How to Solve Bayesian Game Equations?

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SUMMARY

The discussion focuses on solving Bayesian game equations, specifically the Cournot Duopoly with incomplete information. The profit functions are defined as u_i = q_i(θ_i - q_i - q_j), where Firm 1 has a known type θ_1 = 1 and Firm 2 has private information about its type θ_2. The equilibrium quantities are derived as q_'1 = 1/3, q_'2(3/4) = 11/24, and q_'2(5/4) = 5/24. The solution involves deriving best response functions for both firms and solving a system of equations to find the Nash equilibrium.

PREREQUISITES
  • Understanding of Bayesian games and Nash equilibrium concepts
  • Familiarity with Cournot competition models
  • Ability to solve simultaneous equations
  • Knowledge of profit function derivation in game theory
NEXT STEPS
  • Study the derivation of best response functions in Bayesian games
  • Learn about the application of Cournot models in economic theory
  • Explore methods for solving systems of equations in game theory
  • Investigate the implications of incomplete information in strategic decision-making
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Economists, game theorists, and students studying advanced microeconomics, particularly those focusing on strategic interactions in oligopolistic markets.

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Homework Statement



My Textbook gives the following example problem:

Cournot Duopoly with incomplete information.

The profit functions are given by:
u_i = q_i(θ_¡ - q_i - q_j)

Firm 1 has one type θ_1 = 1, but firm 2 has private information about its type θ_2. Firm 1
believes that θ_2= 3/4 with probability 1/2 and θ _2 = 5/4 with probability 1/2, and this belief is common knowledge.

We will look for a pure strategy equilibrium of this game. Firm 2 of type θ_2’s decision
problem is to

max q_2: q_2(θ_2 - q_1 - q_2)

which is solved at
q_'2(θ_2) = (θ_2-q_1)/2


Firm 1’s decision problem, on the other hand, is
max q_1: 1/2 * q_1 (1 - q_1 - q_'2(3/4)) + 1/2 * q_1(1-q_1-q_'2(5/4))

which is solved at
q_'1 = (2-q_'2 (3/4)-q_'2(5/4))/4

Solving yields,
q_'1 = 1/3
q_'2(3/4) = 11/24
q_'2(5/4) = 5/24

Atempt at a solution

I can't figure out how they got from the equations q_'1 and q_'2 to the answers given in the "solving yields" part. It seems like simultaneous equations, but I'm not sure what to do with the q_1 or really where to begin.
 
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Recall that in any bayesian game, strategies are mappings from types to quantities. This means that firm 2 'quantity' must specify what the the type \theta_{2}=3/4 will produce and how much the type \theta_{2}=5/4 will produce. Now, since firm 2 knows his own type, it can maximize using this information: this is why you obtain two best response functions, one for each type. Next, to compute the Nash equilibrium you also need to derive a best response for firm 1. Firm 1 only know the probability of each type and hence, incorporates two different quantities (one for each type) together with the probabilities of meeting each type in his maximization problem. This will give you a third best response that must be a function of the quantity type \theta_2=3/4 is expected to produce, and the quantity that type \theta_2=5/4 is expected to produce. All this gives you 3 equations (2 best responses for firm 2 and one for firm 1) and 3 unknowns (quanties for each type of firm 2 and the quantity for firm 1). You can solve this system of equations the way you like (substitution, reduction, etc). This will give you the solutions you state in the last part of your question.
 

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