ECON6021 (Nov 17&19)

1. ECON6021 (Nov 17&19) Information Asymmetry

2. Informational economics • When a person buys medical insurance, the insuring company does not know whether the person is healthy. Nor does it know how well he is going to take care of himself after buying insurance. • The former type of asymmetry information is called a hidden type problem, or adverse selection problem. • The latter type of asymmetric information is called a hidden action problem, or moral hazard problem. But the notion of moral hazard has subsequently expanded. • Information economics is the study of decision makings between agents when their information is asymmetric.

3. Adverse Selection

4. Why called “Adverse Selection”? • Adverse selection refers to a situation where a selection process (here market) results in a pool of products/individuals with economically undesirable characteristics. • With “hidden type”, either (1) bad products drive out good products or (2) good products subsidize bad products (both receive the same price). • Gresham’s law: bad money drives out good. Or, where two media of exchange come into circulation together the more valuable will tend to disappear.

5. Adverse selection: Used Cars (Lemons) Market Assumption: all of the above is commonly known in the following exercises.

6. Scenario I: Full Information • Suppose that every buyer and every seller know the type of the car they are negotiating. • Then both good cars and bad cars will be traded. • There are simply two products (good and bad cars).

7. Scenario II: No Information • Suppose buyers don’t know the type of the cars they are interested. Also suppose no sellers know the type of the cars they own. Assume all agents are risk neutral. • Expected valuation of a car to buyers= 1/3 * $30K + 2/3 * $20K = $23.33K • Expected valuation of a car to sellers = 1/3 * $25K + 2/3 * $10K = $15K • Both good cars and bad cars will be traded!

8. Scenario III: Asymmetric (Unequal) Information • Sellers know the types of cars they own. But buyers don’t know the types of cars they are going to buy. • Is a buyer willing to pay at a price greater than $25K (say $26K)? • No, because there is 2/3 of probability that the car is bad, and the expected valuation to the buyer=1/3*$30K + 2/3*$20K= $23.33K < the price

9. Scenario III: Asymmetric (Unequal) Information • Is a buyer willing to pay a price of $22K to buy a car? • No, at such a low price, only bad cars owners will sell their cars. But bad cars are worth only $20K to the buyer. $22K is too high a price. • The market price is even lower, at $20K or somewhat lower. Only bad cars will be traded. Good cars don’t find a buyer!!! • Remark: What matters is not the amount of information.

10. Scenario III: Asymmetric Information • Good cars may still find a buyer, if the probability of bad cars in the pool is low. • Let p be such prob. A buyer is willing to pay $25K if (1-p)x$30K + px$20K>$25K, or p<0.5. • Good cars of 2-3 years old will easily find a buyer, while good cars of 10 years old don’t find a buyer

11. Solving the Problems: • Guarantees & Warranties • Liability Laws • Reputation of a store or the manufacturer • Experts--a disinterested party • Standards & Certifications • signaling by the party who has more information [education, money burning, etc.]

12. Moral Hazard Recap: • When a person buys medical insurance, the insuring company does not know whether the person is healthy. Nor does it know how well he is going to take care of himself after buying insurance. • The latter type of asymmetric information is called a hidden action problem, or moral hazard problem. That is, when people are insured by medical insurance, they tend to exert less effort to take care of themselves than the case they are uninsured. • Why called moral hazard? People buy insurance for their houses, and then burn them and claim for compensation greater than the value of the houses.

13. Some knowledge about decisions under uncertainty • Expected value of a gamble=EV=p1v1+p2v2+…+pnvn where pi is the probability for the prize vi and p1+…+pn=1 • A gamble (game, or lottery) is fair if its expected value is zero. • St. Petersburg paradox: a coin is flipped until a head appears. If the head first appears on the nth flip, the player is paid $2n. How much are you willing to pay to play the game? • EV of the game =(1/2)x$2+(1/4)x$4+…(1/2n)x$2n+… = • But rarely are we willing to pay a few thousand dollars for such a game!! • This is because people are generally risk averse! One prefers $1,000 to 1/2 probability of $2,000 and 1/2 probability of $0.

14. Contracting between a risk neutral and risk averse agent • In the absence of moral hazard, the risk neutral agent should bear all risk. • Suppose there are only two states: good and bad (each with 1/2 probability), and a joint venture between a risk neutral agent (N) and a risk averse agent (R) have a revenue of 150 and 100 under the two states. • Consider any contract stipulates that the agent get x at the good state and y at the bad state. N’s expected income is (150-x)/2+(100-y)/2=125-(x+y)/2. R’s expected income is (x+y)/2. • Consider another contract with a sure payment of (x+y)/2 at each state. The each party’s expected income remains unchanged. While N is indifferent to the change, R is strictly better off because risk is eliminated.

15. Principal-Agent Problem & Insurance • A risk neutral principal hires a risk averse agent to help him on a task. Suppose the agent’s effort affects the profits non-deterministically (e.g. farming). • Without moral hazard, the optimal contract is to let the principal bear all the risk and the agent get a fixed income. [Optimal risk sharing] • But in the presence of moral hazard, such a contract is infeasible in the sense that the agent will shirk. A tradeoff is to have a contract stipulating a bonus positively related to the profits generated. • The above analysis can be extended to insurance. In the absence of moral hazard, the optimal insurance contract is a full insurance. • In the presence of moral hazard, full insurance is no longer feasible. Insurance can only be partial [deductible, etc.]

16. Moral hazard as a verification problem • Even if actions are observable, as long as they are not verifiable to a third party, then a contract made contingent on these actions is not enforceable. • The following insurance contract is not enforceable. “If you take good care of yourself, I’ll pay you $5,000 in case of a loss; otherwise, I won’t pay you any in case of a loss.” • Hence, moral hazard may well be a result of incomplete contracts, rather than asymmetric information.

17. Moral hazard as a commitment problem • The idea of moral hazard has subsequently expanded to account for related phenomena. • The most discussed are commitment or time (in)consistency problem. • Actions are observable and even verifiable and hence contractible. • However, when the undesirable action takes place, both parties of the contract will choose not to enforce it. Instead, they renegotiate the contract.

18. A Contract between Mother and Son • A contract between mother and son: “If the son goes to sleep by 10pm, he’ll receive no penalty; otherwise, he will be shot to death.” • Ex ante, the mom wishes the contract enforceable so that, foreseeing the death penalty, the son will go to bed on time. • Suppose HK law allows this contract to be legal. • Suppose they can arrange videotaping so that the court can verify when the son goes to bed. • However, ex post in case the son doesn’t go to bed by 10pm, it would be in both parties’ interest to renegotiate the contract (no one likes to see the son die anyway).-->a time inconsistency problem (or commitment problem) • The son knows this and hence does not go to bed by 10pm.

19. Moral hazard & Government Policy • Moral hazard as a time consistency problem is closely related to government policy, where government is one party of a contract and citizens (or firms) are another party. • An interesting quote: “There are two types of countries in the world; those with deposit insurance, and those not knowing they have deposit insurance.”

20. Moral hazard in a natural disaster • Suppose residents near Yellow River are more vulnerable to attack of typhoons. • Two states of nature: good state and bad state with probability 0.9 and 0.1. • In good state: loss =0 • In bad state: loss = $1m • Residency elsewhere no loss • moving cost = $50k<expected loss=0.1x$1m=100k • in case of bad state, the government can step in to reduce the resident’s loss to $200k at a cost of $500k

21. Moral hazard in a natural disaster The efficient outcome is to have the resident move out. But the government cannot commit not to rescue the resident at the bad state (a benevolent government should rescue). Knowing this, the resident will not move out!

22. Remedies for moral hazard as a commitment problem • Mandatory insurance • Coercion (force the resident to move at the outset) • divided government makes discretion less likely • In general, don’t postpone! Solve the problem now!!

23. Further Applications • Why unemployment can be an equilibrium outcome • Why there is equilibrium credit rationing • Why debt financing and equity financing are different • Why firms exist and what explains their boundaries (holdup problem) • Why currency attack occurs even when the fundamentals are sound