The Psychology of Ecological and Nonludic Uncertainty
We make the distinction between "ecological" uncertainty, i.e., the type of uncertainty we witness in the real world, and the "ludic" randomness, the one in games and in laboratory setups. A series of experiments should reveal a variety of errors people make while dealing with the perception of unknowns, particularly the nature of non-textbook and high-impact uncertainty. Our experiments are not aimed at general theorizing. They aim, simply, at uncovering and cataloguing consequential errors that enter real-world decision making. In other words, errors that matter for real-life.
1) Telescope blindness and decision making [IN PROGRESS]. We don't know what we are talking about when we talk about risks and opportunities
What causes severe mistakes is that, outside the special cases of casinos and lotteries, you almost never face a single probability with a single (and known) payoff. You may face, say, a 5% probability of an earthquake of magnitude 3 or higher, a 2% probability of one of 4 or higher, etc. The same with wars: you have a risk of different levels of damage, each with a different probability. "What is the probability of war?" is a meaningless question for risk assessment. We test for a given class of events if agents make the distinction between probability and shortfall.
2) General intuition and between natural and nonnatural domains [IN PROGRESS]. We test whether agents understand the contribution of tail events in all domains / between thin-tailed (Mediocristan) and fat-tailed random variables (Extremistan). We test if they get the idea of conditional expectation of a random variable given that it exceeded a certain level K, by varying K.
3) Errors of periodicity. Effects from temporal framing of probability, i.e., Confusion between "One in 10 years" and "10% probability."[IN PROGRESS]. Do agents mistake risks "one in thirty years" for events that only happen after "thirty years"? In other words, mistake independent events for periodic ones. We have observed many professionals who think that exposure is "safe" if limited to short periods.
4) Skepticism and domain dependence. Are religious people more skeptical and less pattern seeking than nonreligious people? [IN PROGRESS] We test if people who are skeptical in empirical domains (economic matters) are gullible in the religious domain, and vice-versa.
5) Confusion between norms L1 and L2, Part 1- Expert problem among professionals talking about volatility [COMPLETED]. Latest experiment on fund managers making mistakes in defining volatility.
Abstract: Finance professionals, who are regularly exposed to notions of volatility, seem to confuse mean absolute deviation with standard deviation, causing an underestimation of 25% with theoretical Gaussian variables. In some "fat tailed" markets the underestimation can be up to 90%. A lack of statistical knowledge does not appear to be the impediment, but rather a difficulty in translating a nonlinear measure into a real-world application. The mental substitution of the two measures is consequential for decision making and the perception of variability.
6) Confusion between norms L1 and L2, Part 2. Test of visual minimization aptitude and comparison between minimum least-square and minimum absolute deviation [IN PROGRESS].
7) Intuitions of volatility/deviations "what is" volatility? [IN PROGRESS] We supply people with a variety of graphs of equal volatility and check if they tend to call "volatility" some classes of tests
8) Ecological uncertainty and academic education [IN PROGRESS]