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. Inflation During French Revolution
• 6. Income and Wealth Inequality

Foundations

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

Linear Dynamics: Finite Horizons

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

Linear Dynamics: Infinite Horizons

• 17. Eigenvalues and Eigenvectors
• 18. Computing Square Roots

Probability and Distributions

• 19. Distributions and Probabilities
• 20. LLN and CLT
• 21. Monte Carlo and Option Pricing
• 22. Heavy-Tailed Distributions
• 23. Racial Segregation

Nonlinear Dynamics

• 24. Dynamics in One Dimension
• 25. The Solow-Swan Growth Model
• 26. The Cobweb Model
• 27. The Overlapping Generations Model
• 28. Commodity Prices

Monetary-Fiscal Policy Interactions

• 29. Money Financed Government Deficits and Price Levels
• 30. Some Unpleasant Monetarist Arithmetic
• 31. Inflation Rate Laffer Curves
• 32. Laffer Curves with Adaptive Expectations

Stochastic Dynamics

• 33. AR(1) Processes
• 34. Markov Chains: Basic Concepts
• 35. Markov Chains: Irreducibility and Ergodicity
• 36. Univariate Time Series with Matrix Algebra

Optimization

• 37. Linear Programming
• 38. Shortest Paths

Modeling in Higher Dimensions

• 39. The Perron-Frobenius Theorem
• 40. Input-Output Models
• 41. A Lake Model of Employment
• 42. Networks

Markets and Competitive Equilibrium

• 43. Supply and Demand with Many Goods
• 44. Market Equilibrium with Heterogeneity

Estimation

• 45. Simple Linear Regression Model
• 46. Maximum Likelihood Estimation

Other

• 47. Troubleshooting
• 48. References
• 49. Execution Statistics