Final Flashcards
(31 cards)
In general terms, what is adverse selection?
Situation where only constant-price contracts are offered and the informed party decides to participate upon observation. Job market/unraveling.
In general terms, what is cheap talk?
Costless messages or actions are sent from the informed party to the uninformed.
In general terms, what is screening/NLP?
The uninformed side offers a menu to the informed party. Used in airline prices.
In general terms, what is mechanism design?
Similar to screening, but more complicated forms of moving the informed party to a particular outcome. Often utilize auctions or public good valuations.
In cheap talk, what does a lower value for “b” mean?
Preferences between sender/receiver are more closely aligned
What is each party trying to accomplish in cheap talk?
Minimize their loss function:
- Sender = L(l y - b - θ l)
- Receiver = L(l y - θ l)
What are the results of the cheap talk model?
- No PBE where sender gives message m = θ
- The difference in length between two adjacent intervals is 4b.
- There is always a babbling equilibrium where one interval/partition exists
- The number of partitions is decreasing in b.
What is the most efficient equilibrium in a cheap talk model?
Where the number of intervals is maximized
nx+2bn(n-1) = 1
How can the relationship between “b” and “n” be explained?
b < 1/2n(n-1)
How do you construct partitions/intervals in the cheap talk model?
- Set nx+2bn(n-1) = 1
- Solve for “n”, plug in to solve for “x”
- Use to solve for intervals
How do you calculate the expected utility for the receiver/sender in cheap talk?
- Find the area under the curve by taking the integral of the partitions
- If loss function is absolute value, have to split babbling into parts to keep values positive
* *For instance, ∫(1/2 - x)dx + ∫(x - 1/2)dx - Sum of welfare should be negative since there is loss
How do you find the Pareto dominant equilibrium in cheap talk?
- Maximize the number of partitions given “x”
- Plug back in and solve for “x”
- Use to determine interval lengths
How do you find the values of “b” where the only equilibrium is a babbling one?
- Plug n = 2 into nx+2bn(n-1) > 1
- Solve for “b”
- Plug in “x” almost equal to 0
If one or neither party can send a signal and there is a uniform offer presented to all market participants, which model are you dealing with?
Adverse selection
What is the Pareto efficient allocation in adverse selection?
The full information case
How do you find the equilibrium in adverse selection when information is asymmetric?
- Find w* = E[θl r(θ) ≤ w*]
- Max. the profit function (by solving for θ in terms of w. Plug back into expectation
* *Be sure to subtract all costs, whether wage or fixed if not already accounted for in the profit function).
How do you calculate the expected output given a w in adverse selection?
- Find the range of θ that satisfies r(θ) ≤ w
a) If uniform, E[θ] = midpoint –> a+b/2
b) If not, E[θl a ≤ θ ≤ b] = ∫ θ * f(θ)/F(b) - F(a)
What are the main assumptions of adverse selection?
- Multiple principals competing for agents
- The agent has a privately known type
- r(θ) is the type-dependent outside option (reservation)
What is the first-best solution in adverse selection?
- SPE where w*(θ) = θ
What is the second-best solution in adverse selection?
- PBE where r’(θ) > 0 and r(θ) < θ for both types
- w* = E[θl r(θ) ≤ w*]
- Equilibrium wage is increasing in θ
Why can’t the government produce better outcomes in the adverse selection model?
It is assumed that they do not have better information than the principals/agents
What are the assumptions of screening/NLP?
- Principal is uninformed, but sets terms of the exchange
- There are multiple types of agents
- Agents have different utilities w/ single-crossing property (high types willing to pay more for an additional unit).
What is the sequence of events in NLP?
- Agent privately observes θ
- Principal offers a menu {q, T}
- Agent accepts/rejects and outcomes are realized
What happens in the full info. NLP model?
Principal sets a binding IR (perfect price discrimination) by finding max. utility for the agent