5. Experimental and behavioural economics
A. Knowledge & Comprehension
1. According to Tversky and Kahneman (1974) how do people assess the probability of an
uncertain event or the value of an uncertain quantity? In your answer, use and explain the
concept of heuristics.
‘People rely on a limited number of heuristic principles which reduce the complex tasks of
assessing probabilities and predicting values to simpler judgmental operations. In general,
these heuristics are quite useful, but sometimes they lead to severe and systematic errors’
It depends on physical quantities like distance and size.
People use common ideas to determine the event or value of the quantity by using the
concept of heuristics, which are sort of (common) rules they follow to make the decision
easier and more quick.
2. What are biases, and when do they occur?
Biases are opinions made up before the situation is known, these occur mostly when
information is incomplete.
Biases are systematic mistakes that can occur from misapplied heuristics. They occur when
events are uncertain (more risky), complex or extreme. Decision has to be made quick or
without too much energy.
3. What is the first heuristic that Kahneman and Tversky (1974) discuss and to what kind of
biases could it lead?
It’s called ‘Representativeness’; (text; ) ‘probabilities are evaluated by the degree to which A
is representative of B, that is, by the degree to which A resembles B’. So that means, to what
extent A can be compared with B. Biases arise because several factors that should affect
judgments of probability are not taken into account by this heuristic.
- Insensitivity to prior probability of outcomes (how big is the chance something is A or B
when there are much more from one group)
- Insensitivity to sample size (when people don’t take the different sizes of a group into
account)
- Misconceptions of chance (when there’s a 50-50% chance and red has been on for a
while, people tend to think the next will be black, although there again is just another
chance of 50-50%)
- Insensitivity to predictability (when a prediction is made more positive to favor and
evidence is neglected) (the higher the predictability, the wider the range of predicted
values)
- The illusion of validity (the unwarranted confidence which is produced by a good fit
between the predicted outcome and the input information )
- Misconceptions of regression (when you select only the good ones out of the first group,
the results in the next test will be lower to your expectation)
4. Briefly summarise the second and third heuristics mentioned in this paper.
Availability:
How frequently a situation occurs to predict something and base your choice on that.
Biases that arise are due to the retrievability of instances (how easy is information about the
group accessible), biases due to the effectiveness of a search set (how easy it is to imagine or
think of a situation), biases of imaginability and illusory correlation.
Adjustment and Anchoring:
A. Knowledge & Comprehension
1. According to Tversky and Kahneman (1974) how do people assess the probability of an
uncertain event or the value of an uncertain quantity? In your answer, use and explain the
concept of heuristics.
‘People rely on a limited number of heuristic principles which reduce the complex tasks of
assessing probabilities and predicting values to simpler judgmental operations. In general,
these heuristics are quite useful, but sometimes they lead to severe and systematic errors’
It depends on physical quantities like distance and size.
People use common ideas to determine the event or value of the quantity by using the
concept of heuristics, which are sort of (common) rules they follow to make the decision
easier and more quick.
2. What are biases, and when do they occur?
Biases are opinions made up before the situation is known, these occur mostly when
information is incomplete.
Biases are systematic mistakes that can occur from misapplied heuristics. They occur when
events are uncertain (more risky), complex or extreme. Decision has to be made quick or
without too much energy.
3. What is the first heuristic that Kahneman and Tversky (1974) discuss and to what kind of
biases could it lead?
It’s called ‘Representativeness’; (text; ) ‘probabilities are evaluated by the degree to which A
is representative of B, that is, by the degree to which A resembles B’. So that means, to what
extent A can be compared with B. Biases arise because several factors that should affect
judgments of probability are not taken into account by this heuristic.
- Insensitivity to prior probability of outcomes (how big is the chance something is A or B
when there are much more from one group)
- Insensitivity to sample size (when people don’t take the different sizes of a group into
account)
- Misconceptions of chance (when there’s a 50-50% chance and red has been on for a
while, people tend to think the next will be black, although there again is just another
chance of 50-50%)
- Insensitivity to predictability (when a prediction is made more positive to favor and
evidence is neglected) (the higher the predictability, the wider the range of predicted
values)
- The illusion of validity (the unwarranted confidence which is produced by a good fit
between the predicted outcome and the input information )
- Misconceptions of regression (when you select only the good ones out of the first group,
the results in the next test will be lower to your expectation)
4. Briefly summarise the second and third heuristics mentioned in this paper.
Availability:
How frequently a situation occurs to predict something and base your choice on that.
Biases that arise are due to the retrievability of instances (how easy is information about the
group accessible), biases due to the effectiveness of a search set (how easy it is to imagine or
think of a situation), biases of imaginability and illusory correlation.
Adjustment and Anchoring:
