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Quantitative Economics with Python
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Thomas J. Sargent
John Stachurski
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Undergraduate Course
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Undergraduate course
Graduate course
About these Lectures
Introduction to Python
About Python
Setting up Your Python Environment
An Introductory Example
Python Essentials
OOP I: Introduction to Object Oriented Programming
The Scientific Libraries
NumPy
Matplotlib
SciPy
Numba
Other Scientific Libraries
Advanced Python Programming
Writing Good Code
OOP II: Building Classes
OOP III: Samuelson Multiplier Accelerator
More Language Features
Debugging
Data and Empirics
Pandas
Pandas for Panel Data
Linear Regression in Python
Maximum Likelihood Estimation
Tools and Techniques
Geometric Series for Elementary Economics
Linear Algebra
Complex Numbers and Trignometry
LLN and CLT
Linear State Space Models
Finite Markov Chains
Cass-Koopmans Optimal Growth Model
A First Look at the Kalman Filter
Dynamic Programming
Shortest Paths
Job Search I: The McCall Search Model
Job Search II: Search and Separation
Optimal Savings I: The Permanent Income Model
Optimal Savings II: LQ Techniques
Consumption Smoothing with Complete and Incomplete Markets
LQ Control
LQ Control: Foundations
Optimal Savings I: The Permanent Income Model
Multiple Agent Models
Schelling’s Segregation Model
A Lake Model of Employment and Unemployment
Rational Expectations Equilibrium
Markov Perfect Equilibrium
Asset Pricing and Finance
Asset Pricing I: Finite State Models
References
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