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Benchmarking (version 0.29)

Benchmark and Frontier Analysis Using DEA and SFA

Description

Methods for frontier analysis, Data Envelopment Analysis (DEA), under different technology assumptions (fdh, vrs, drs, crs, irs, add/frh, and fdh+), and using different efficiency measures (input based, output based, hyperbolic graph, additive, super, and directional efficiency). Peers and slacks are available, partial price information can be included, and optimal cost, revenue and profit can be calculated. Evaluation of mergers is also supported. Methods for graphing the technology sets are also included. There is also support for comparative methods based on Stochastic Frontier Analyses (SFA) and for convex nonparametric least squares for convex functions (StoNED). In general, the methods can be used to solve not only standard models, but also many other model variants. It complements the book, Bogetoft and Otto, Benchmarking with DEA, SFA, and R, Springer-Verlag, 2011, but can of course also be used as a stand-alone package.

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Version

Install

install.packages('Benchmarking')

Monthly Downloads

3,234

Version

0.29

License

GPL (>= 2)

Maintainer

Lars Otto

Last Published

August 7th, 2020

Functions in Benchmarking (0.29)

dea.dual

Dual DEA models and assurance regions
dea.add

Additive DEA model
critValue

Critical values from bootstrapped DEA models
charnes1981

Data: Charnes et al. (1981): Program follow through
dea.boot

Bootstrap DEA models
Benchmarking-package

Data Envelopment Analyses (DEA) and Stochastic Frontier Analyses (SFA) -- Model Estimations and Efficiency Measuring
cost.opt

DEA optimal cost, revenue, and profit
dea

DEA efficiency
dea.merge

Estimate potential merger gains and their decompositions
dea.direct

Directional efficiency
make.merge

Make an aggregation matrix to perform mergers
malmq

Malmquist index
excess

Excess input compared over frontier input
lambda

Lambdas or the weight of the peers
eff.dens

Estimate and plot density of efficiencies
eladder

Efficiency ladder for a single firm
malmquist

Malmquist index for fimrs in a panel
milkProd

Data: Milk producers
mea

MEA multi-directional efficiency analysis
typeIerror

Probability of type I error for test in a bootstrap DEA model
norWood2004

Data: Forestry in Norway
outlier.ap

Detection of outliers in benchmark models
pigdata

Data: Multi-output pig producers
dea.plot

Plot of DEA technologies
projekt

Data: Milk producers
slack

Calculate slack in an efficiency analysis
eff, efficiencies

Calculate efficiencies for Farrell and sfa object
sfa

Stochastic frontier estimation
sdea

Super efficiency
peers

Find peer firms and units
stoned

Convex nonparametric least squares