*! version 0.3 29 Oct 2019
help sbmeff

Title

sbmeff -- Slacks-based Measure of Efficiency in Stata

Syntax

sbmeff inputvars = desirable_outputvars [if] [in]
, dmu(varname) [options]

sbmeff inputvars = desirable_outputvars : undesirable_outputvars [if] [in]
, dmu(varname) [options]

Main
dmu:(varname) specifies names of DMUs. It is required.

time:(varname) specifies time period for contemporaneous production technology. If time(varname) is not specified, global production technology is assumed.

sequential specifies sequential production technology.

vrs specifies production technology with variable returns to scale. By default, production technology with constant returns to scale is assumed.

saving(filename[,replace]) specifies that the results be saved in filename.dta.

maxiter(#) specifies the maximum number of iterations, which must be an integer greater than 0. The default value of maxiter is 16000.

tol(real) specifies the convergence-criterion tolerance, which must be greater than 0. The default value of tol is 1e-8.

Description

sbmeff selects the input and output variables from the user designated data file or in the opened data set and solves Slacks-based Measure of Efficiency models by options specified.

The sbmeff program uses the buit-in mata function linearprogram(). Stata 16 or later is required.

The sbmeff program requires initial data set that contains the input and output variables for observed units.

Variable names must be identified by inputvars for input variable, by desirable_outputvars for desirable output variable, and by undesirable_outputvars for undesirable output variable
to allow that sbmeff program can identify and handle the multiple input-output data set.

Examples

{"use ...\example_sbm.dta"}

. sbmeff labor capital energy=gdp, dmu(id) time(t) vrs

. sbmeff labor capital energy=gdp, dmu(id) sav(sbm_result)

. sbmeff labor capital energy=gdp:co2, dmu(id) time(t) vrs

. sbmeff labor capital energy=gdp:co2, dmu(id) sav(sbm_result,replace)

Saved Results

Macro:

r(file) the stored results of sbmeff that have observation rows of DMUs and variable columns with input data, output data, efficiency scores, and slacks.

References

Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130(3):498-509.

Tone, K. (2004). Dealing with Undesirable Outputs in DEA: A Slacks-Based Measure (SBM) Approach. North American Productivity Workshop 2004, Toronto, 23-25 June 2004, 44-45.

Author

Kerry Du

Xiamen University

Xiamen, China

E-mail: kerrydu@xmu.edu.cn