output.decomposition {ioanalysis} | R Documentation |
Decomposition of Output Changes
Description
Performs decomposition of output changes given two periods of data. You can decompose by origin over internal, external, or total and you can additionally decompose by changes due to final demand, technical change, or total. This follows the technique of Sonis et al (1996).
Usage
output.decomposition(io1, io2, origin = "all", cause = "all")
Arguments
io1 |
The first period |
io2 |
An |
origin |
Character. Choosing to decompose changes to the sectors due to |
cause |
Character. Choosing to decompose changes to the sectors due to changes in |
Details
A superscript of indicates changes due to final demand,
indicates changes due to the Leontief inverse, and no superscript indicates total. A subscript of
indicates changes in output originating internally of the sectors,
indicates externally, and no subscript indicates total.
is the Leontief inverse and
is aggregated final demand. Analysis is over changes from period 1 to period 2. The values are calculated as follows:
Originating: Total
Originating: Internal
Originating: External
Value
The function always outputs a named row of some variant of delta.X
. A prefix indicates the changes origin where total is blank. A suffix indicates the cause of the change where total is also blank.
int |
A prefix for internal |
ext |
A prefix for external |
f |
A suffix for final demand |
L |
A suffix for technical or Leontief |
Author(s)
John J. P. Wade, Ignacio Sarmiento-Barbieri
References
Nazara, Suahasil & Guo, Dong & Hewings, Geoffrey J.D., & Dridi, Chokri, 2003. PyIO. Input-Output Analysis with Python. REAL Discussion Paper 03-t-23. University of Illinois at Urbana-Champaign. (http://www.real.illinois.edu/d-paper/03/03-t-23.pdf)
Sonis, Michael & Geoffrey JD Hewings, & Jiemin Guo. Sources of structural change in input-output systems: a field of influence approach. Economic Systems Research 8, no. 1 (1996): 15-32.
See Also
Examples
data(toy.IO)
data(toy.IO2)
class(toy.IO)
class(toy.IO) == class(toy.IO2)
OD1 <- output.decomposition(toy.IO, toy.IO2)
OD1$Hogwarts
OD2 <- output.decomposition(toy.IO, toy.IO2, origin = "external",
cause = c("finaldemand","leontief"))
OD2