compute_malmquist: Compute Malmquist

In Riksrevisjonen/pioneeR: Productivity and Efficiency Analysis using DEA

Compute Malmquist

Description

Calculate the Malmquist productivity index and its components using Data Envelopment Analysis.

Usage

compute_malmquist(data, input, output, id, time, orientation = c("in", "out"))

Arguments

data	Dataset to analyse.
input	A character vector with input variables.
output	A character vector with output variables.
id	A string with the DMU id or name variable.
time	A string with the time period variable.
orientation	Model orientation.

Details

Results are returned a la Farrell. This implies that for output-oriented models values above one signify improvements in productivity, while values less than one imply deterioration in productivity. For input-oriented models the interpretation is reversed; values less than one denote improvements and values above one denote deterioration.

Note that compute_malmquist() only works for balanced panel datasets.

Value

A list of class pioneer_mlm

References

Färe, R., Grosskopf, S. (1996). Intertemporal production frontiers: With dynamic DEA. Springer.

Examples

# Load example data
chnEconomy <- deaR::EconomyLong
# Estimate Malmquist
mod <- compute_malmquist(
  data = chnEconomy,
  id = 'DMUs',
  time = 'Period',
  input = c('Labor', 'Capital'),
  output = 'GIOV',
  orientation = 'in')
# Print results
print(mod)
# Get summary
summary(mod)
# Convert to data frame
df <- as.data.frame(mod)

Riksrevisjonen/pioneeR documentation built on Oct. 26, 2024, 6:05 p.m.