deaR (version 1.4.1)

model_profit: Profit efficiency DEA model.

Description

Cost, revenue and profit efficiency DEA models.

Usage

model_profit(datadea,
             dmu_eval = NULL,
             dmu_ref = NULL,
             price_input = NULL,
             price_output = NULL,
             rts = c("crs", "vrs", "nirs", "ndrs", "grs"),
             L = 1,
             U = 1,
             restricted_optimal = TRUE,
             returnlp = FALSE,
             ...)

Arguments

datadea

A deadata object, including n DMUs, m inputs and s outputs.

dmu_eval

A numeric vector containing which DMUs have to be evaluated. If NULL (default), all DMUs are considered.

dmu_ref

A numeric vector containing which DMUs are the evaluation reference set. If NULL (default), all DMUs are considered.

price_input

Unit prices of inputs for cost or profit efficiency models. It is a value, vector of length m, or matrix m x ne (where ne is the length of dmu_eval).

price_output

Unit prices of outputs for revenue or profit efficiency models. It is a value, vector of length s, or matrix s x ne.

rts

A string, determining the type of returns to scale, equal to "crs" (constant), "vrs" (variable), "nirs" (non-increasing), "ndrs" (non-decreasing) or "grs" (generalized).

L

Lower bound for the generalized returns to scale (grs).

U

Upper bound for the generalized returns to scale (grs).

restricted_optimal

Logical. If it is TRUE, the optimal inputs are restricted to be <= inputs (for cost efficiency models) or the optimal outputs are restricted to be >= outputs (for revenue efficiency models).

returnlp

Logical. If it is TRUE, it returns the linear problems (objective function and constraints) of stage 1.

...

Ignored, for compatibility issues.

Author

Vicente Coll-Serrano (). Quantitative Methods for Measuring Culture (MC2). Applied Economics.

Vicente Bolós (). Department of Business Mathematics

Rafael Benítez (). Department of Business Mathematics

University of Valencia (Spain)

References

Coelli, T.; Prasada Rao, D.S.; Battese, G.E. (1998). An introduction to efficiency and productivity analysis. Jossey-Bass, San Francisco, pp 73–104. tools:::Rd_expr_doi("10.1002/ev.1441")

See Also

model_deaps, model_nonradial, model_sbmeff

Examples

# Example 1. Replication of results in Coelli et al. (1998, p.166).
# Cost efficiency model.
data("Coelli_1998")
# Selection of prices: input_prices is the transpose where the prices for inputs are. 
input_prices <- t(Coelli_1998[, 5:6]) 

data_example1 <- make_deadata(Coelli_1998,
                              ni = 2,
                              no = 1)
result1 <- model_profit(data_example1,
                       price_input = input_prices,
                       rts = "crs", 
                       restricted_optimal = FALSE) 
# notice that the option by default is restricted_optimal = TRUE
efficiencies(result1)

# Example 2. Revenue efficiency model.
data("Coelli_1998")
# Selection of prices for output: output_prices is the transpose where the prices for outputs are. 
output_prices <- t(Coelli_1998[, 7]) 
data_example2 <- make_deadata(Coelli_1998,
                             ni = 2,
                             no = 1)
result2 <- model_profit(data_example2,
                       price_output = output_prices,
                       rts = "crs", 
                       restricted_optimal = FALSE) 
# notice that the option by default is restricted_optimal = TRUE
efficiencies(result2)

# Example 3. Profit efficiency model.
data("Coelli_1998")
# Selection of prices for inputs and outputs: input_prices and output_prices are 
# the transpose where the prices (for inputs and outputs) are. 
input_prices <- t(Coelli_1998[, 5:6]) 
output_prices <- t(Coelli_1998[, 7]) 
data_example3 <- make_deadata(Coelli_1998,
                              ni = 2,
                              no = 1)
result3 <- model_profit(data_example3,
                        price_input = input_prices,
                        price_output = output_prices,
                        rts = "crs", 
                        restricted_optimal = FALSE) 
# notice that the option by default is restricted_optimal = TRUE
efficiencies(result3)