Chapter 6:The Economics of Information and
Choice Under Uncertainty
Chapter Outline
 The Economics Of Information
 Choice Under Uncertainty
 Insuring Against Bad Outcomes
 Until this chapter, we assumed perfect information
but in practice, decisions are made w/o such, i.e.
under asymmetric information and uncertainty.
Two issues in Chapter 6
1. how we gather and evaluate relevant information
2. Include uncertainty to Chapter 3 Consumer Choice
Model.
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Signaling
A toad’s croak at night is a signal between potential
advesaries –conveying information about its size
 Signaling: communication that conveys information.
 Two properties of signaling: between potential
adversaries:
1. Signals must be costly to fake (Costly-to-Fake
Principle)
2. If some individuals use signals that convey favorable
information about themselves, others will be forced to
reveal information even when it is considerably less
favorable (The Full-disclosure Principle)
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Costly-to-Fake Principle
 Costly-to-fake principle: for a signal to an adversary to
be credible, it must be costly to fake, i.e. if a small toad
could costlessly imitate the deep croak of big toads, then
a deep croak is no longer the characteristic of big toads.
Problem: Big toads have a natural advantage - the
deepness of a croak alone emerges as a reliable signal.
The Costly-to-Fake Principle has applications to signals
between people in economic applications.
 Economic applications:
– Product Quality Assurance
– Choosing a Trustworthy Employee
– Choosing a Hard-Working, Smart Employee
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Economic Applications of the Costly-toFake Principle
1. Product Quality Assurance – products are so complex for the average
consumer to determine the quality. To producers of high quality products
who need to communicating such quality and hence charge higher prices,
need to communicate via heavy advertising. The basis of such evidence
that it works is that most consumers surveyed at purchase state “– as
seen on TV.”
2. Choosing a Trustworthy Employee – most employees steal or cheat
their employers. Solution: choose from people who belong to a certain
group whose behavior is difficult to fake over a long period. For example .
Recruit New York nannies who belong to a group that would find it to
fake –membership of a Mormon tradition! :
3. Choosing a Hard-Working, and Smart Employee –choose graduates
from an lite university and those who graduate with honors! But recall
the recent story about cheating by undergraduates at Harvard. Problem –
it is not clear how graduates from such institutions contribute to high
productivity!
The Full-Disclosure Principle
Figure 6.1: The
Information
Implicit
in Silence
The Full-disclosure Principle-individuals must
disclose even unfavorable qualities about themselves, lest their silence be
taken to mean that they have something even worse to hide.
 Explains smaller toads croak at all since their low pitch reveals their
size or inadequacy in croaking!
 All toads crock to keep them from appearing smaller than they really
are.
 The Full-Disclosure principle derives from asymmetric information – a
silent toad knows its size BUT the rival can only make an informed
guess.
Applications of Costly-to-Fake
Principle
 Product Warranties
– Producers know much more than consumers about how good their
products are. Producers of high quality products issue long and
comprehensive warrants (liberal guarantees), e.g. Hyundai cars in
the US. Henceforth, all Hyundai products might be deemed of
credible quality.
 Regulating the Employment Interviewer
– Lack of evidence that something resides in a favored category will
often suggest that it belongs to a less favored one. For example, laws
prohibit asking the candidate his/her marital status. Reason –
prevent employers from discriminating on basis of demographic
information. Problem: smart candidates volunteer this information
to get into the favorable pool!
 The Lemons Principle
– Cars offered for sale, taken as a group, are simply of lower average
quality than cars not offered for sale.
 The Stigma of the Newcomer--- used to avoid ‘local bad reputation’ by
relocating. Thus, a newcomer was often viewed as having bad reputation. Those
deemed trustworthy in their locale, chose to reap those rewards.
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Probability And Expected Value
 Economic decisions made under uncertainty are
essentially gambles
 Expected value: the sum of all possible outcomes,
weighted by its respective probability of occurrence.
– In addition to the expected value of a gamble (EV),
most people also consider how they feel about each of
its possible outcomes.
 People choose the alternative that has the highest
expected utility.
– Expected utility: the expected utility of a gamble is
the expected value of utility over all possible
outcomes.
 The expected values of the outcomes of a set of alternatives need not
have the same ranking as the expected utilities of the alternatives.
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Probability And Expected Value
 Diminishing marginal utility: for a utility function
defined on wealth, one in which the marginal utility
declines as wealth rises.
 Fair gamble: a gamble whose expected value is zero.
Type of Risk Preferences
• Risk averse: preferences described by a utility function
with diminishing marginal utility of wealth.
• Risk seeking: preferences described by a utility function
with increasing marginal utility of wealth.
• Risk neutral: preferences described by a utility function
with constant marginal utility of wealth.
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Figure 6.2: A Concave Utility Function
The Von Neumann-Morgenstern
Expected Utility Model – model of
choice between uncertain
alternatives
Central Premise – people choose
the alternative that has the highest
expected utility (EU). Assume a
utility function with numerical
values to satisfaction associated with
different outcomes. That is, the
expected utility of a gamble is the
expected value of utility over ALL
possible outcomes.
 Concave Utility function – U(M)( where M= total wealth) is concave if for
any pairs of M1 and M2, the function lies above the chord that joins [M1,
U(M1)] and [M2, U(M2)]
 U(M) also exhibits diminishing marginal utility of wealth.
 People with a concave U(M) are Risk Averse – always refuse a gamble
whose EV =0
 Gambles with EV =0 are termed Fair Gambles (tossing a coin)
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Figure 6.3: A Risk-Averse Person Will Always
Refuse a Fair Gamble
 U(M) is concave in wealth
(M)
Winning endpoint
 EU = ½ (18) + ½ (38) = 28
 Note that 28 lies on the
chord between 18 and 32
BUT under the gamble= 40
Losing
endpoint
 The EU of refusing the
gamble is U(40) =32 >28 =
EV
 It clear that a risk-averse
consumer will reject not
 For U(M), all gambles with EV wealth
only fair gambles but even
<52 yield lower EU than that of keeping
those with EV>0
initial wealth level at 40.
 Note: The arc between A and C = EV
lies above the chord AC = EU. Thus, EV
between A and C lies above the EU
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Figure 6.4: The Utility Function of a
Risk-Seeking Person is Convex in Total Wealth
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Figure 6.5: Risk Neutrality
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Figure 6.6: The Value of Reducing
Uncertainty
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Risk Pooling
• Law of large numbers: a statistical law that
says that if an event happens independently
with probability p in each of N instances, the
proportion of cases in which the event
occurs approaches p as N grows larger.
– Makes it possible for people to reduce their risk
exposure through pooling arrangements.
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Adverse Selection and Moral Hazard
• Adverse selection: process by which the
less desirable potential trading partners
volunteer to exchange.
• Moral hazard: incentives that lead people
to file fraudulent claims or to be negligent in
their care of goods insured against theft or
damage.
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Figure 6.9: The Reservation Price
for Insurance
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Figure A6.1: A Hypothetical Uniform
Wage Distribution
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Figure A6.2: The Expected Value of an
Offer that is Greater than $150
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Figure A6.3: The Acceptance Wage
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Figure A6.4: A Hypothetical
Price Distribution
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Figure A6.5: The Acceptance Price as a
Function of the Cost of Search
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Figure A6.6: An Unbiased Estimate
with a Uniform Distribution
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Figure A6.7: The Expected Value
of The Highest Estimate N = 1,2,3 & 4
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