model_profit | R Documentation |
Cost, revenue and profit efficiency DEA models.
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,
...)
datadea |
A |
dmu_eval |
A numeric vector containing which DMUs have to be evaluated.
If |
dmu_ref |
A numeric vector containing which DMUs are the evaluation reference set.
If |
price_input |
Unit prices of inputs for cost or profit efficiency models.
It is a value, vector of length |
price_output |
Unit prices of outputs for revenue or profit efficiency models.
It is a value, vector of length |
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 |
returnlp |
Logical. If it is |
... |
Ignored, for compatibility issues. |
Vicente Coll-Serrano (vicente.coll@uv.es). Quantitative Methods for Measuring Culture (MC2). Applied Economics.
Vicente Bolós (vicente.bolos@uv.es). Department of Business Mathematics
Rafael Benítez (rafael.suarez@uv.es). Department of Business Mathematics
University of Valencia (Spain)
Coelli, T.; Prasada Rao, D.S.; Battese, G.E. (1998). An introduction to efficiency and productivity analysis. Jossey-Bass, San Francisco, pp 73–104. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/ev.1441")}
model_deaps
, model_nonradial
,
model_sbmeff
# 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)
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