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Compute Malmquist

Source: R/compute_malmquist.R
compute_malmquist.Rd

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.

Value

A list of class pioneer_mlm

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.

References

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