Quantitative Economics with Julia

This website presents a set of lectures on quantitative economic modeling, designed and written by Jesse Perla, Thomas J. Sargent and John Stachurski. The language instruction is Julia.

Getting Started with Julia

• 1. Setting up Your Julia Environment
• 2. Introductory Examples
• 3. Julia Essentials
• 4. Arrays, Tuples, Ranges, and Other Fundamental Types
• 5. Introduction to Types and Generic Programming

Package Ecosystem

• 6. Generic Programming
• 7. General Purpose Packages
• 8. Data and Statistics Packages
• 9. Solvers, Optimizers, and Automatic Differentiation

Software Engineering

• 10. Visual Studio Code and Other Tools
• 11. GitHub, Version Control and Collaboration
• 12. Packages, Testing, and Continuous Integration
• 13. The Need for Speed

Tools and Techniques

• 14. Geometric Series for Elementary Economics
• 15. Linear Algebra
• 16. Orthogonal Projections and Their Applications
• 17. LLN and CLT
• 18. Continuous State Markov Chains
• 19. Numerical Linear Algebra and Factorizations
• 20. Krylov Methods and Matrix Conditioning

Introduction to Dynamics

• 21. Dynamics in One Dimension
• 22. AR1 Processes
• 23. Finite Markov Chains
• 24. Linear State Space Models
• 25. Wealth Distribution Dynamics
• 26. A First Look at the Kalman Filter
• 27. Shortest Paths

Dynamic Programming

• 28. Job Search I: The McCall Search Model
• 29. Job Search II: Search and Separation
• 30. A Problem that Stumped Milton Friedman
• 31. Job Search III: Search with Learning
• 32. Job Search IV: Modeling Career Choice
• 33. Job Search V: On-the-Job Search
• 34. Optimal Growth I: The Stochastic Optimal Growth Model
• 35. Optimal Growth II: Time Iteration
• 36. Optimal Growth III: The Endogenous Grid Method
• 37. LQ Dynamic Programming Problems
• 38. Optimal Savings I: The Permanent Income Model
• 39. Optimal Savings II: LQ Techniques
• 40. Consumption and Tax Smoothing with Complete and Incomplete Markets
• 41. Optimal Savings III: Occasionally Binding Constraints
• 42. Robustness
• 43. Discrete State Dynamic Programming

Modeling in Continuous Time

• 44. Modeling COVID 19 with Differential Equations
• 45. Modeling Shocks in COVID 19 with Stochastic Differential Equations

Multiple Agent Models

• 46. Schelling’s Segregation Model
• 47. A Lake Model of Employment and Unemployment
• 48. Rational Expectations Equilibrium
• 49. Markov Perfect Equilibrium
• 50. Asset Pricing I: Finite State Models
• 51. Asset Pricing II: The Lucas Asset Pricing Model
• 52. Asset Pricing III: Incomplete Markets
• 53. Uncertainty Traps
• 54. The Aiyagari Model
• 55. Default Risk and Income Fluctuations
• 56. Globalization and Cycles

Time Series Models

• 57. Covariance Stationary Processes
• 58. Estimation of Spectra
• 59. Additive Functionals
• 60. Multiplicative Functionals
• 61. Classical Control with Linear Algebra
• 62. Classical Filtering With Linear Algebra

Dynamic Programming Squared

• 63. Dynamic Stackelberg Problems
• 64. Optimal Taxation in an LQ Economy
• 65. Optimal Taxation with State-Contingent Debt
• 66. Optimal Taxation without State-Contingent Debt

Other

• 67. About these Lectures
• 68. Troubleshooting
• 69. References
• 70. Execution Statistics