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Chapter 9

PSY342H1 Chapter Notes - Chapter 9: Expected Utility Hypothesis, Loss Aversion, Risk Aversion

Course Code
Ari Silburt

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Chapter 9 - Decision Making
Decision is a choice among possibilities.
Decision making involves assessment of all the courses of action available and determination
of the action to take that will lead to the best consequences.
A decision occurs when a person with an unfulfilled need takes an action to satisfy that need
or desire and often person does that all the relevant information in hand
For all decisions two factors are critical:
i. Value of action to us
ii. The likely outcome
Science of Decision Making
One way to make a decision is to weigh out the pros and cons of each alternative
Normative/Prescriptive theories are the theories that tell us what we SHOULD do. They
also made use of previous actual human behaviour because it is believed that from an
evolutionary point of view humans try to make the best possible rational decision
Descriptive theories focus on how we actually make decisions and not on we should make
them. They work to increase the understanding of decision making. They also help explain
how human behaviour often departs from rationality and help predict the decisions of
Most research in decision making comes from the area of gambling where one is not sure
about the outcome of the alternatives and strives to choose the best possible alternative that
will maximize the profit
Cognitive activity in decision making involves evaluation of each possible choice (what do I
want) and the determination of the one that makes us most likely to achieve a goal (What are
the pros and cons)
The Decision Tree
Decision Tree is a graphical display that represents the courses of action or options
available, the probability of the outcome and the consequences of each action
Often in decision making one of the alternatives is relatively more risky and there is higher
uncertainty about the outcome
Decision tree defines alternatives, beliefs (about likelihoods) and consequences ABCs of
i. Alternatives are different courses of action, options, choices and strategies available
to the decision maker and they are represented as branches of the tree. Usually there
are large number of alternative but for the sake of decision making, they are narrowed
down as much as possible. The discovery and articulation of the alternatives involves
problem solving
ii. Belief is an estimate of the likelihood that a particular outcome will occur if we
choose a particular alternative. The goal of decision making is to have the decision
make think more rationally, so information about beliefs is added to the tree in the
form of numerical probabilities of the occurrence of an event (payoff) although in
real life we cannot define exact probability of an event
iii. Consequences are the benefits of losses that you receive or experience from the
choice of a particular alternative and the events that follow from that choice. It is
defined in terms of outcomes, values, or utilities:
a) Outcome is the result
b) Value is its net worth
c) Utility is the desirability of the value to you
Since the evaluation depends on personal goals and values, consequences of a decision
are subjective. It is important to look at the consequences from the decision maker’s point
of view i.e. in terms of utility. Mathematical probability rules do not people’s natural
judgements, therefore, it is important to have psychologically descriptive model e.g.
expected utility model
Rational Decision Making: The Expected Utility Model
Expected utility is the utility (desirability) of a particular outcome weighed by the likelihood
of that outcome’s occurring
Expected utility model assumes rational behaviour from a decision maker in
i. Evaluating the likelihoods of alternatives
ii. Assessing the consequences
iii. Assigning utilities (utilities do not have to add up to 1)
iv. Multiplying utilities by the likelihoods (probabilities that add up to 1)
v. Choosing the option with the highest expected utility
The utility of an outcome is entirely subjective i.e. the objective worth does not matter, what
matters in what is important to the decision maker
How the Model Works
Formal decision theory is the form of (subjective) expected utility model proposed that we:
i. Evaluate each course of action by multiplying utility of consequence and probability
of the occurrence of the consequence which gives the expected utility
Expected utility = p (x) * u (x)
ii. Add the weighted values the expected utilities to create a summary of evaluation
of each alternative
Expected utility = ∑ p (x) * u (x)
iii. Choose the course of action with the highest expected utility. Maximizing utility is
the core of a rational decision.
In terms of gambling, often there is a penalty if the bet is not won and in that case we must
include the downside i.e.
Expected value = (Probability of winning * Payoff) (Probability of losing * Amount of loss)
Expected utility Model and Behavioral Research
Expected utility model was tested in context of gambling where alternative were the
monetary gain or losses, likelihood was the probability of losing or winning and
consequences were the payoffs.
Participants were asked to sell the gambles. 3 patterns were observed:
i. As the gamble increased in the amount of payoff, the sellers increased their selling
price since there was a possibility (low that may be but..) of the other person gaining
more from the bet.
ii. As the probability of winning increase, sellers increases their selling price since there
were higher chances of the other person gaining more from the bet
iii. There was a clear fan pattern indicating that participants made the calculation of
value = probability * utility
Variance was also observed in decision making. There were variance preferences/risk
i. Risk averse prefer certain gains where possible payoffs vary within a small range
ii. Risk seeking prefer high potential gains and high potential losses.
iii. Loss aversion refers to the people who avoid a gamble with any potential loss
outcome regardless of variance or expected value
Utility curves are sigmoidal graphs that relate the subjective evaluation (i.e. utility on y axis)
to an objective measure on x-axis. It shows marginal utility i.e. change in utility as a
function of relative payoff. 3 patterns are visible:
i. Diminishing utility effect was observed in gains since initially gains carry a lot of
value i.e. utility and more gains have a higher value. But, there comes a point when
additional gains become less valued than the same amount of earlier gains
ii. Similar diminishing utility effect was observed in losses where initial loss hurts a lot
but the pain diminishes as losses accumulate.
iii. The degree of curvature of gain and loss functions correspond to risk attitudes. On
the gain side, the shape of the graph was concave which implies risk aversion and
shows that when it comes to gains, people prefer the sure thing. On the loss side, the
shape of the graph was convex which implies that when it comes to losing, people
would rather choose the risk seeking strategy where they have a chance of losing
iv. The slope of the loss section of the curve was much steep than the gain portion while
shows that losses hurt twice as much as gains please. E.g. if there is a chance of
winning $200 and losing $100, people will not play the bet although the expected
utility is higher for the gains but loss hurts twice as more.