本期推荐一份Python学习资料，由Sargent教授和Stachurski教授领导开发的量化经济学课程。
1.Objective
The lecture series treats
- algorithms and numerical methods for quantitative economic problems,
- related mathematical and statistical concepts, and
- basics of coding skills and software engineering.
As stated above, the coding language for this lecture series is Python.
2.Outline
- Python Programming for Economics and Finance
- Quantitative Economics with Python
- Advanced Quantitative Economics with Python
The breakdown is as the names suggest. The first series focuses on programming and is a prerequisite for both the second and the third. The second series is aimed at (very) advanced undergraduate students and beginning graduate students. The third is for advanced graduate students and researchers.
2.1 Python Programming for Economics and Finance
Introduction to Python
- About Python
- Setting up Your Python Environment
- An Introductory Example
- Functions
- Python Essentials
- OOP I: Introduction to Object Oriented Programming
- OOP II: Building Classes
The Scientific Libraries
- Python for Scientific Computing
- NumPy
- Matplotlib
- SciPy
- Numba
- Parallelization
- Pandas
Advanced Python Programming
- Writing Good Code
- More Language Features
- Debugging
Other
- Troubleshooting
- Execution Statistics
2.2 Quantitative Economics with Python
Tools and Techniques
- Geometric Series for Elementary Economics
- Multivariate Hypergeometric Distribution
- Modeling COVID 19
- Linear Algebra
- Complex Numbers and Trigonometry
- LLN and CLT
- Heavy-Tailed Distributions
- Multivariate Normal Distribution
- Univariate Time Series with Matrix Algebra
Introduction to Dynamics
- Dynamics in One Dimension
- AR1 Processes
- Finite Markov Chains
- Inventory Dynamics
- Linear State Space Models
- Application: The Samuelson Multiplier-Accelerator
- Kesten Processes and Firm Dynamics
- Wealth Distribution Dynamics
- A First Look at the Kalman Filter
- Shortest Paths
- Cass-Koopmans Planning Problem
- Cass-Koopmans Competitive Equilibrium
Search
- Job Search I: The McCall Search Model
- Job Search II: Search and Separation
- Job Search III: Fitted Value Function Iteration
- Job Search IV: Correlated Wage Offers
- Job Search V: Modeling Career Choice
- Job Search VI: On-the-Job Search
Consumption, Savings and Growth
- Cake Eating I: Introduction to Optimal Saving
- Cake Eating II: Numerical Methods
- Optimal Growth I: The Stochastic Optimal Growth Model
- Optimal Growth II: Accelerating the Code with Numba
- Optimal Growth III: Time Iteration
- Optimal Growth IV: The Endogenous Grid Method
- The Income Fluctuation Problem I: Basic Model
- The Income Fluctuation Problem II: Stochastic Returns on Assets
Information
- Job Search VII: Search with Learning
- Likelihood Ratio Processes
- A Problem that Stumped Milton Friedman
- Exchangeability and Bayesian Updating
- Likelihood Ratio Processes and Bayesian Learning
- Bayesian versus Frequentist Decision Rules
LQ Control
- LQ Control: Foundations
- The Permanent Income Model
- Permanent Income II: LQ Techniques
- Production Smoothing via Inventories
Multiple Agent Models
- Schelling’s Segregation Model
- A Lake Model of Employment and Unemployment
- Rational Expectations Equilibrium
- Stability in Linear Rational Expectations Models
- Markov Perfect Equilibrium
- Uncertainty Traps
- The Aiyagari Model
Asset Pricing and Finance
- Asset Pricing: Finite State Models
- Competitive equilibria with Arrow securities
- Heterogeneous Beliefs and Bubbles
Data and Empirics
- Pandas for Panel Data
- Linear Regression in Python
- Maximum Likelihood Estimation
Other
- Troubleshooting
- References
- Execution Statistics
2.3 Advanced Quantitative Economics with Python
About these Lectures
Tools and Techniques
- Orthogonal Projections and Their Applications
- Continuous State Markov Chains
- Reverse Engineering a la Muth
- Discrete State Dynamic Programming
LQ Control
- Information and Consumption Smoothing
- Consumption Smoothing with Complete and Incomplete Markets
- Tax Smoothing with Complete and Incomplete Markets
- Robustness
- Markov Jump Linear Quadratic Dynamic Programming
- How to Pay for a War: Part 1
- How to Pay for a War: Part 2
- How to Pay for a War: Part 3
- Optimal Taxation in an LQ Economy
Multiple Agent Models
- Robust Markov Perfect Equilibrium
- Default Risk and Income Fluctuations
- Globalization and Cycles
- Coase’s Theory of the Firm
Dynamic Linear Economies
- Recursive Models of Dynamic Linear Economies
- Growth in Dynamic Linear Economies
- Lucas Asset Pricing Using DLE
- IRFs in Hall Models
- Permanent Income Model using the DLE Class
- Rosen Schooling Model
- Cattle Cycles
- Shock Non Invertibility
Classic Linear Models
- Von Neumann Growth Model (and a Generalization)
Time Series Models
- Covariance Stationary Processes
- Estimation of Spectra
- Additive and Multiplicative Functionals
- Classical Control with Linear Algebra
- Classical Prediction and Filtering With Linear Algebra
- Knowing the Forecasts of Others
Asset Pricing and Finance
- Asset Pricing II: The Lucas Asset Pricing Model
- Two Modifications of Mean-Variance Portfolio Theory
- Irrelevance of Capital Structure with Complete Markets
- Equilibrium Capital Structures with Incomplete Markets
Dynamic Programming Squared
- Stackelberg Plans
- Ramsey Plans, Time Inconsistency, Sustainable Plans
- Optimal Taxation with State-Contingent Debt
- Optimal Taxation without State-Contingent Debt
- Fluctuating Interest Rates Deliver Fiscal Insurance
- Fiscal Risk and Government Debt
- Competitive Equilibria of a Model of Chang
- Credible Government Policies in a Model of Chang
References
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