UsefulLinks
Economics
Specialized Areas and Emerging Topics
Computational Economics
1. Introduction to Computational Economics
2. Mathematical Foundations
3. Programming Fundamentals
4. Numerical Methods
5. Simulation Methods
6. Agent-Based Modeling
7. Machine Learning in Economics
8. Macroeconomic Applications
9. Microeconomic Applications
10. Financial Economics Applications
11. Industrial Organization Applications
12. Labor Economics Applications
13. Advanced Computational Topics
3.
Programming Fundamentals
3.1.
Core Programming Concepts
3.1.1.
Variables and Data Types
3.1.1.1.
Numeric Types
3.1.1.2.
String Types
3.1.1.3.
Boolean Types
3.1.1.4.
Collections
3.1.2.
Control Structures
3.1.2.1.
Conditional Statements
3.1.2.2.
For Loops
3.1.2.3.
While Loops
3.1.2.4.
Loop Control
3.1.3.
Functions and Procedures
3.1.3.1.
Function Definition
3.1.3.2.
Parameters and Arguments
3.1.3.3.
Return Values
3.1.3.4.
Scope and Namespaces
3.1.4.
Data Structures
3.1.4.1.
Arrays and Lists
3.1.4.2.
Dictionaries and Hash Tables
3.1.4.3.
Sets
3.1.4.4.
Tuples
3.2.
Programming Languages for Economics
3.2.1.
Python
3.2.1.1.
Language Features
3.2.1.2.
Economic Applications
3.2.1.3.
Ecosystem and Libraries
3.2.2.
R
3.2.2.1.
Statistical Computing Focus
3.2.2.2.
Economic Applications
3.2.2.3.
Package System
3.2.3.
Julia
3.2.3.1.
High-Performance Computing
3.2.3.2.
Economic Applications
3.2.3.3.
Syntax and Features
3.2.4.
MATLAB
3.2.4.1.
Matrix-Oriented Computing
3.2.4.2.
Economic Toolboxes
3.2.4.3.
Numerical Computing
3.3.
Essential Libraries and Packages
3.3.1.
Scientific Computing Libraries
3.3.1.1.
NumPy for Numerical Computing
3.3.1.2.
SciPy for Scientific Computing
3.3.1.3.
Linear Algebra Operations
3.3.1.4.
Optimization Routines
3.3.2.
Data Manipulation Tools
3.3.2.1.
Pandas for Data Analysis
3.3.2.2.
Data Cleaning and Transformation
3.3.2.3.
Time Series Handling
3.3.3.
Visualization Libraries
3.3.3.1.
Matplotlib for Basic Plotting
3.3.3.2.
Seaborn for Statistical Visualization
3.3.3.3.
Interactive Visualization Tools
3.4.
Software Development Practices
3.4.1.
Version Control
3.4.1.1.
Git Fundamentals
3.4.1.2.
Repository Management
3.4.1.3.
Collaboration Workflows
3.4.2.
Code Quality
3.4.2.1.
Documentation Standards
3.4.2.2.
Code Style Guidelines
3.4.2.3.
Testing and Debugging
3.4.3.
Reproducible Research
3.4.3.1.
Environment Management
3.4.3.2.
Dependency Tracking
3.4.3.3.
Computational Notebooks
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4. Numerical Methods