A Julia package for efficiency and productivity measurement using Data Envelopment Analysis (DEA)
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DataEnvelopmentAnalysis.jl is a Julia package that provides functions for efficiency and productivity measurement using Data Envelopment Analysis (DEA). Particularly, it implements a variety of technical efficiency models, economic efficiency models and productivity change models.
The package is being developed for Julia 1.6 and above on Linux, macOS, and Windows.
The packes 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("DataEnvelopmentAnalysis")The latest stable release documentation is available here.
Technical efficiency DEA models
- Radial input and output oriented model.
- Directional distance function model.
- Additive models: weighted additive model, measure of inefficiency proportions (MIP), normalized weighted additive model, range adjusted measure (RAM), bounded adjusted measure (BAM).
- Generalized distance function model.
- Russell graph and oriented model.
- Enhanced Russell Graph Slack Based Measure.
- Modified directional distance function.
- Hölder distance function.
- Reverse directional distance function.
- Environmental model.
Economic efficiency DEA models
- Cost model.
- Revenue model.
- Profit model.
- Profitability model.
Productivity change models
- Mamlmquist index.
- Malmquist-Luenberger index.
Statistical Analysis
- Bootstrap Radial DEA Model.
- Returns to Scale (RTS) Test.
DataEnvelopmentAnalysis.jl is being developed by Javier Barbero and José Luis Zofío.