| gemInputOutputTable_7_4 {GE} | R Documentation |
A General Equilibrium Model based on a 7×4 (Standard) Input-Output Table
Description
This is a general equilibrium model based on a 7×4 standard input-output table. There is no negative number in this standard input-output table, and both the input and output parts are 7×4 matrices. The standard input-output table consists of input and output parts with the same dimensions.
Usage
gemInputOutputTable_7_4(
IT,
OT,
es.agri = 0,
es.manu = 0,
es.serv = 0,
es.hh = 0,
es.VA.agri = 0.25,
es.VA.manu = 0.5,
es.VA.serv = 0.8,
...
)
Arguments
IT |
the input part of the input-output table in the base period (unit: trillion yuan). |
OT |
the output part of the input-output table in the base period (unit: trillion yuan). |
es.agri, es.manu, es.serv |
the elasticity of substitution between the intermediate input and the value-added input of the agriculture sector, manufacturing sector and service sector. |
es.hh |
the elasticity of substitution among products consumed by the household sector. |
es.VA.agri, es.VA.manu, es.VA.serv |
the elasticity of substitution between labor input and capital input of the agriculture sector, manufacturing sector and service sector. |
... |
arguments to be transferred to the function sdm of the package CGE. |
Details
Given a 7×4 input-output table, this model calculates the corresponding general equilibrium. This input-output table contains 3 production sectors and 1 household. The household consumes products and supplies labor, capital, stock and tax receipt. Generally speaking, the value of the elasticity of substitution in this model should be between 0 and 1.
Value
A general equilibrium, which is a list with the following elements:
p - the price vector with labor as numeraire.
D - the demand matrix, also called the input table. Wherein the benchmark prices are used.
DV - the demand value matrix, also called the value input table. Wherein the current price is used.
SV - the supply value matrix, also called the value output table. Wherein the current price is used.
value.added - the value-added of the three production sectors.
dstl - the demand structure tree list of sectors.
... - some elements returned by the sdm2 function.
Examples
IT2017 <- matrix(c(
1.47, 6.47, 0.57, 2.51,
2.18, 76.32, 12.83, 44.20,
0.82, 19.47, 23.33, 35.61,
6.53, 13.92, 21.88, 0,
0.23, 4.05, 6.76, 0,
0, 6.43, 3.40, 0,
0.13, 8.87, 10.46, 0
), 7, 4, TRUE)
OT2017 <- matrix(c(
11.02, 0, 0, 0,
0, 135.53, 0, 0,
0, 0, 79.23, 0,
0, 0, 0, 42.33,
0, 0, 0, 11.04,
0.34, 0, 0, 9.49,
0, 0, 0, 19.46
), 7, 4, TRUE)
rownames(IT2017) <- rownames(OT2017) <-
c("agri", "manu", "serv", "lab", "cap", "tax", "dividend")
colnames(IT2017) <- colnames(OT2017) <-
c("sector.agri", "sector.manu", "sector.serv", "sector.hh")
ge <- gemInputOutputTable_7_4(
IT = IT2017,
OT = OT2017
)
#### labor supply reduction
OTLSR <- OT2017
OTLSR["lab", "sector.hh"] <- OTLSR["lab", "sector.hh"] * 0.9
geLSR <- gemInputOutputTable_7_4(
IT = IT2017,
OT = OTLSR
)
geLSR$z / ge$z
geLSR$p / ge$p
#### capital accumulation
OTCA <- OT2017
OTCA["cap", "sector.hh"] <- OTCA["cap", "sector.hh"] * 1.1
geCA <- gemInputOutputTable_7_4(
IT = IT2017,
OT = OTCA
)
geCA$z / ge$z
geCA$p / ge$p
#### technology progress
IT.TP <- IT2017
IT.TP ["lab", "sector.manu"] <-
IT.TP ["lab", "sector.manu"] * 0.9
geTP <- gemInputOutputTable_7_4(
IT = IT.TP,
OT = OT2017
)
geTP$z / ge$z
geTP$p / ge$p
##
IT.TP2 <- IT.TP
IT.TP2 ["cap", "sector.manu"] <-
IT.TP2["cap", "sector.manu"] * 1.02
geTP2 <- gemInputOutputTable_7_4(
IT = IT.TP2,
OT = OT2017
)
geTP2$z / ge$z
geTP2$p / ge$p
##
IT.TP3 <- IT2017
IT.TP3 ["lab", "sector.manu"] <-
IT.TP3 ["lab", "sector.manu"] * 0.9
IT.TP3 ["lab", "sector.agri"] <-
IT.TP3 ["lab", "sector.agri"] * 0.8
geTP3 <- gemInputOutputTable_7_4(
IT = IT.TP3,
OT = OT2017
)
geTP3$value.added / ge$value.added
prop.table(geTP3$value.added) - prop.table(ge$value.added)
#### demand structure change
IT.DSC <- IT2017
IT.DSC["serv", "sector.hh"] <- IT.DSC ["serv", "sector.hh"] * 1.2
geDSC <- gemInputOutputTable_7_4(
IT = IT.DSC,
OT = OT2017
)
geDSC$z[1:3] / ge$z[1:3]
geDSC$p / ge$p
#### tax change
OT.TC <- OT2017
OT.TC["tax", "sector.agri"] <- OT.TC["tax", "sector.agri"] * 2
geTC <- gemInputOutputTable_7_4(
IT = IT2017,
OT = OT.TC
)
geTC$z / ge$z
geTC$p / ge$p
##
IT.TC2 <- IT2017
IT.TC2["tax", "sector.manu"] <- IT.TC2["tax", "sector.manu"] * 0.8
geTC2 <- gemInputOutputTable_7_4(
IT = IT.TC2,
OT = OT2017
)
geTC2$z / ge$z
geTC2$p / ge$p