** 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