A Julia package for economic efficiency measurement using Data Envelopment Analysis (DEA).
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BenchmarkingEconomicEfficiency.jl is a Julia package that provides functions for economic efficiency measurement using Data Envelopment Analysis (DEA). The package is an extension of the DataEnvelopmentAnalysis.jl package. The package is being developed for Julia 1.0 and above on Linux, macOS, and Windows.
For the methodological understanding and empirical interpretation of the different models we refer the reader to the accompanying book: Pastor, Jesús T., Aparicio, Juan, & Zofío, José L. (2022), Benchmarking Economic Efficiency: Technical and Allocative Fundamentals, International Series in Operations Research & Management Science (ISOR, Vol. 346). Springer, Cham. https://doi.org/10.1007/978-3-030-84397-7.
The package uses internally the JuMP modelling language for mathematicall optimization with solvers GLPK and Ipopt.
The package can be installed with the Julia package manager:
julia> using Pkg; Pkg.add("BenchmarkingEconomicEfficiency")Profit DEA models
- Profit Russell model.
- Profit Additive model.
- Profit Enhanced Russell Graph (or Slack Based) model.
- Profit Directional Distance Function model.
- Profit Hölder model.
- Profit Modified Directional Distance Function model.
- Profit Reverse Directional Distance Function model.
- Profit General Direct Approach model.
Profitability DEA models
- Profitability Efficiency measurement.
Cost DEA models
- Cost Radial model
- Cost Russell model.
- Cost Additive model.
- Cost Directional Distance Function model.
- Cost Hölder model.
- Cost Reverse Directional Distance Function model.
- Cost General Direct Approach model.
Revenue DEA models
- Revenue Radial model
- Revenue Russell model.
- Revenue Additive model.
- Revenue Directional Distance Function model.
- Revenue Hölder model.
- Revenue Reverse Directional Distance Function model.
- Revenue General Direct Approach model.
BenchmarkingEconomicEfficiency.jl is being developed by Javier Barbero and José Luís Zofío.