Intermediate Quantitative Economics with Python

This website presents a set of lectures on quantitative economic modeling.

Tools and Techniques

• 1. Modeling COVID 19
• 2. Linear Algebra
• 3. QR Decomposition
• 4. Circulant Matrices
• 5. Singular Value Decomposition (SVD)
• 6. VARs and DMDs
• 7. Using Newton’s Method to Solve Economic Models

Elementary Statistics

• 8. Elementary Probability with Matrices
• 9. LLN and CLT
• 10. Two Meanings of Probability
• 11. Multivariate Hypergeometric Distribution
• 12. Multivariate Normal Distribution
• 13. Fault Tree Uncertainties
• 14. Introduction to Artificial Neural Networks
• 15. Randomized Response Surveys
• 16. Expected Utilities of Random Responses

Linear Programming

• 17. Optimal Transport
• 18. Von Neumann Growth Model (and a Generalization)

Introduction to Dynamics

• 19. Finite Markov Chains
• 20. Inventory Dynamics
• 21. Linear State Space Models
• 22. Samuelson Multiplier-Accelerator
• 23. Kesten Processes and Firm Dynamics
• 24. Wealth Distribution Dynamics
• 25. A First Look at the Kalman Filter
• 26. Another Look at the Kalman Filter

Search

• 27. Job Search I: The McCall Search Model
• 28. Job Search II: Search and Separation
• 29. Job Search III: Fitted Value Function Iteration
• 30. Job Search IV: Correlated Wage Offers
• 31. Job Search V: Modeling Career Choice
• 32. Job Search VI: On-the-Job Search
• 33. Job Search VII: A McCall Worker Q-Learns

Consumption, Savings and Capital

• 34. Cass-Koopmans Model
• 35. Cass-Koopmans Competitive Equilibrium
• 36. Transitions in an Overlapping Generations Model
• 37. Cake Eating I: Introduction to Optimal Saving
• 38. Cake Eating II: Numerical Methods
• 39. Optimal Growth I: The Stochastic Optimal Growth Model
• 40. Optimal Growth II: Accelerating the Code with Numba
• 41. Optimal Growth III: Time Iteration
• 42. Optimal Growth IV: The Endogenous Grid Method
• 43. The Income Fluctuation Problem I: Basic Model
• 44. The Income Fluctuation Problem II: Stochastic Returns on Assets

Bayes Law

• 45. Non-Conjugate Priors
• 46. Posterior Distributions for AR(1) Parameters
• 47. Forecasting an AR(1) Process

Information

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

LQ Control

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

Multiple Agent Models

• 62. A Lake Model of Employment and Unemployment
• 63. Rational Expectations Equilibrium
• 64. Stability in Linear Rational Expectations Models
• 65. Markov Perfect Equilibrium
• 66. Uncertainty Traps
• 67. The Aiyagari Model

Asset Pricing and Finance

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

Data and Empirics

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

Auctions

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

Other

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