Quantitative Economics with Python

This website presents a set of lectures on quantitative economic modeling, designed and written by Thomas J. Sargent and John Stachurski.

For an overview of the series, see this page

Tools and Techniques

• 1. Geometric Series for Elementary Economics
• 2. Modeling COVID 19
• 3. Linear Algebra
• 4. QR Decomposition
• 5. Complex Numbers and Trigonometry
• 6. Circulant Matrices

Elementary Statistics

• 7. LLN and CLT
• 8. Two Meanings of Probability
• 9. Multivariate Hypergeometric Distribution
• 10. Multivariate Normal Distribution
• 11. Heavy-Tailed Distributions
• 12. Fault Tree Uncertainties
• 13. Univariate Time Series with Matrix Algebra
• 14. Introduction to Artificial Neural Networks
• 15. Randomized Response Surveys
• 16. Expected Utilities of Random Responses
• 17. Singular Value Decomposition (SVD)

Linear Programming

• 18. Linear Programming
• 19. Optimal Transport
• 20. Von Neumann Growth Model (and a Generalization)

Introduction to Dynamics

• 21. Dynamics in One Dimension
• 22. AR1 Processes
• 23. Finite Markov Chains
• 24. Inventory Dynamics
• 25. Linear State Space Models
• 26. Samuelson Multiplier-Accelerator
• 27. Kesten Processes and Firm Dynamics
• 28. Wealth Distribution Dynamics
• 29. A First Look at the Kalman Filter
• 30. Shortest Paths
• 31. Cass-Koopmans Planning Problem
• 32. Cass-Koopmans Competitive Equilibrium

Search

• 33. Job Search I: The McCall Search Model
• 34. Job Search II: Search and Separation
• 35. Job Search III: Fitted Value Function Iteration
• 36. Job Search IV: Correlated Wage Offers
• 37. Job Search V: Modeling Career Choice
• 38. Job Search VI: On-the-Job Search

Consumption, Savings and Growth

• 39. Cake Eating I: Introduction to Optimal Saving
• 40. Cake Eating II: Numerical Methods
• 41. Optimal Growth I: The Stochastic Optimal Growth Model
• 42. Optimal Growth II: Accelerating the Code with Numba
• 43. Optimal Growth III: Time Iteration
• 44. Optimal Growth IV: The Endogenous Grid Method
• 45. The Income Fluctuation Problem I: Basic Model
• 46. The Income Fluctuation Problem II: Stochastic Returns on Assets

Information

• 47. Job Search VII: Search with Learning
• 48. Likelihood Ratio Processes
• 49. Computing Mean of a Likelihood Ratio Process
• 50. A Problem that Stumped Milton Friedman
• 51. Exchangeability and Bayesian Updating
• 52. Likelihood Ratio Processes and Bayesian Learning
• 53. Bayesian versus Frequentist Decision Rules

LQ Control

• 54. LQ Control: Foundations
• 55. Lagrangian for LQ Control
• 56. Eliminating Cross Products
• 57. The Permanent Income Model
• 58. Permanent Income II: LQ Techniques
• 59. Production Smoothing via Inventories

Multiple Agent Models

• 60. Schelling’s Segregation Model
• 61. A Lake Model of Employment and Unemployment
• 62. Rational Expectations Equilibrium
• 63. Stability in Linear Rational Expectations Models
• 64. Markov Perfect Equilibrium
• 65. Uncertainty Traps
• 66. The Aiyagari Model

Asset Pricing and Finance

• 67. Asset Pricing: Finite State Models
• 68. Competitive Equilibria with Arrow Securities
• 69. Heterogeneous Beliefs and Bubbles

Data and Empirics

• 70. Pandas for Panel Data
• 71. Linear Regression in Python
• 72. Maximum Likelihood Estimation

Auctions

• 73. First-Price and Second-Price Auctions
• 74. Multiple Good Allocation Mechanisms

Other

• 75. Troubleshooting
• 76. References
• 77. Execution Statistics

Previous website

While this new site will receive all future updates, you may still view the old site here for the next month.