due to new information which, by definition, is impossible to predict. Therefore, the evidence that changes in stock prices are hard to…

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Space and Galaxy light speed travel. Elements of this image furnished by NASA.

No Free Lunches: Bernoulli is Right, Keynes is Wrong

What the Big Bang teaches us about nothing

Jacob Bernoulli made a now obvious observation about probability over three-and-a-half centuries ago: If nothing is known about the outcome of a random event, all outcomes can be assumed to be equally probable. Bernoulli’s Principle of Insufficient Reason (PrOIR) is commonly used. Throw a fair die. There are six outcomes, one for each face of the cube. The chance of getting five pips showing on the roll of a die is therefore one sixth. If a million lottery tickets are sold and you buy one ticket, the chances of winning are one in a million. This reasoning is intuitively obvious.  The assumption about the die is wrong if the die is loaded. But you don’t know that. You know nothing. So Bernoulli’s PrIOR…

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Nerd with glasses hacking websites

Beware of Geeks Bearing Formulas—It’s Often Pseudoscience

Pseudoscience based on data without theory and theory without data undermine the credibility of real science, which is the key to human progress

Elsewhere I have warned of the perils of making decisions based on data without theory. For example, the patterns discovered by data-mining computer algorithms are often nothing more than meaningless coincidences. It is also perilous to go to the opposite extreme—to make decisions based on theory without data. Once upon a time, for example, economists were fond of sketching labor demand and supply curves and assuming that the economy was at their intersection. That is, labor demand is equal to supply, so that everyone who wants to work is working. The unemployed have chosen to be unemployed because they value leisure more than income. True believers were fond of this theory and little troubled by reality. Between 1929 and 1933,…