nlprofitDEA {hyperbolicDEA}

Non-linear profit DEA model

Description

This function implements a non-linear profit DEA model that optimizes the ratio of cost over revenue given the prices for a DMU. It returns the estimated lambdas, optimal values for inputs and outputs, and a profit efficiency score. The profit efficiency score is calculated as the square root of the ratio of the observed revenue-cost ratio to the optimal revenue-cost ratio.

Usage

nlprofitDEA(X, Y, pX, pY, RTS = "crs")

Arguments

X

Vector, matrix or dataframe with DMUs as rows and inputs as columns.

Y

Vector, matrix or dataframe with DMUs as rows and outputs as columns.

pX

Vector, matrix or dataframe with prices for each DMU and input. It must have the same dimensions as X.

pY

Vector, matrix or dataframe with prices for each DMU and output. It must have the same dimensions as Y.

RTS

Character string indicating the returns-to-scale, e.g. "crs", "vrs".

Value

A list object containing the following:

lambdas

Estimated values for the composition of the respective Benchmarks. The lambdas are stored in a matrix with dimensions nrow(X) x nrow(X), where the row is the DMU under observation and the columns are the peers used for the Benchmark.

opt_value

Optimal inputs and outputs.

profit_eff

New profit efficiency score that accounts for simultaneous adjustments in inputs and outputs.

See Also

'deaprofitability()' function in the Julia package BenchmarkingEconomicEfficiency.jl.

Examples

X <- matrix(c(1,2,3,3,2,1,2,2), ncol = 2)
Y <- matrix(c(1,1,1,1), ncol = 1)

pX <- matrix(c(2,1,2,1,2,1,1,2), ncol =  2, byrow = TRUE)
pY <- matrix(c(1,1,1,1), ncol = 1)

max_prof_nolin <- nlprofitDEA(X,Y,pX,pY)