A First Course in Quantitative Economics with Python

This lecture series provides an introduction to quantitative economics using Python.

Introduction

• 1. About These Lectures

Economic Data

• 2. Long-Run Growth
• 3. Business Cycles
• 4. Price Level Histories
• 5. Income and Wealth Inequality

Foundations

• 6. Introduction to Supply and Demand
• 7. Linear Equations and Matrix Algebra
• 8. Complex Numbers and Trigonometry
• 9. Geometric Series for Elementary Economics

Linear Dynamics: Finite Horizons

• 10. Present Values
• 11. Consumption Smoothing
• 12. Equalizing Difference Model
• 13. A Monetarist Theory of Price Levels
• 14. Monetarist Theory of Price Levels with Adaptive Expectations

Linear Dynamics: Infinite Horizons

• 15. Eigenvalues and Eigenvectors

Probability and Distributions

• 16. Distributions and Probabilities
• 17. LLN and CLT
• 18. Monte Carlo and Option Pricing
• 19. Heavy-Tailed Distributions
• 20. Racial Segregation

Nonlinear Dynamics

• 21. The Solow-Swan Growth Model
• 22. Dynamics in One Dimension
• 23. The Cobweb Model
• 24. The Overlapping Generations Model
• 25. Commodity Prices

Monetary-Fiscal Policy Interactions

• 26. Money Financed Government Deficits and Price Levels
• 27. Unpleasant Monetarist Arithmetic
• 28. Inflation Rate Laffer Curves
• 29. Laffer Curves with Adaptive Expectations

Stochastic Dynamics

• 30. AR1 Processes
• 31. Markov Chains: Basic Concepts
• 32. Markov Chains: Irreducibility and Ergodicity
• 33. Univariate Time Series with Matrix Algebra

Optimization

• 34. Linear Programming
• 35. Shortest Paths

Modeling in Higher Dimensions

• 36. The Perron-Frobenius Theorem
• 37. Input-Output Models
• 38. A Lake Model of Employment
• 39. Networks

Markets and Competitive Equilibrium

• 40. Supply and Demand with Many Goods
• 41. Market Equilibrium with Heterogeneity

Estimation

• 42. Simple Linear Regression Model
• 43. Maximum Likelihood Estimation

Other

• 44. Troubleshooting
• 45. References
• 46. Execution Statistics