Chapter 5
Uncertainty and Consumer
Behavior
Topics to be Discussed
 Describing Risk
 Preferences Toward Risk
 Reducing Risk
 The Demand for Risky Assets
©2005 Pearson Education, Inc.
Chapter 5
2
Introduction
 Choice with certainty is reasonably
straightforward.
 How do we make choices when certain
variables such as income and prices are
uncertain (making choices with risk)?
©2005 Pearson Education, Inc.
Chapter 5
3
Describing Risk
 To measure risk we must know:
1. All of the possible outcomes.
2. The probability or likelihood that each
outcome will occur (its probability).
©2005 Pearson Education, Inc.
Chapter 5
4
Describing Risk
 Interpreting Probability
1. Objective Interpretation

Based on the observed frequency of past
events
2. Subjective Interpretation

Based on perception that an outcome will
occur
©2005 Pearson Education, Inc.
Chapter 5
5
Interpreting Probability
 Subjective Probability
Different information or different abilities to
process the same information can influence
the subjective probability
Based on judgment or experience
©2005 Pearson Education, Inc.
Chapter 5
6
Describing Risk
 With an interpretation of probability
must determine 2 measures to help
describe and compare risky choices
1. Expected value
2. Variability
©2005 Pearson Education, Inc.
Chapter 5
7
Describing Risk
 Expected Value
The weighted average of the payoffs or
values resulting from all possible outcomes.
 Expected
value measures the central tendency;
the payoff or value expected on average.
©2005 Pearson Education, Inc.
Chapter 5
8
Expected Value – An Example
 Investment in offshore drilling exploration:
 Two outcomes are possible
Success – the stock price increases from
$30 to $40/share
Failure – the stock price falls from $30 to
$20/share
©2005 Pearson Education, Inc.
Chapter 5
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Expected Value – An Example
 Objective Probability
100 explorations, 25 successes and 75
failures
Probability (Pr) of success = 1/4 and the
probability of failure = 3/4
©2005 Pearson Education, Inc.
Chapter 5
10
Expected Value – An Example
EV  Pr(success )(value of success)
 Pr(failure )(value of failure)
EV  1 4 ($40/share )  3 4 ($20/share )
EV  $25/share
©2005 Pearson Education, Inc.
Chapter 5
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Expected Value
 In general, for n possible outcomes:
Possible outcomes having payoffs X1, X2, …
Xn
Probabilities of each outcome is given by
Pr1, Pr2, … Prn
E(X)  Pr1X 1  Pr 2 X 2  ...  Pr n X n
©2005 Pearson Education, Inc.
Chapter 5
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Describing Risk
 Variability
The extent to which possible outcomes of an
uncertain even may differ
How much variation exists in the possible
choice
©2005 Pearson Education, Inc.
Chapter 5
13
Variability – An Example
 Suppose you are choosing between two
part-time sales jobs that have the same
expected income ($1,500)
 The first job is based entirely on
commission.
 The second is a salaried position.
©2005 Pearson Education, Inc.
Chapter 5
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Variability – An Example
 There are two equally likely outcomes in
the first job--$2,000 for a good sales job
and $1,000 for a modestly successful
one.
 The second pays $1,510 most of the time
(.99 probability), but you will earn $510 if
the company goes out of business (.01
probability).
©2005 Pearson Education, Inc.
Chapter 5
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Variability – An Example
Outcome 1
Outcome 2
Prob.
Income
Prob.
Income
Job 1:
Commission
.5
2000
.5
1000
Job 2:
Fixed Salary
.99
1510
.01
510
©2005 Pearson Education, Inc.
Chapter 5
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Variability – An Example
 Income from Possible Sales Job
Job 1 Expected Income
E(X1 )  .5($2000)  .5($1000)  $1500
Job 2 Expected Income
E(X 2 )  .99($1510)  .01($510)  $1500
©2005 Pearson Education, Inc.
Chapter 5
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Variability
 While the expected values are the same,
the variability is not.
 Greater variability from expected values
signals greater risk.
 Variability comes from deviations in
payoffs
Difference between expected payoff and
actual payoff
©2005 Pearson Education, Inc.
Chapter 5
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Variability – An Example
Deviations from Expected Income ($)
Outcome Deviation Outcome Deviation
1
2
Job
1
$2000
$500
$1000
-$500
Job
2
1510
10
510
-900
©2005 Pearson Education, Inc.
Chapter 5
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Variability
 Average deviations are always zero so
we must adjust for negative numbers
 We can measure variability with standard
deviation
The square root of the average of the
squares of the deviations of the payoffs
associated with each outcome from their
expected value.
©2005 Pearson Education, Inc.
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Variability
 Standard deviation is a measure of risk
Measures how variable your payoff will be
More variability means more risk
Individuals generally prefer less variability –
less risk
©2005 Pearson Education, Inc.
Chapter 5
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Variability
 The standard deviation is written:
  Pr1 X 1  E ( X )
©2005 Pearson Education, Inc.
2
  Pr X
Chapter 5
2
2
 E( X )
2

22
Standard Deviation – Example 1
Deviations from Expected Income ($)
Outcome Deviation Outcome Deviation
1
2
Job
1
$2000
$500
$1000
-$500
Job
2
1510
10
510
-900
©2005 Pearson Education, Inc.
Chapter 5
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Standard Deviation – Example 1
 Standard deviations of the two jobs are:
  Pr1 X 1  E ( X ) 2   Pr2 X 2  E ( X ) 2 
 1  0.5($250,000)  0.5($250,000)
 1  250,000  500
 2  0.99($100)  0.01($980,100)
 2  9,900  99.50
©2005 Pearson Education, Inc.
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Standard Deviation – Example 1
 Job 1 has a larger standard deviation and
therefore it is the riskier alternative
 The standard deviation also can be used
when there are many outcomes instead
of only two.
©2005 Pearson Education, Inc.
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Standard Deviation – Example 2
 Job 1 is a job in which the income ranges
from $1000 to $2000 in increments of
$100 that are all equally likely.
 Job 2 is a job in which the income ranges
from $1300 to $1700 in increments of
$100 that, also, are all equally likely.
©2005 Pearson Education, Inc.
Chapter 5
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Outcome Probabilities - Two Jobs
Job 1 has greater
spread: greater
standard deviation
and greater risk
than Job 2.
Probability
0.2
Job 2
0.1
Job 1
$1000
©2005 Pearson Education, Inc.
$1500
Chapter 5
$2000
Income
27
Decision Making – Example 1
 What if the outcome probabilities of two
jobs have unequal probability of
outcomes
Job 1: greater spread & standard deviation
Peaked distribution: extreme payoffs are less
likely that those in the middle of the
distribution
You will choose job 2 again
©2005 Pearson Education, Inc.
Chapter 5
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Unequal Probability Outcomes
The distribution of payoffs
associated with Job 1 has a
greater spread and standard
deviation than those with Job 2.
Probability
0.2
Job 2
0.1
Job 1
$1000
©2005 Pearson Education, Inc.
$1500
Chapter 5
$2000
Income
29
Decision Making – Example 2
 Suppose we add $100 to each payoff in
Job 1 which makes the expected payoff =
$1600.
Job 1: expected income $1,600 and a
standard deviation of $500.
Job 2: expected income of $1,500 and a
standard deviation of $99.50
©2005 Pearson Education, Inc.
Chapter 5
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Decision Making – Example 2
 Which job should be chosen?
Depends on the individual
Some may be willing to take risk with higher
expected income
Some will prefer less risk even with lower
expected income
©2005 Pearson Education, Inc.
Chapter 5
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Risk and Crime Deterrence
 Attitudes toward risk affect willingness to
break the law
 Suppose a city wants to deter people
from double parking.
 Monetary fines may be better than jail
time
©2005 Pearson Education, Inc.
Chapter 5
32
Risk and Crime Deterrence
 Costs of apprehending criminals are not
zero, therefore
Fines must be higher than the costs to
society
Probability of apprehension is actually less
than one
©2005 Pearson Education, Inc.
Chapter 5
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Risk and Crime Deterrence Example
 Assumptions:
1. Double-parking saves a person $5 in terms
of time spent searching for a parking space.
2. The driver is risk neutral.
3. Cost of apprehension is zero.
©2005 Pearson Education, Inc.
Chapter 5
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Risk and Crime Deterrence Example
 A fine greater than $5.00 would deter the
driver from double parking.
Benefit of double parking ($5) is less than
the cost ($6.00) equals a net benefit that is
negative.
If the value of double parking is greater than
$5.00, then the person would still break the
law
©2005 Pearson Education, Inc.
Chapter 5
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Risk and Crime Deterrence Example
 The same deterrence effect is obtained
by either
A $50 fine with a .1 probability of being
caught results in an expected penalty of $5
 or
A $500 fine with a .01 probability of being
caught results in an expected penalty of $5.
©2005 Pearson Education, Inc.
Chapter 5
36
Risk and Crime Deterrence Example
 Enforcement costs are reduced with high
fine and low probability
 Most effective if drivers don’t like to take
risks
©2005 Pearson Education, Inc.
Chapter 5
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Preferences Toward Risk
 Can expand evaluation of risky
alternative by considering utility that is
obtained by risk
A consumer gets utility from income
Payoff measured in terms of utility
©2005 Pearson Education, Inc.
Chapter 5
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Preferences Toward Risk Example
 A person is earning $15,000 and
receiving 13.5 units of utility from the job.
 She is considering a new, but risky job.
0.50 chance of $30,000
0.50 chance of $10,000
©2005 Pearson Education, Inc.
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Preferences Toward Risk Example
 Utility at $30,000 is 18
 Utility at $10,000 is 10
 Must compare utility from the risky job
with current utility of 13.5
 To evaluate the new job, we must
calculate the expected utility of the risky
job
©2005 Pearson Education, Inc.
Chapter 5
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Preferences Toward Risk
 The expected utility of the risky option is
the sum of the utilities associated with all
her possible incomes weighted by the
probability that each income will occur.
E(u) = (Prob. of Utility 1) *(Utility 1)
+ (Prob. of Utility 2)*(Utility 2)
©2005 Pearson Education, Inc.
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Preferences Toward Risk –
Example
 The expected is:
E(u) = (1/2)u($10,000) + (1/2)u($30,000)
= 0.5(10) + 0.5(18)
= 14
E(u) of new job is 14 which is greater than
the current utility of 13.5 and therefore
preferred.
©2005 Pearson Education, Inc.
Chapter 5
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Preferences Toward Risk
 People differ in their preference toward
risk
 People can be risk averse, risk neutral, or
risk loving.
©2005 Pearson Education, Inc.
Chapter 5
43
Preferences Toward Risk
 Risk Averse
A person who prefers a certain given income
to a risky income with the same expected
value.
The person has a diminishing marginal utility
of income
Most common attitude towards risk
 Ex:
©2005 Pearson Education, Inc.
Market for insurance
Chapter 5
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Risk Averse - Example
 A person can have a $20,000 job with
100% probability and receive a utility
level of 16.
 The person could have a job with a 0.5
chance of earning $30,000 and a 0.5
chance of earning $10,000.
©2005 Pearson Education, Inc.
Chapter 5
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Risk Averse – Example
 Expected Income of risky job
E(I) = (0.5)($30,000) + (0.5)($10,000)
E(I) = $20,000
 Expected Utility of Risky job
E(u) = (0.5)(10) + (0.5)(18)
E(u) = 14
©2005 Pearson Education, Inc.
Chapter 5
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Risk Averse – Example
 Expected income from both jobs is the
same – risk averse may choose current
job
 Expected utility is greater for certain job
Would keep certain job
 Risk averse person’s losses (decreased
utility) are more important than risky
gains
©2005 Pearson Education, Inc.
Chapter 5
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Risk Averse
 Can see risk averse choices graphically
 Risky job has expected income =
$20,000 with expected utility = 14
Point F
 Certain job has expected income =
$20,000 with utility = 16
Point D
©2005 Pearson Education, Inc.
Chapter 5
48
Risk Averse Utility Function
Utility
E
18
D
16
The consumer is risk
averse because she would
prefer a certain income of
$20,000 to an uncertain
expected income =
$20,000
C
14
F
A
10
0
©2005 Pearson Education, Inc.
10
16 20
Chapter 5
30
Income ($1,000)
49
Preferences Toward Risk
 A person is said to be risk neutral if they
show no preference between a certain
income, and an uncertain income with
the same expected value.
 Constant marginal utility of income
©2005 Pearson Education, Inc.
Chapter 5
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Risk Neutral
 Expected value for risky option is the
same as utility for certain outcome
E(I) = (0.5)($10,000) + (0.5)($30,000)
= $20,000
E(u) = (0.5)(6) + (0.5)(18) = 12
 This is the same as the certain income of
$20,000 with utility of 12
©2005 Pearson Education, Inc.
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Risk Neutral
E
Utility 18
The consumer is risk
neutral and is indifferent
between certain events
and uncertain events
with the same
expected income.
C
12
A
6
0
©2005 Pearson Education, Inc.
10
20
Chapter 5
30
Income ($1,000)
52
Preferences Toward Risk
 A person is said to be risk loving if they
show a preference toward an uncertain
income over a certain income with the
same expected value.
Examples: Gambling, some criminal activity
 Increasing marginal utility of income
©2005 Pearson Education, Inc.
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Risk Loving
 Expected value for risky option – point F
E(I) = (0.5)($10,000) + (0.5)($30,000)
= $20,000
E(u) = (0.5)(3) + (0.5)(18) = 10.5
 Certain income is $20,000 with utility of 8
– point C
 Risky alternative is preferred
©2005 Pearson Education, Inc.
Chapter 5
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Risk Loving
Utility
E
18
The consumer is risk
loving because she
would prefer the gamble
to a certain income.
F
10.5
C
8
A
3
0
©2005 Pearson Education, Inc.
10
20
Chapter 5
30
Income ($1,000)
55
Preferences Toward Risk
 The risk premium is the maximum
amount of money that a risk-averse
person would pay to avoid taking a risk.
 The risk premium depends on the risky
alternatives the person faces.
©2005 Pearson Education, Inc.
Chapter 5
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Risk Premium – Example
 From the previous example
A person has a .5 probability of earning
$30,000 and a .5 probability of earning
$10,000
The expected income is $20,000 with
expected utility of 14.
©2005 Pearson Education, Inc.
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Risk Premium – Example
 Point F shows the risky scenario – the
utility of 14 can also be obtained with
certain income of $16,000
 This person would be willing to pay up to
$4000 (20 – 16) to avoid the risk of
uncertain income.
 Can show this graphically by drawing a
straight line between the two points – line
CF
©2005 Pearson Education, Inc.
Chapter 5
58
Risk Premium – Example
Risk Premium
Utility
G
20
18
E
C
14
Here, the risk
premium is $4,000
because a certain
income of $16,000
gives the person
the same expected
utility as the
uncertain income
with expected value
of $20,000.
F
A
10
0
©2005 Pearson Education, Inc.
10
16
20
Chapter 5
30
40
Income ($1,000)
59
Risk Aversion and Income
 Variability in potential payoffs increases
the risk premium.
 Example:
A job has a .5 probability of paying $40,000
(utility of 20) and a .5 chance of paying 0
(utility of 0).
©2005 Pearson Education, Inc.
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60
Risk Aversion and Income
 Example (cont.):
The expected income is still $20,000, but the
expected utility falls to 10.
 E(u)
= (0.5)u($0) + (0.5)u($40,000)
= 0 + .5(20) = 10
The certain income of $20,000 has utility of
16
If person must take new job, their utility will
fall by 6
©2005 Pearson Education, Inc.
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61
Risk Aversion and Income
 Example (cont.):
They can get 10 units of utility by taking a
certain job paying $10,000
The risk premium, therefore, is $10,000 (i.e.
they would be willing to give up $10,000 of
the $20,000 and have the same E(u) as the
risky job.
©2005 Pearson Education, Inc.
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Risk Aversion and Income
 The greater the variability, the more the
person would be willing to pay to avoid
the risk and the larger the risk premium.
©2005 Pearson Education, Inc.
Chapter 5
63
Risk Aversion & Indifference
Curves
 Can describe a person’s risk aversion
using indifference curves that relate
expected income to variability of income
(standard deviation)
 Since risk is undesirable, greater risk
requires greater expected income to
make the person equally well off
 Indifference curves are therefore upward
sloping
©2005 Pearson Education, Inc.
Chapter 5
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Risk Aversion and Indifference
Curves
Expected
Income
U3
U2
U1
Highly Risk Averse:An
increase in standard
deviation requires a
large increase in
income to maintain
satisfaction.
Standard Deviation of Income
©2005 Pearson Education, Inc.
Chapter 5
65
Risk Aversion and Indifference
Curves
Expected
Income
Slightly Risk Averse:
A large increase in standard
deviation requires only a
small increase in income
to maintain satisfaction.
U3
U2
U1
Standard Deviation of Income
©2005 Pearson Education, Inc.
Chapter 5
66
Reducing Risk
 Consumers are generally risk averse
and therefore want to reduce risk
 Three ways consumers attempt to
reduce risk are:
1. Diversification
2. Insurance
3. Obtaining more information
©2005 Pearson Education, Inc.
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Reducing Risk
 Diversification
Reducing risk by allocating resources to a
variety of activities whose outcomes are not
closely related.
 Example:
Suppose a firm has a choice of selling air
conditioners, heaters, or both.
The probability of it being hot or cold is 0.5.
How does a firm decide what to sell?
©2005 Pearson Education, Inc.
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68
Income from Sales of
Appliances
Hot Weather
Cold
Weather
Air
conditioner
sales
$30,000
$12,000
Heater sales
12,000
30,000
©2005 Pearson Education, Inc.
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Diversification – Example
 If the firms sells only heaters or air
conditioners their income will be either
$12,000 or $30,000.
 Their expected income would be:
1/2($12,000) + 1/2($30,000) = $21,000
©2005 Pearson Education, Inc.
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Diversification – Example
 If the firm divides their time evenly between
appliances their air conditioning and heating
sales would be half their original values.
 If it were hot, their expected income would be
$15,000 from air conditioners and $6,000 from
heaters, or $21,000.
 If it were cold, their expected income would be
$6,000 from air conditioners and $15,000 from
heaters, or $21,000.
©2005 Pearson Education, Inc.
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71
Diversification – Example
 With diversification, expected income is
$21,000 with no risk.
 Better off diversifying to minimize risk
 Firms can reduce risk by diversifying
among a variety of activities that are not
closely related
©2005 Pearson Education, Inc.
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72
Reducing Risk – The Stock
Market
 If invest all money in one stock, then take
on a lot of risk
If that stock loses value, you lose all your
investment value
 Can spread risk out by investing in may
different stocks or investments
Ex: Mutual funds
©2005 Pearson Education, Inc.
Chapter 5
73
Reducing Risk – Insurance
 Risk averse are willing to pay to avoid
risk.
 If the cost of insurance equals the
expected loss, risk averse people will buy
enough insurance to recover fully from a
potential financial loss.
©2005 Pearson Education, Inc.
Chapter 5
74
The Decision to Insure
©2005 Pearson Education, Inc.
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75
Reducing Risk – Insurance
 For risk averse consumer, guarantee of
same income regardless of outcome has
higher utility than facing the probability of
risk.
 Expected utility with insurance is higher
than without
©2005 Pearson Education, Inc.
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76
The Law of Large Numbers
 Insurance companies know that although
single events are random and largely
unpredictable, the average outcome of
many similar events can be predicted.
 When insurance companies sell many
policies, they face relatively little risk
©2005 Pearson Education, Inc.
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77
Reducing Risk – Actuarially Fair
 Insurance company can be sure total
premiums paid will equal total money
paid out
 Companies set the premiums so money
received will be enough to pay expected
losses.
©2005 Pearson Education, Inc.
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78
Reducing Risk – Actuarially Fair
 Some events with very little knowledge of
probability of occurrence such as floods
and earthquakes are no longer insured
privately
Cannot calculate true expected values and
expected loses
Governments have had to create insurance
for these types of events
 Ex:
©2005 Pearson Education, Inc.
National Flood Insurance Program
Chapter 5
79
The Value of Information
 Risk often exists because we don’t know
all the information surrounding a decision
 Because of this, information is valuable
and people are willing to pay for it
©2005 Pearson Education, Inc.
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80
The Value of Information
 The value of complete information
The difference between the expected value
of a choice with complete information and the
expected value when information is
incomplete.
©2005 Pearson Education, Inc.
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81
The Value of Information –
Example
 Per capita milk consumption has fallen
over the years
 The milk producers engaged in market
research to develop new sales strategies
to encourage the consumption of milk.
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82
The Value of Information –
Example
 Findings
Milk demand is seasonal with the greatest
demand in the spring
Price elasticity of demand is negative and
small
Income elasticity is positive and large
©2005 Pearson Education, Inc.
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83
The Value of Information –
Example
 Milk advertising increases sales most in
the spring.
 Allocating advertising based on this
information in New York increased profits
by 9% or $14 million.
 The cost of the information was relatively
low, while the value was substantial
(increased profits).
©2005 Pearson Education, Inc.
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84
Demand for Risky Assets
 Most individuals are risk averse and yet
choose to invest money in assets that
carry some risk.
Why do they do this?
How do they decide how much risk to bear?
 Must examine the demand for risky
assets
©2005 Pearson Education, Inc.
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85
The Demand for Risky Assets
 Assets
Something that provides a flow of money or
services to its owner.
 Ex:
homes, savings accounts, rental property,
shares of stock
The flow of money or services can be explicit
(dividends) or implicit (capital gain).
©2005 Pearson Education, Inc.
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The Demand for Risky Assets
 Capital Gain
An increase in the value of an asset.
 Capital loss
A decrease in the value of an asset.
©2005 Pearson Education, Inc.
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87
Risky & Riskless Assets
 Risky Asset
Provides an uncertain flow of money or
services to its owner.
Examples
 apartment
rent, capital gains, corporate bonds,
stock prices
 Don’t know with certainty what will happen to
the value of a stock.
©2005 Pearson Education, Inc.
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88
Risky and Riskless Assets
 Riskless Asset
Provides a flow of money or services that is
known with certainty.
Examples
 short-term
government bonds, short-term
certificates of deposit
©2005 Pearson Education, Inc.
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89
The Demand for Risky Assets
 People hold assets because of the
monetary flows provided
 To compare assets, must consider the
monetary flow relative to the asset’s price
(value)
 Return on an Asset
The total monetary flow of an asset,
including capital gains or losses, as a fraction
of its price.
©2005 Pearson Education, Inc.
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90
The Demand for Risky Assets
 Individuals hope to have an asset that
has returns larger than the rate of
inflation
Want to have greater purchasing power
 Real Return of an Asset (inflation
adjusted)
The simple (or nominal) return less the rate
of inflation.
©2005 Pearson Education, Inc.
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The Demand for Risky Assets
 Since returns are not known with
certainty, investors often make decisions
based on expected returns
 Expected Return
Return that an asset should earn on average
In the end, the actual return could be higher
or lower than the expected return
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Investments – Risk and Return
(1926-1999)
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The Demand for Risky Assets
 The higher the return, the greater the
risk.
 Investors will choose lower return
investments in order to reduce risk
 A risk-averse investor must balance risk
relative to return
Must study the trade-off between return and
risk
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Trade-offs: Risk and Returns
Example
 An investor is choosing between T-Bills
and stocks:
1. T-bills – riskless
2. Stocks – risky
 Investor can choose only T-bills, only
stocks, or some combination of both
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Trade-offs: Risk and Returns
Example
 Rf = risk free return on T-bill
Expected return equals actual return on a
riskless asset
 Rm = the expected return on stocks
 rm = the actual returns on stock
 Assume Rm > Rf or no risk averse
investor would buy the stocks
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Trade-offs: Risk and Returns
Example
 How do we determine the allocation of
funds between the two choices
b = fraction of funds placed in stocks
(1-b) = fraction of funds placed in T-bills
 Expected return on portfolio is weighted
average of expected return on the two
assets
RP  bRm  (1  b) R f
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Trade-offs: Risk and Returns
Example
 Assume, Rm = 12%, Rf = 4%, and b = 1/2
RP  bRm  (1  b) R f
RP  (1 / 2)(12%)  (1  1 / 2)( 4%)
RP  8 %
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Trade-offs: Risk and Returns
Example
 How risky is the portfolio?
As stated before, one measure of risk is
standard deviation
Standard deviation of the risky asset, m
Standard deviation of risky portfolio, p
Can show that:
 p  b m
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Trade-offs: Risk and Returns
Example
 We still need to figure out how the
allocation between the investment
choices
 A type of budget line can be constructed
describing the trade-off between risk and
expected return
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Trade-offs: Risk and Returns
Example
R p  bRm  (1  b) R f
Rp  R f 
( Rm  R f )
m
p
 Expected return on the portfolio, rp
increases as the standard deviation, p of
that return increases
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Trade-offs: Risk and Returns
Example
 The slope of the line is called the price of
risk
Tells how much extra risk an investor must
incur to enjoy a higher expected return
Slope  (Rm  Rf )/ m
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Choosing Between Risk & Return
 If all funds are invested in T-bills (b=0),
expected return is Rf
 If all funds are invested in stocks (b=1),
expected return is Rm but with standard
deviation of m
 Funds may be invested between the
assets with expected return between Rf
and Rm, with standard deviation between
m and 0
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Choosing Between Risk & Return
 We can draw indifference curves showing
combinations of risk and return that leave
an investor equally satisfied
 Comparing the pay-offs and risk between
the two investment choices and the
preferences of the investor, the optimal
portfolio choice can be determined
 Investor wants to maximize utility within
the “affordable” options
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Choosing Between Risk & Return
Expected
Return,Rp
U2 is the optimal choice since it gives the highest
return for a given risk and is still affordable
U3
U2
U1
Rm
Budget Line
R*
Rf

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m
Standard Deviation
of Return,  p
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Choosing Between Risk & Return
 Different investors have different attitudes
toward risk
 If we consider a very risk averse investor (A)
 Portfolio will contain mostly T-bills and less in stock
with return slightly larger than Rf
 If we consider a riskier investor (B)
 Portfolio will contain mostly stock and less T-bills with
a higher return Rb but with higher standard deviation
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The Choices of Two Different
Investors
UB
Expected
Return,Rp
UA
Budget line
Rm
RA
Given the same
budget line,
investor A
chooses low
return- low risk,
R
while investor B
chooses high
return-high risk.
RB
f
A
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B
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m
Standard Deviation
of Return,  p
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Investing in the Stock Market
 In 1990’s many people began investing in
the stock market for the first time
Percent of US families who had directly or
indirectly invested in the stock market
 1989
= 32%
 1998 = 49%
Percent with share of wealth in stock market
 1989
= 26%
 1998 = 54%
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Investing in the Stock Market
 Why were stock market investments
increasing during the 90’s?
Ease of online trading
Significant increase in stock prices during
late 90’s
Employers shifting to self-directed retirement
plans
Publicity for “do it yourself” investing
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Behavioral Economics
 Sometimes individuals’ behavior
contradict basic assumptions of
consumer choice
More information about human behavior
might lead to better understanding
This is the objective of behavioral economics
 Improving
understanding of consumer choice by
incorporating more realistic and detailed
assumptions regarding human behavior
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Behavioral Economics
 There are a number of examples of
consumer choice contradictions
You take at trip and stop at a restaurant that
you will most likely never stop at again. You
still think it fair to leave a 15% tip rewarding
the good service.
You choose to buy a lottery ticket even
though the expected value is less than the
price of the ticket
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Behavioral Economics
 Reference Points
Economists assumes that consumers place
a unique value on the goods/services
purchased
Psychologists have found that perceived
value can depend on circumstances
 You
are able to buy a ticket to the sold out Cher
concert for the published price of $125. You
find out you can sell the ticket for $500 but you
choose not to, even though you would never
have paid more than $250 for the ticket.
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Behavioral Economics
 Reference Points
The point from which an individual makes a
consumption decision
From the example, owning the Cher ticket is
the reference point
 Individuals
dislike losing things they own
 They value items more when they own them
than when they do not
 Losses are valued more than gains
 Utility loss from selling the ticket is greater than
original utility gain from purchasing it
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Behavioral Economics
 Experimental Economics
Students were divided into two groups
Group one was given a mug with market
value of $5.00
Group two received nothing
Students with mugs were asked how much
they would take to sell the mug back
 Lowest
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Behavioral Economics
 Experimental Economics (cont.)
Group without mugs was asked minimum
amount of cash they would except in lieu of
the mug
 On
average willing to accept $3.50 instead of
getting the mug
Group one had reference point of owning the
mug
Group two had reference point of no mug
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Behavioral Economics
 Fairness
Individuals often make choice because they
think they are fair and appropriate
 Charitable
giving, tipping in restaurants
Some consumers will go out of their way to
punish a store they think is “unfair” in their
pricing
Manager might offer higher than market
wages to make for happier working
environment or more productive worker
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Behavioral Economics
 The Laws of Probability
Individuals don’t always evaluate uncertain
events according to the laws of probability
Individuals also don’t always maximize
expected utility
Law of small numbers
 Overstate
probability of an event when faced
with little information
 Ex: overstate likelihood they will win the lottery
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Behavioral Economics
 Theory up to now has explained much
but not all of consumer choice
 Although not all of consumer decisions
can be explained by theory up to this
point, it helps understand much of it
 Behavioral economics is a developing
field to help explain and elaborate on
situations not well explained by the basic
consumer model
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