Benchmarking (version 0.10)

dea.merge: Efficiency results after mergers and their decompositions

Description

Calculate and decompose efficiency from mergers of similar firms, horisontal integration.

Usage

dea.merge(X, Y, M, RTS = "vrs", ORIENTATION = "in",
             XREF = NULL, YREF = NULL, FRONT.IDX = NULL, TRANSPOSE = FALSE,
             LP = FALSE, CONTROL = NULL, LPK = NULL, ...)

Arguments

X

K times m matrix as in dea

Y

K times n matrix as in dea

M

Kg times K matrix where each row defines a merger by the firms ((colloms) included; matrix as returned from method make.marge

RTS

as in dea

ORIENTATION

as in dea

XREF

as in dea

YREF

as in dea

FRONT.IDX

as in dea

TRANSPOSE

as in dea

LP

as in dea

CONTROL

as in dea

LPK

as in dea

...

as in dea

Value

• Eff
  overall efficiencies of mergers, Kg vector
• Estar
  adjusted overall efficiencies of mergers after the removal of individual learning, Kg vector
• learning
  = individual learning effects me (row) vectors, K* (row) vectors
• harmony
  harmony effects, Kg vector
• size
  size effects, K* vector0

References

PB & LO, chapter XX

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.