| sdm_dstl {GE} | R Documentation |
Structural Dynamic Model (alias Structural Growth Model) with a Demand Structure Tree List
Description
This is a wrapper of the function CGE::sdm.
The parameter A of CGE::sdm is replaced with a demand structure tree list.
This function can be replaced by the more comprehensive function sdm2,
so it is not recommended.
Usage
sdm_dstl(dstl, names.commodity, names.agent, ...)
Arguments
dstl |
a demand structure tree list. |
names.commodity |
names of commodities. |
names.agent |
names of agents. |
... |
arguments to be passed to the function CGE::sdm. |
Value
A general equilibrium, which is a list with the following elements:
D - the demand matrix.
DV - the demand value matrix.
SV - the supply value matrix.
... - some elements returned by the CGE::sdm function
References
LI Wu (2019, ISBN: 9787521804225) General Equilibrium and Structural Dynamics: Perspectives of New Structural Economics. Beijing: Economic Science Press. (In Chinese)
LI Wu (2010) A Structural Growth Model and its Applications to Sraffa's System. http://www.iioa.org/conferences/18th/papers/files/104_20100729011_AStructuralGrowthModelanditsApplicationstoSraffasSstem.pdf
Manuel Alejandro Cardenete, Ana-Isabel Guerra, Ferran Sancho (2012, ISBN: 9783642247453) Applied General Equilibrium: An Introduction. Springer-Verlag Berlin Heidelberg.
Torres, Jose L. (2016, ISBN: 9781622730452) Introduction to Dynamic Macroeconomic General Equilibrium Models (Second Edition). Vernon Press.
See Also
Examples
#### a pure exchange economy with two agents and two commodities
dst.CHN <- node_new("util.CHN",
type = "SCES", alpha = 1, beta = c(0.8, 0.2), es = 2,
"lab.CHN", "lab.ROW"
)
node_plot(dst.CHN)
dst.ROW <- node_new("util.ROW",
type = "SCES", alpha = 1, beta = c(0.05, 0.95), es = 2,
"lab.CHN", "lab.ROW"
)
dstl <- list(dst.CHN, dst.ROW)
ge <- sdm_dstl(dstl,
names.commodity = c("lab.CHN", "lab.ROW"),
names.agent = c("CHN", "ROW"),
B = matrix(0, 2, 2, TRUE),
S0Exg = matrix(c(
100, 0,
0, 600
), 2, 2, TRUE)
)
## supply change
geSC <- sdm_dstl(dstl,
names.commodity = c("lab.CHN", "lab.ROW"),
names.agent = c("CHN", "ROW"),
B = matrix(0, 2, 2, TRUE),
S0Exg = matrix(c(
200, 0,
0, 600
), 2, 2, TRUE)
)
geSC$p / ge$p
## preference change
dst.CHN$beta <- c(0.9, 0.1)
gePC <- sdm_dstl(dstl,
names.commodity = c("lab.CHN", "lab.ROW"),
names.agent = c("CHN", "ROW"),
B = matrix(0, 2, 2, TRUE),
S0Exg = matrix(c(
100, 0,
0, 600
), 2, 2, TRUE)
)
gePC$p / ge$p
#### a pure exchange economy with two agents and four basic commodities
prod.CHN <- node_new("prod.CHN",
type = "SCES", alpha = 1, beta = c(0.5, 0.5), es = 0.75,
"lab.CHN", "cap.CHN"
)
node_plot(prod.CHN)
prod.ROW <- node_new("prod.ROW",
type = "SCES", alpha = 2, beta = c(0.4, 0.6), es = 0.75,
"lab.ROW", "cap.ROW"
)
dst.CHN <- node_new("CHN",
type = "SCES", alpha = 1, beta = c(0.8, 0.2), es = 2,
prod.CHN, prod.ROW
)
node_plot(dst.CHN)
node_print(dst.CHN)
p <- c("lab.CHN" = 1, "cap.CHN" = 1, "lab.ROW" = 1, "cap.ROW" = 1)
demand_coefficient(dst.CHN, p)
dst.ROW <- node_new("ROW",
type = "SCES", alpha = 1, beta = c(0.05, 0.95), es = 2,
prod.CHN, prod.ROW
)
node_plot(dst.ROW)
node_print(dst.ROW)
dstl <- list(dst.CHN, dst.ROW)
ge <- sdm_dstl(dstl,
names.commodity = c("lab.CHN", "cap.CHN", "lab.ROW", "cap.ROW"),
names.agent = c("CHN", "ROW"),
B = matrix(0, 4, 2, TRUE),
S0Exg = matrix(c(
100, 0,
100, 0,
0, 600,
0, 800
), 4, 2, TRUE)
)
## Add currencies to the example above.
prod_money.CHN <- node_new("prod_money.CHN",
type = "FIN", rate = c(1, 0.1), # 0.1 is the interest rate.
prod.CHN, "money.CHN"
)
prod_money.ROW <- node_new("prod_money.ROW",
type = "FIN", rate = c(1, 0.1),
prod.ROW, "money.ROW"
)
dst.CHN <- node_new("util.CHN",
type = "SCES", alpha = 1, beta = c(0.8, 0.2), es = 2,
prod_money.CHN, prod_money.ROW
)
dst.ROW <- node_new("util.ROW",
type = "SCES", alpha = 1, beta = c(0.05, 0.95), es = 2,
prod_money.CHN, prod_money.ROW
)
dstl <- list(dst.CHN, dst.ROW)
ge <- sdm_dstl(dstl,
names.commodity = c(
"lab.CHN", "cap.CHN", "money.CHN",
"lab.ROW", "cap.ROW", "money.ROW"
),
names.agent = c("CHN", "ROW"),
B = matrix(0, 6, 2, TRUE),
S0Exg = matrix(c(
100, 0,
100, 0,
100, 0,
0, 600,
0, 800,
0, 100
), 6, 2, TRUE)
)
ge$p["money.ROW"] / ge$p["money.CHN"] # the exchange rate
#### Example 7.6 in Li (2019), which illustrates foreign exchange rates.
interest.rate.CHN <- 0.1
interest.rate.ROW <- 0.1
firm.CHN <- node_new("output.CHN",
type = "FIN", rate = c(1, interest.rate.CHN),
"cc1.CHN", "money.CHN"
)
node_set(firm.CHN, "cc1.CHN",
type = "CD", alpha = 1, beta = c(0.5, 0.5),
"lab.CHN", "iron"
)
household.CHN <- node_new("util",
type = "FIN", rate = c(1, interest.rate.CHN),
"wheat", "money.CHN"
)
moneylender.CHN <- Clone(household.CHN)
firm.ROW <- node_new("output.ROW",
type = "FIN", rate = c(1, interest.rate.ROW),
"cc1.ROW", "money.ROW"
)
node_set(firm.ROW, "cc1.ROW",
type = "CD", alpha = 1, beta = c(0.5, 0.5),
"iron", "lab.ROW"
)
household.ROW <- node_new("util",
type = "FIN", rate = c(1, interest.rate.ROW),
"wheat", "money.ROW"
)
moneylender.ROW <- Clone(household.ROW)
dstl <- list(
firm.CHN, household.CHN, moneylender.CHN,
firm.ROW, household.ROW, moneylender.ROW
)
ge <- sdm_dstl(dstl,
names.commodity = c(
"wheat", "lab.CHN", "money.CHN",
"iron", "lab.ROW", "money.ROW"
),
names.agent = c(
"firm.CHN", "household.CHN", "moneylender.CHN",
"firm.ROW", "household.ROW", "moneylender.ROW"
),
B = {
tmp <- matrix(0, 6, 6)
tmp[1, 1] <- 1
tmp[4, 4] <- 1
tmp
},
S0Exg = {
tmp <- matrix(NA, 6, 6)
tmp[2, 2] <- 100
tmp[3, 3] <- 600
tmp[5, 5] <- 100
tmp[6, 6] <- 100
tmp
}
)
ge$p.money <- ge$p
ge$p.money["money.CHN"] <- ge$p["money.CHN"] / interest.rate.CHN
ge$p.money["money.ROW"] <- ge$p["money.ROW"] / interest.rate.ROW
ge$p.money <- ge$p.money / ge$p.money["money.CHN"]
ge$p.money["money.ROW"] / ge$p.money["money.CHN"] # the exchange rate
#### the example (see Table 2.1 and 2.2) of the canonical dynamic
#### macroeconomic general equilibrium model in Torres (2016).
discount.factor <- 0.97
return.rate <- 1 / discount.factor - 1
depreciation.rate <- 0.06
production.firm <- node_new("output",
type = "CD", alpha = 1, beta = c(0.65, 0.35),
"labor", "capital.goods"
)
household <- node_new("util",
type = "CD", alpha = 1, beta = c(0.4, 0.6),
"product", "labor"
)
leasing.firm <- node_new("output",
type = "FIN", rate = c(1, return.rate),
"product", "dividend"
)
dstl <- list(
production.firm, household, leasing.firm
)
ge <- sdm_dstl(dstl,
names.commodity = c("product", "labor", "capital.goods", "dividend"),
names.agent = c("production.firm", "household", "leasing.firm"),
B = matrix(c(
1, 0, 1 - depreciation.rate,
0, 1, 0,
0, 0, 1,
0, 1, 0
), 4, 3, TRUE),
S0Exg = {
tmp <- matrix(NA, 4, 3)
tmp[2, 2] <- 1
tmp[4, 2] <- 1
tmp
},
priceAdjustmentVelocity = 0.03,
maxIteration = 1,
numberOfPeriods = 15000,
ts = TRUE
)
ge$D # the demand matrix
ge$p / ge$p[1]
plot(ge$ts.z[, 1], type = "l")
#### an example of applied general equilibrium (see section 3.4, Cardenete et al., 2012).
dst.consumer1 <- node_new("util",
type = "CD", alpha = 1, beta = c(0.3, 0.7),
"prod1", "prod2"
)
dst.consumer2 <- node_new("util",
type = "CD", alpha = 1, beta = c(0.6, 0.4),
"prod1", "prod2"
)
dst.firm1 <- node_new("output",
type = "Leontief", a = c(0.5, 0.2, 0.3),
"VA", "prod1", "prod2"
)
node_set(dst.firm1, "VA",
type = "CD",
alpha = 0.8^-0.8 * 0.2^-0.2, beta = c(0.8, 0.2),
"lab", "cap"
)
dst.firm2 <- Clone(dst.firm1)
dst.firm2$a <- c(0.25, 0.5, 0.25)
node_set(dst.firm2, "VA",
alpha = 0.4^-0.4 * 0.6^-0.6, beta = c(0.4, 0.6)
)
node_print(dst.firm2)
dstl <- list(dst.firm1, dst.firm2, dst.consumer1, dst.consumer2)
ge <- sdm_dstl(dstl,
names.commodity = c("prod1", "prod2", "lab", "cap"),
names.agent = c("firm1", "firm2", "consumer1", "consumer2"),
B = {
tmp <- matrix(0, 4, 4)
tmp[1, 1] <- 1
tmp[2, 2] <- 1
tmp
},
S0Exg = {
tmp <- matrix(NA, 4, 4)
tmp[3, 3] <- 30
tmp[4, 3] <- 20
tmp[3, 4] <- 20
tmp[4, 4] <- 5
tmp
}
)
[Package GE version 0.4.5 Index]