Jupyter Notebooks (*.ipynb):
A set of accompanying Jupyter notebooks can be used interactively for instruction and self-learning purposes and to replicate the results reported in the article and the book. The package is also hosted on its own GitHub open-source repository from which it can be downloaded.
1) Jupyter notebook for replicating the results in Barbero and Zofío (2022):
2) Jupyter notebooks for replicating the examples and empirical application in Pastor, Aparicio and Zofío (2022):
Bundle with the notebooks for all chapters: Download
Individual notebooks for each chapter:
- Chapter 2. Conceptual Background: Firms’ Objectives, Decision Variables, and Economic Efficiency:
Replication notebook - Chapter 3. Shephard’s Input and Output Distance Functions: Cost and Revenue Efficiency Decompositions:
Replication notebook - Chapter 4. The Generalized Distance Function (GDF): Profitability Efficiency Decomposition:
Replication notebook - Chapter 5. The Russell Measures: Economic Inefficiency Decompositions
Replication notebook - Chapter 6. The Weighted Additive Distance Function (WADF): Economic Inefficiency Decompositions
Replication notebook - Chapter 7. The Enhanced Russell Graph Measure (ERG=SBM): Economic Inefficiency Decompositions
Replication notebook - Chapter 8. The Directional Distance Function (DDF): Economic Inefficiency Decompositions
Replication notebook - Chapter 9: The Hölder Distance Functions: Economic Inefficiency Decompositions
Replication notebook - Chapter 11. The Modified Directional Distance Function (MDDF): Economic Inefficiency Decompositions
Replication notebook - Chapter 12. The Reverse Directional Distance Function (RDDF): Economic Inefficiency Decomposition
Replication notebook - Chapter 13. A Unifying Framework for Decomposing Economic Inefficiency: The General Direct Approach and the Reverse Approaches
Replication notebook