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Computational Methods for Economists using Python

Contributor Guide

Contributor Guide

Coding in Python

1. Introduction to Python
2. Python Standard Library
3. Exception Handling and File Input/Output
4. Object Oriented Programming
5. NumPy
6. Pandas
7. Matplotlib
8. SciPy: Root finding, minimizing, interpolation
9. Docstrings and Documentation
10. Unit Testing

Git and GitHub

11. Git and GitHub

Basic Empirical Methods

12. Basic Empirical Methods
13. Logistic Regression Model

Basic Machine Learning

14. Basic Machine Learning

Neural Nets and Deep Learning

15. Neural Nets and Deep Learning

Structural Estimation

16. Introduction to Structural Estimation
17. Maximum Likelihood Estimation
18. Generalized Method of Moments Estimation
19. Simulated Method of Moments Estimation
20. Writing a Structural Estimation Paper

Appendix

Glossary
Appendix

References

References

Repository
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Neural Nets and Deep Learning

Contents

15.1. Footnotes

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By Richard W. Evans

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