Analyzed Nash Equilibrium and Collusion in Firms

  • Day: 2024-09-10
  • Time: 00:00 to 00:15
  • Project: Business
  • Workspace: WP 1: Strategic / Growth & Development
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Nash Equilibrium, Collusion, Game Theory, Python, Profit Calculation

Description

Session Goal

The session aimed to analyze Nash equilibrium and collusive behavior between two firms using game theory principles, with a focus on calculating quantities, profits, and critical discount factors.

Key Activities

  • Computed Nash equilibrium quantities and profits for two firms, identifying issues with collusive output being zero.
  • Developed Python code to calculate Nash equilibrium using SymPy, including tracking intermediate variables.
  • Analyzed collusive behavior and profits using Python, focusing on critical discount factors.
  • Evaluated inconsistencies in collusive profits and suggested recalculations for profit-sharing and discount factors.
  • Analyzed collusive profit calculation for Firm B, noting negative profits due to high marginal costs, and suggested revisiting the collusion setup for asymmetric output shares.

Achievements

  • Successfully calculated Nash equilibrium quantities and profits.
  • Developed and executed Python code for Nash equilibrium and collusion analysis.
  • Identified and highlighted inconsistencies in collusive profits and critical discount factors.

Pending Tasks

  • Recalculate profit-sharing and discount factors to address identified inconsistencies.
  • Revisit collusion setup to allow for asymmetric output shares to improve firm profitability.

Evidence

  • source_file=2024-09-10.sessions.jsonl, line_number=3, event_count=0, session_id=f31949f990e8b1337ffd177c828a4f532e9134486be0608840e3417d3bafad64
  • event_ids: []