Undergraduate Course¶

• All
• Undergraduate course
• Graduate course

• About these Lectures
• Introduction to Python
  • About Python
  • Setting up Your Python Environment
  • An Introductory Example
  • Python Essentials
  • OOP I: Introduction to Object Oriented Programming
  • OOP II: Building Classes
• The Scientific Libraries
  • Python for Scientific Computing
  • NumPy
  • Matplotlib
  • SciPy
  • Numba
  • Parallelization
  • Pandas
• Advanced Python Programming
  • Writing Good Code
  • More Language Features
  • Debugging
• Data and Empirics
  • Pandas for Panel Data
  • Linear Regression in Python
  • Maximum Likelihood Estimation
• Tools and Techniques
  • Geometric Series for Elementary Economics
  • Linear Algebra
  • Complex Numbers and Trigonometry
  • LLN and CLT
  • Linear State Space Models
  • Finite Markov Chains
  • Cass-Koopmans Optimal Growth Model
  • A First Look at the Kalman Filter
• Dynamic Programming
  • Shortest Paths
  • Job Search I: The McCall Search Model
  • Job Search II: Search and Separation
  • Optimal Savings I: The Permanent Income Model
  • Optimal Savings II: LQ Techniques
  • Consumption Smoothing with Complete and Incomplete Markets
• LQ Control
  • LQ Control: Foundations
  • Optimal Savings I: The Permanent Income Model
• Multiple Agent Models
  • Schelling’s Segregation Model
  • A Lake Model of Employment and Unemployment
  • Rational Expectations Equilibrium
  • Markov Perfect Equilibrium
• Asset Pricing and Finance
  • Asset Pricing I: Finite State Models
• References