dea.merge {Benchmarking} | R Documentation |
Calculate and decompose potential gains from mergers of similar firms (horizontal integration).
dea.merge(X, Y, M, RTS = "vrs", ORIENTATION = "in", XREF = NULL, YREF = NULL, FRONT.IDX = NULL, TRANSPOSE=FALSE)
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Most of the arguments correspond to the arguments in
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X |
K times m matrix as in |
Y |
K times n matrix as in |
M |
Kg times K matrix where each row defines a merger by the
firms (collums) included; matrix as returned from method
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RTS |
as in |
ORIENTATION |
as in |
XREF |
as in |
YREF |
as in |
FRONT.IDX |
as in |
TRANSPOSE |
as in |
The K firms are merged into Kg new, merged firms.
The decomposition is summarized on page 275 and in table 9.1 page 276 in Bogetoft and Otto (2011) and is based on Bogetoft and Wang (2005)
Eff |
Overall efficiencies of mergers, Kg vector |
Estar |
Adjusted overall efficiencies of mergers after the removal of individual learning, Kg vector |
learning |
Learning effects, Kg vector |
harmony |
Harmony (scope) effects, Kg vector |
size |
Size (scale) effects, Kg vector |
Peter Bogetoft and Lars Otto larsot23@gmail.com
Bogetoft and Otto; Benchmarking with DEA, SFA, and R; chapter 9; Springer 2011.
Bogetoft and Wang; “Estimating the Potential Gains from Mergers”; Journal of Productivity Ana-lysis, 23, pp. 145-171, 2005.
dea
and make.merge
x <- matrix(c(100,200,300,500),ncol=1,dimnames=list(LETTERS[1:4],"x")) y <- matrix(c(75,100,300,400),ncol=1,dimnames=list(LETTERS[1:4], "y")) dea.plot.frontier(x,y,RTS="vrs",txt=LETTERS[1:length(x)], xlim=c(0,1000),ylim=c(0,1000) ) dea.plot.frontier(x,y,RTS="drs", add=TRUE, lty="dashed", lwd=2) dea.plot.frontier(x,y,RTS="crs", add=TRUE, lty="dotted") dea(x,y,RTS="crs") M <- make.merge(list(c(1,2), c(3,4)), X=x) xmer <- M %*% x ymer <- M %*% y points(xmer,ymer,pch=8) text(xmer,ymer,labels=c("A+B","C+D"),pos=4) dea.merge(x,y,M, RTS="vrs") dea.merge(x,y,M, RTS="crs")