Name | Lecture | Office hours | Contact | |
Instructor | Marcin Pęski | Monday, 2-5pm, WI 523 | Tuesday 2-6pm by appointment (email), Max Gluskin 207 | mpeski@gmail.com |
TA | Rami Abou-Seido | TBA | n/a |
Date | Topic | Videos | Questions | Concepts | Skills | Examples | Extra readings |
06-01 | What is information? How to reason about information? |
States of the world.
Information. Information structure. Knowledge sets. Reasoning about knowledge. Common knowledge. |
Represent a story with asymmetric information with state space and information of players.
Explain how new information affects the information structure. Reason about knowledge and knowledge about knowledge. |
Investigation.
Hats. Two generals |
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13-01 | How to evaluate evidence? |
Type space.
Bayes formula. Prior and interim beliefs. Bayesian Nash equilibrium. |
Represent a story with asymmetric information with a type space.
Use the Bayes formula to find conditional probabilities Derive interim beliefs from a prior. Find Bayesian Nash equilibria in games with incomplete information. |
Mammograms.
Investigation. Jury. |
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20-01 |
Why it is difficult to get flood insurance?
Why the economy class seats are so uncomfortable? |
Market unraveling due to adverse selection.
Screening with menus. Individual rationality and incentive compatibility. |
Find conditions for market unraveling due to adverse selection
Check whether a menu is incentive compatible and individually rational. Find optimal menus. |
Market for lemons.
Health insurance with pre-existing condition. Price-quantity discrimination. |
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27-01 |
When talk is cheap.
Why to always bring your transcript to the interview? And why top MBA schools do not reveal grades? |
Communication game. Equilibrium with beliefs.
Incentives to communicate in cheap talk games. Communication with verifiable talk. Verifiable information disclosure. Good news and bad news. |
Find equilibria in simple cheap talk games.
Explain when refusing to reveal information is informative. |
Doctor and patient with alligned and misalligned preferences.
Transcript. Grade revelation. |
Osborne 10.8 (wait with reading after lecture | ||
03-02 | Learning from others behavior. |
Extensive form games.
Nash and Subgame perfect equilibrium. Extensive form games with incomplete information. Weak Perfect Bayesian Equilibrium. |
Find equilibria of extensive form games.
Use Bayes formula and players’ strategies to update beliefs. Find equilibria of simple extensive form games with incomplete information. . |
Entry game.
Restaurants. |
Osborne 10.1-10.3 | ||
10-02 | Midterm. | ||||||
24-02 |
Why do we go to the university?
Suits, wedding rings, and red frogs. |
Signaling games.
Pooling and separating equilibria. Intuitive criterion. |
Find equilibria of signaling games |
Spence’s job market.
Suits. Conspicuous consumption. |
Osborne 10.5-10.7 | ||
2-03 | How to pay a worker. |
Moral hazard.
Linear contacts and bonuses. Optimal contracts. |
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9-03 | How to pay a worker, part II | TBA | |||||
16-03 | “We never negotiate with terrorists.” |
Modeling reputations.
WPBE with mixed strategies. |
Conditions for successful reputation building (payoffs, length of the game, beliefs)
Finding reputation equilibria Computing value of reputation |
Chain store game.
Centipede game. Reputation for promise-keeping |
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23-03 |
Herds and fashions.
How to (not) follow the others |
Informational cascades
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Size of herd necessary for a cascade
Finding probability of a bad cascade |
Herds. | |||
30-03 |
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Trump | n | eu | ek |
U | (1 − p)/(1 − p + (1 − q)p) | ((1 − q)p)/(1 − p + (1 − q)p) | 0 |
K | 0 | 0 | 1 |
Mueller | n | eu | ek |
N | 1 | 0 | 0 |
E | 0 | 1 − q | q |
ω = n:Mueller\Trump | Wait | Fire Mueller |
Finish | 1, 1 | 1, 0 |
Continue | 0, 2 | 0, − 5 |
ω = eu, ek:Mueller\Trump | Wait | Fire Mueller |
Finish | 2, − 5 | 0, 0 |
Continue | 3, − 10 | 1, − 5 |
Ann\Damian | ω = Bob | ω = l |
Fire Bob | 1, t − vB | 0, − v |
Fire Celine | 0, − vC | 1, t − vC |
Wellington wins | BuyM | SellM |
BuyR | 1,1 | 3,-3 |
SellR | -3,3 | -1,-1 |
Napoleon wins | BuyM | SellM |
BuyR | -1,-1 | -3,3 |
SellR | 3,-3 | 1,1 |
Tiger’s payoffs | f | s |
chase | − 1 | 2 |
no chase | 0 | 0 |
Payoffs | not attacked | attacked, type h | attacked, type s |
singing | 1 | − df | − ds |
rnning away | 1 | 0 | 0 |
Consultant, Client | Hire | No hire |
Effort | a, 1 | 0,0 |
No effort | b, − 1 | 0,0 |