Transcript lecture 1 - Vanderbilt University

Chapter 19:
The Problem of Adverse
Selection
Managerial Economics: A Problem Solving Appraoch (2nd Edition)
Luke M. Froeb, [email protected]
Brian T. McCann, [email protected]
Website, managerialecon.com
COPYRIGHT © 2008; Thomson South-Western, a part of The Thomson Corporation. Thomson, the Star logo, and
South-Western are trademarks used herein under license.
Slides prepared by Lily Alberts for Professor Froeb
Summary of main points
• Insurance is a wealth-creating transaction that
moves risk from those who don’t want it to those
who are willing to bear it for a fee.
• Adverse selection is a problem that arises from
information asymmetry—anticipate it, and, if you
can, figure out how to consummate the
unconsummated wealth-creating transaction (e.g.,
between a low-risk customer and an insurance
company).
• The adverse selection problem disappears if the
asymmetry of information disappears.
Summary of main points (cont.)
• Screening is an uninformed party’s effort to learn
the information that the more informed party has.
Successful screens have the characteristic that it is
unprofitable for bad “types” to mimic the behavior
of good types.
• Signaling is an informed party’s effort to
communicate her information to the less informed party. Every successful screen can also be
used as a signal.
• Online auction and sales sites, like eBay, address
the adverse selection problem with authentication
and escrow services, insurance, and on-line
reputations.
Introductory anecdote: Zappos
• Zappos.com is an online shoe retailer that depends heavily
on customer service – a key differentiator for Zappos.
• As part of the hiring process, Zappos recruits are required
to complete a four-week training process.
• Zappos discovered that training alone could not imbue
employees with the attitude and personality required to
maintain Zappos’ reputation for customer service.
• Specifically, Zappos was having trouble measure such
intangible qualities and devised a system to get the employees
with these qualities to identify themselves.
• After one week of training, Zappos offers $2000 to any
person who will quit on the spot.
• About 3% of employees take this offer, and the remaining group
generally deliver the quality of service Zappos desires.
Introduction: adverse selection
• The problem Zappos faces is known as adverse selection.
Zappos want to hire only good employees, but cannot
distinguish the good from the bad.
• For Zappos, the employees known whether they are hard workers
with the attitude and personality that Zappos seeks, but Zappos
does not know which employees possess those attributes.
• When one party in a transaction has more or better information
than the other, adverse selection is a problem.
• Low-quality employees generally have more incentive to accept
an offer of employment (they might not get another), which
exacerbates the problem of adverse selection.
• Employers need to find a way to distinguish the high- from the
low-quality workers. Zappos $2000 offer is one way to
“screen” out the low-quality applicants, and is a solution to
the adverse selection problem.
Insurance and risk
• The problem of adverse selection is easily illustrated in the
market for insurance.
• The demand for insurance comes from consumers who do
not like risk. We model risk as a lottery – a random variable
with a payment attached to each outcome.
• A risk-neutral consumer values a lottery at its expected value.
• A risk-averse consumer values a lottery at less than its
expected value.
• For example, flipping a fair coin. If the coin lands on heads the
payoff is $100; on tails, $0. A risk-adverse consumer would value
the lottery at $40, while a risk-neutral consumer would value it
at %50.
• Insurance moves “risk” from the risk adverse consumer (lower
value) to a risk neutral insurance company (high value).
Insurance and risk (cont.)
• Insurance is also a wealth creating transaction, except that it
moves a “bad” from someone who doesn’t want it (risk averse
consumer) to someone who willing to accept the risk for a fee
(insurance company).
• Numerical example: Rachel owns a bicycle valued at $100.
• The bike has a possibility of being stolen, meaning Rachel’s
ownership is like a lottery: lose $100 if it’s stolen, lose $0 if it isn’t.
• If the probability of theft is 20%, then the expected cost of the
lottery is (0.2)($100) = ($20).
• If Rachel buys a bike insurance policy that will reimburse her for the
value of the bike if stolen for $25, she eliminates the risk of owning
a bike.
• Both insurance company and Rachel are better off with this policy.
The company earns $5 ($25-$20), on average, and Rachel can stop
worrying about bike theft, i.e., she “pays” the insurance company
$25 each year so she doesn’t have to face the risk of bike theft.
Insurance and risk (cont.)
• It’s important to note, the insurance company never actually
earns $5. Either the company loses $75 if the bike is stolen,
or earns $25 if it’s not.
• The expected value of offering insurance, though, is $5
0.2 x ($75) + 0.8 x ($25) = $5
• One main function of the financial industry is also the
allocation of risk, moving risk from lower- to higher-valued
uses.
• Discussion: Describe precisely how a futures contract
transfers risk from the seller of the contract to the buyer of
the contract.
The first lesson of adverse selection
• To explain on adverse selection, we modify the bike example.
Now suppose that there are two equally sized risk-adverse
consumer groups:
• Group 1 with a probability of theft of 0.2
• Group 2 with a probability of theft of 0.4
• What happens when you try to sell insurance at a price of
$35?
• HINT: do NOT assume that both groups will purchase at this price
• Because only high-risk consumers would be willing to pay the
higher price, the company would consistently be paying out
policies.
• So, anticipate adverse selection and protect yourself against it.
• This means anticipate that only the high-risk types will buy, so
price the insurance at $45
The first lesson (cont.)
• In 1986, D.C. passed the Prohibition of Discrimination in the
Provision of Insurance Act outlawing HIV testing by health
insurance companies.
• As a result many insurance companies left D.C.
• The companies were unable to distinguish the low-risk from the
high-risk consumers. If the companies sold only to HIV-positive
consumers they would lose money.
• In 1989, the law was repealed, and the adverse selection
problem disappeared. Companies could once again differentiate
between high- and low-risk consumers and offered two
differently priced policies to cover each group.
• By eliminating asymmetry of information (insurance companies
could tell who was high-risk and who was low-risk) the problem
of adverse selection was solved.
Anticipating adverse selection (cont.)
• In financial markets, adverse selection becomes a problem
when the owners of a company want to sell shares to the
public but know more information about the prospects of the
company than potential investors.
• Potential investors should thus anticipate that companies
with poor prospects are most likely to sell to the public.
• For example, small initial public offerings (IPOs) of less than
$100 million lose money, on average, whereas large IPOs have
“normal” returns.
• The winner’s curse of common-value auctions is also a type
of adverse selection.
The second lesson of adverse selection
• In the bicycle example, if the insurance company sells
policies at $45, low-risk consumers wont buy (because
with their lower risk, their cost is only $35)
• But these consumers would be willing to pay $25, which is
still more than the cost to the company of insuring the bike
($20).
• This means the low-risk consumers are not served because
it is difficult to profitably transact with them.
• The problem of adverse selection presents many
potentially profitable (unconsummated) wealth-creating
transactions.
• Using screening or signaling helps overcome the adverse
selection problem so that low-risk individuals can be
transacted with profitably.
Screening
• One simple solution to adverse selection is to gather
enough information to distinguish high-risk from low-risk
consumers.
• But this can be difficult and costly to do.
• Privacy and anti-discrimination laws frequently prevent insurance
agencies, and other companies, from gathering or using certain
information (race, gender, credit scores).
• To solve this problem more indirect methods can be used
to identify individual risk. Screening is an effort by the
less-informed party to induce of consumers to reveal
their types.
• Information may be gathered indirectly by offering
consumers a menu of choices, and consumers reveal
information about their risks by the choices they make.
Screening (cont.)
• Screening is frequently used in the insurance market.
• Suppose high-risk individuals prefer full insurance at
$45, to partial insurance (for instance receiving only
$50 if your bike is stolen) at $15.
• For a successful screen, it must not be profitable for
the high-risk consumers to mimic the choice of the
low-risk consumers.
• Using a screening method allows companies to
consummate the unconsummated wealth-creating
transactions by eliminating information asymmetry.
Car Buying Screen
• In the used car market, adverse selection is known as the
lemons problem.
• On a car lot there are bad cars (“lemons”) worth $2000 and
good cars (“cherries”) worth $4000.
• Sellers know which cars are cherries and which are lemons.
• So, if an uninformed buyer walks onto the lot and offers to
buy a car for $3000, only the lemons owner would sell.
• The result is that the buyer overpays by $1000 for a bad car.
• But if the buyer offers to pay $4000, both lemons owners
and cherry owners will sell. However, the expected value of
the car in both cases will be $3000, so again the buyer
overpays.
• Anticipating adverse selection, the buyer will offer only
$2,000, ensuring a lemon, but at least he won’t overpay.
Car buying (cont.)
• Owners of good cars are analogous to low-risk
insurance consumers – they are unable to transact.
• How can this unconsummated wealth-creating
transaction be consummated? In other words, how
can you design a screen for those who want to buy a
cherry, and not a lemon?
• One option is to offer to buy a car for $4000 and
demand a money-back guarantee.
• If the car is really worth $4000, the cherry owner
knows that it won’t be returned.
• But the lemons owner will refuse the offer.
Marriage screen
• Discussion: Louisiana offers a choice between two
marriage contracts: a covenant contract which makes
divorce expensive; and a regular contract which
makes divorce relatively cheap. How does Louisiana
marriage law function as a screen?
• HINT: What is adverse selection problem in marriage?
• Screening is also useful as implemented by Zappos to
identify high- from low-quality employees.
• Zappos made it profitable for low-quality employees to
identify themselves by offering the $2000 payment to quit.
• Incentive compensation is another tool companies use
to identify low-quality workers.
Incentive compensation as a screen
• When hiring sales people there are hard workers, who will
sell 100 units per week, and lazy workers, who will sell only
50 units per week.
• Asymmetric information means only workers known if
they’re lazy or hard working.
• A Straight salary leads to adverse selection.
• Because both types of employee will accept an offer of
$800/week, you will attract a mix of lazy and hard workers.
• Incentive pay ($10 per sale) solves the problem: hard
workers earn $1000 and lazy workers will reject the offer
(they expect to earn only $500).
• Incentive pay imposes risk on the workers – some sales factors
are out of their control.
• Another screen with less risk: offer a base salary of $500 plus
$10 per sale for every unit above 50 sales.
Signaling
• Definition: Signaling describes the efforts of the more
informed party (consumers) to reveal information about
themselves to the less informed party (the insurance
company). A successful signal is one that bad types will
not mimic.
• Proposition: Any successful screen can also be used as a
signal
• Low-risk consumers could offer to buy insurance with a big
deductible, good employees could offer to work on
commission, and sellers with good cars could include a
warranty with the purchase.
• The crucial element of a successful signal is that it must not
be profitable for the bad-types to mimic the signaling
behavior of the good-types.
Signaling (cont.)
• Some of the value of education is in its signaling value.
• Students can signal employers that they’re hardworking,
quick-learning, dedicated, etc. by spending the time and
money necessary to pursue an education.
• Firms brand and advertise products to signal quality to
consumers.
• As a result, most consumers are now willing to pay more
for branded and advertised goods.
• Low-quality firms wont find it profitable to advertise
because once consumers use the product and notice the
difference, they will switch brands and the firm will have
wasted money on the advertising.
• (Note that some states prohibit advertising, e.g., for
financial advisors, that would serve as a signal of quality.)
Adverse Selection on eBay
• Sellers have better information than buyers about the
quality of goods being offered for sale.
• Anticipating adverse selection leads buyers to offer less,
which makes sellers less willing to sell high quality goods.
• Consummated transactions are more likely to leave buyers
disappointed in the quality (“lemons”).
• How does eBay try to solve this problem?
• By providing:
• Escrow services
• Fraud insurance
• Seller ratings – provided by past buyers
• eBay’s ability to address the adverse selection problem has allowed
them to begin selling more expensive items, like cars, where the
problem can result in much bigger losses.
Alternate Intro Anecdote
• Insurance Company X provides group disability insurance products to
businesses, who in turn offer the product to their employees
• Pricing policies to prevent a loss is difficult since the company does not
know which customers are high-risk (likely to file a claim)
• If policies are priced at the average risk, only high risk consumer will
purchase.
• If policies are priced at low risk, both high and low-risk consumers
purchase, leading to expected costs above price.
• By using available geographic and industry experience information as a
screening tool, the company was able to identify groups prone to higher risks
and to price those policies appropriately
• Companies in Miami, Florida had (on average) higher long-term disability
claims while companies in Washington, D.C. had lower long-term disability
claims
• Short term disability for a teacher might cost 18% more than the base
cost; the same policy for a group of automotive exhaust repairers would
cost 107% more than the base.
Anecdote: Pre-Hire “Training”
• South Carolina manufacturing firm hiring new
employees
• Requires 24 unpaid classroom hours over 8 days in 4 week
period
• Final step before full-time employment
• If candidate is tardy, he/she is sent home and not allowed
to return
• Results
• Of 30 people, two candidates are sent home
• Only ten of the 1,300 workers hired under the program
have had significant attendance issues
• Program reduced the rate of bad hires from about eight
percent to less than one percent
24
1. Introduction: What this book is about
Managerial Economics 2. The one lesson of business
3.Benefits, costs and decisions
Table of contents
4. Extent (how much) decisions
5. Investment decisions: Look ahead and reason back
6. Simple pricing
7.Economies of scale and scope
8. Understanding markets and industry changes
9. Relationships between industries: The forces moving us towards long-run equilibrium
10. Strategy, the quest to slow profit erosion
11. Using supply and demand: Trade, bubbles, market making
12. More realistic and complex pricing
13. Direct price discrimination
14. Indirect price discrimination
15. Strategic games
16. Bargaining
17. Making decisions with uncertainty
18. Auctions
19.The problem of adverse selection
20.The problem of moral hazard
21. Getting employees to work in the best interests of the firm
22. Getting divisions to work in the best interests of the firm
23. Managing vertical relationships
24. You be the consultant
EPILOG: Can those who teach, do?