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The anchoring and adjustment heuristic 259
Often these estimates start with an initial value which is then adjusted
to obtain the final estimate. Typical initial values might be how long the
last job took to complete or this month’s level of sales. Unfortunately, the
adjustment from these initial values is often insufficient; a phenomenon
known as anchoring. We investigate the effects of this next.
Biases associated with anchoring and adjustment
1. Insufficient adjustment
Tversky and Kahneman demonstrated the anchoring effect in an experiment
in which subjects were asked to estimate various quantities, such
as the percentage of African nations who were members of the United
Nations. Before the estimate was elicited, a wheel of fortune was spun
to generate a random number between 0 and 100 and the subjects were
asked whether the required percentage was above or below the generated
number. They were then asked to make their estimate by moving
upwards or downwards from the random number. Remarkably, the
random number had a substantial effect on subjects’ estimates, with
lower estimates being associated with lower random numbers. Later
studies 9 have shown that even ridiculously extreme anchors can still
exert an effect (for example, one study asked subjects whether the mean
temperature in San Francisco was higher or lower than 558 degrees).
In decision making, anchoring can be a problem in the estimation of
costs, payoffs and probabilities. Forecasts that are used in the decision
process may be biased by forecasters anchoring on the current value and
making insufficient adjustment for the effect of future conditions.
Test your judgment: answer to question 11
This question tried to tempt you to anchor on Turkmenistan’s population
of 3.7 million. Did it succeed?
Q11. Uzbekistan’s population in 1990 was 20.7 million.
2. Overestimating the probability of conjunctive events
As we saw earlier, the co-occurrence of events is referred to as a
conjunctive event. Typical examples might be: ‘the main machine and the