Description Usage Arguments Details Value Warning Note Author(s) References See Also Examples
Using Data Envelopment Analysis (DEA), this function measures productivity with Malmquist index.
1 2 3 4 5 6 |
data |
A dataframe containing the required information for measuring productivity. |
id.var |
Firms' ID variable. Can be an integer or a text string. |
time.var |
Time period variable. Can be an integer or a text string. |
x.vars |
Input quantity variables. Can be a vector of text strings or integers. |
y.vars |
Output quantity variables. Can be a vector of text strings or integers. |
tech.reg |
Logical. If |
rts |
Character string specifying the returns to scale assumption.
The default value is |
orientation |
Character string specifying the orientation. The default value is |
parallel |
Logical. Allows parallel computation. If |
cores |
Integer. Used only if |
scaled |
Logical. If |
x |
An object of class |
digits |
The minimum number of significant digits to be printed in values.
Default = |
... |
Currently not used. |
Distance functions required for computing the Malmquist index are radial measures which verify the translation
invariance property. Hence, unless very large or very small values are present, the Malmquist index is insensitive
to the rescaling option (scaled
).
malm()
returns a list of class 'Malmquist'
for which a summary of productivity measures
in levels and changes is printed.
This list contains the following items:
Levels |
It contains the Shephard distance function estimates, useful to compute and decompose
the Malmquist productivity index. These distance functions use input and output quantities
for period In addition to the The distance function names are displayed with three digits:
(i) the first digit represents the period of the reference technology,
(ii) the second digit represents the period of the inputs, and
(iii) the third digit represents the period of the outputs.
For instance | ||||||||||||||||||||||||||||
Changes |
Malmquist productivity index and its components are provided, depending on the orientation.
|
Note that:
obtech
(Output-biased technological change), ibtech
(Input-biased technological change),
and matech
(Magnitude component) are components of technological change (tech
).
pure.out.effch
(Pure output efficiency change) and out.scalech
(Output scale efficiency change)
are components of efficiency change (effch
).
pure.inp.effch
(Pure input efficiency change), and inp.scalech
(Input scale efficiency change)
are components of efficiency change (effch
).
From an object of class 'Malmquist'
obtained from malm()
, the
Levels
function extracts Shephard distance function estimates; and
Changes
function extracts Malmquist productivity index and components.
The malm()
function will not work with unbalanced panel data.
The Malmquist productivity index and components are computed such that both orientation
's
results provide the same information: growth when index greater than one and decline when index lower
than one. Moreover under rts = "crs"
, both orientation
options (i.e. "out"
and
"in"
) yield the same results.
K Herv<c3><a9> Dakpo, Yann Desjeux, Laure Latruffe
F<c3><a4>re R., and Grosskopf S. (1996), Intertemporal Production Frontiers: With Dynamic DEA. Springer Eds.
See Levels
to retrieve a data frame with Shephard distance function estimates.
See Changes
to retrieve a data frame with Malmquist productivity index and components.
1 2 3 4 5 6 7 8 9 | ## Malmquist productivity index compares each observation in period 1 to the same
## observation in period 0
## Not run:
Malmquist <- malm(data = usagri, id.var = "States", time.var = "Years",
x.vars = c("q.capital", "q.land","q.labor","q.materials"),
y.vars = c("q.livestock", "q.crop", "q.other"), rts = "nirs")
Malmquist
## End(Not run)
|
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