Heuristics: Anchoring Pt.1

In this article, we will look at one of the main heuristics explored in behavioural economics – anchoring. We will see how it occurs, its implications and its uses over the coming articles on this topic.

Anchoring when guessing involves using another concept, statistic or idea as a base reference when deciding an estimate for something. For example, if you knew that the average lifespan of a dog is around ten years and was told to guess that of a cat, you can use that figure of 10 years as an anchor and estimate slightly above or below this value. The actual average lifespan of a cat is roughly 12 years, so using this anchor would have helped dramatically as opposed to guessing randomly. The process, also known as ‘anchoring and adjustment’, is where you start with some anchor and adjust your answer to be either larger or smaller depending on which way you think is appropriate. However, this could also create a problem if the anchor used may be assumed to be similar but turns out to be extremely far from the true answer and can lead to irrational choices and a negative outcome for the individual. One example of anchoring leading to the wrong result is in a study where visitors at the San Francisco Exploratorium were asked the following two questions[1]:

‘Is the height of the tallest redwood tree more or less than 1200 feet? What is your best guess about the height of the tallest redwood tree?’

One group was asked this exact set of questions, while another was given the questions with 180 feet instead of 1200. The scenario established was with one group having the ‘high anchor’ of 1200 feet and the other having the ‘low anchor’ of 180 feet. After taking in and collating the responses, the two groups produced very different mean estimates. The ‘high anchor’ of 1200 led to an average guess of 844 feet, whereas in the group with the ‘low anchor’ of 180, the average was 282 feet – a difference of 562. If this difference were represented in a ratio to the difference between the anchors (1020), you would get a ratio of 0.55. As a percentage, this would be 55%, evidencing the deep-rooted influence anchors have even if the individual does not realise it. Another study showing the power of random anchors demonstrated it in a relatively disturbing and unsettling way. German judges, each with experience exceeding at least 15 years in service, first read a description of a woman who had been caught shoplifting.[2] They were then instructed to roll weighted dice that were loaded to only land on either a three or a nine. As soon as the dice stopped moving and the result was read, the judges were asked whether they would sentence the woman to a term in prison greater or lesser than the outcome in months. Finally, they were asked to specify the exact prison sentence they would give to the shoplifter. On average, the judges with a dice outcome of nine suggested a penalty of 8 months, while those with a result of three only proposed a charge of 5 months. In this case, the anchoring effect was 50%, despite being in a serious and high stakes pretence where any biases, whether intentional or unconscious, can damage lives and lead to extended suffering and punishment.

To test this idea first hand, we created a Google Form and conducted our own study to try and replicate such results. One of the questions asked was the following:

‘The average lifespan of a horse is roughly 20 years. What do you think the average lifespan of an African elephant is?’

The anchor, in this case, was the lifespan of a horse, which I gave as around 20 years, while the lifespan of an African elephant ranged between 70-80 years. We hypothesised that by providing the much shorter lifespan of the horse before asking the subject to estimate the lifespan of an elephant, the horse’s lifespan would act as an anchor from which individuals would then adjust upwards to decide their guess. Therefore, we predicted that the majority of participants would guess a value within 1.5 times more than the horse’s lifespan (i.e. they would think below 50), with very few guessing the correct value. So far, there have been 44 responses to the form. For that particular question, only 5 participants out of the total 44, or around 11%, estimated the average lifespan of an African elephant correctly. Thirty-seven of the participants, or 84%, guessed below the answer of 70, and more specifically, 32 or 73% had an estimate below our prediction of 50. This is more than enough to qualify as a majority, meaning our prediction that the majority of participants would guess below 1.5 times the anchor was true. Thus, there is sufficient evidence to accept our hypothesis that giving a low anchor can influence estimates and lead to results significantly below the proper answer.

[1] ‘Thinking, Fast and Slow’, Pages 123-124 – Daniel Kahneman, 2011

[2] ‘Thinking, Fast and Slow’, Pages 125-126 – Daniel Kahneman, 2011


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