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
Elementary Statistics
- 10. Elementary Probability with Matrices
- 11. Univariate Time Series with Matrix Algebra
- 12. LLN and CLT
- 13. Two Meanings of Probability
- 14. Multivariate Hypergeometric Distribution
- 15. Multivariate Normal Distribution
- 16. Heavy-Tailed Distributions
- 17. Fault Tree Uncertainties
- 18. Introduction to Artificial Neural Networks
- 19. Randomized Response Surveys
- 20. Expected Utilities of Random Responses
Linear Programming
Introduction to Dynamics
Search
Consumption, Savings and Capital
- 41. Cass-Koopmans Model
- 42. Cass-Koopmans Competitive Equilibrium
- 43. Cake Eating I: Introduction to Optimal Saving
- 44. Cake Eating II: Numerical Methods
- 45. Optimal Growth I: The Stochastic Optimal Growth Model
- 46. Optimal Growth II: Accelerating the Code with Numba
- 47. Optimal Growth III: Time Iteration
- 48. Optimal Growth IV: The Endogenous Grid Method
- 49. The Income Fluctuation Problem I: Basic Model
- 50. The Income Fluctuation Problem II: Stochastic Returns on Assets
Bayes Law
Information
- 54. Job Search VII: Search with Learning
- 55. Likelihood Ratio Processes
- 56. Computing Mean of a Likelihood Ratio Process
- 57. A Problem that Stumped Milton Friedman
- 58. Exchangeability and Bayesian Updating
- 59. Likelihood Ratio Processes and Bayesian Learning
- 60. Incorrect Models
- 61. Bayesian versus Frequentist Decision Rules
LQ Control
Multiple Agent Models
Asset Pricing and Finance
Data and Empirics
Previous website
While this new site will receive all future updates, you may still view the old site here for the next month.