gemInputOutputTable_5_5 {GE}

General Equilibrium Models based on a 5×5 Input-Output Table (see Zhang Xin, 2017, Table 3.2.1)

Description

Some general equilibrium models based on a 5×5 input-output table (see Zhang Xin, 2017, Table 3.2.1).

Usage

gemInputOutputTable_5_5(...)

Arguments

...

arguments to be passed to the function sdm2.

References

Zhang Xin (2017, ISBN: 9787543227637) Principles of Computable General Equilibrium Modeling and Programming (Second Edition). Shanghai: Gezhi Press. (In Chinese)

Examples

names.commodity <- c("agri", "manu", "serv", "lab", "cap")
names.agent <- c("agri", "manu", "serv", "consumer", "investor")

IT <- matrix(c(
  200, 300, 150, 280, 70,
  80, 400, 250, 550, 320,
  30, 420, 240, 350, 110,
  500, 250, 330, 0, 0,
  190, 230, 180, 0, 0
), 5, 5, TRUE)

OT <- matrix(c(
  1000, 0, 0, 0, 0,
  0, 1600, 0, 0, 0,
  0, 0, 1150, 0, 0,
  0, 0, 0, 758.5714, 321.4286,
  0, 0, 0, 421.4286, 178.5714
), 5, 5, TRUE)

dimnames(IT) <- dimnames(OT) <- list(names.commodity, names.agent)

addmargins(IT)
addmargins(OT)

#### a model with non-nested production functions (demand structure trees)
dst.agri <- node_new("output",
  type = "SCES", es = 1, alpha = 1,
  beta = prop.table(c(200, 80, 30, 500, 190)),
  "agri", "manu", "serv", "lab", "cap"
)

dst.manu <- node_new("output",
  type = "SCES", es = 1, alpha = 1,
  beta = prop.table(c(300, 400, 420, 250, 230)),
  "agri", "manu", "serv", "lab", "cap"
)

dst.serv <- node_new("output",
  type = "SCES", es = 1, alpha = 1,
  beta = prop.table(c(150, 250, 240, 330, 180)),
  "agri", "manu", "serv", "lab", "cap"
)

dst.consumer <- node_new("util",
  type = "SCES", es = 0.5, alpha = 1,
  beta = prop.table(c(280, 550, 350)),
  "agri", "manu", "serv"
)

dst.investor <- node_new("util",
  type = "SCES", es = 0.5, alpha = 1,
  beta = prop.table(c(70, 320, 110)),
  "agri", "manu", "serv"
)

ge1.benchmark <- sdm2(list(dst.agri, dst.manu, dst.serv, dst.consumer, dst.investor),
  B = matrix(c(
    1, 0, 0, 0, 0,
    0, 1, 0, 0, 0,
    0, 0, 1, 0, 0,
    0, 0, 0, 0, 0,
    0, 0, 0, 0, 0
  ), 5, 5, TRUE),
  S0Exg = {
    S0Exg <- matrix(NA, 5, 5)
    S0Exg[4:5, 4] <- c(1080, 600) * (1180 / (1180 + 500))
    S0Exg[4:5, 5] <- c(1080, 600) * (500 / (1180 + 500))
    S0Exg
  },
  names.commodity = c("agri", "manu", "serv", "lab", "cap"),
  names.agent = c("agri", "manu", "serv", "consumer", "investor"),
  numeraire = c("lab")
)

addmargins(ge1.benchmark$D)
addmargins(ge1.benchmark$S)

#### a model with nested production functions (demand structure trees)
dst.agri <- node_new("output",
  type = "SCES", es = 0, alpha = 1,
  beta = prop.table(c(200 + 80 + 30, 500 + 190)),
  "cc.II", "cc.VA"
)
node_set(dst.agri, "cc.II",
  type = "SCES", es = 0, alpha = 1,
  beta = prop.table(c(200, 80, 30)),
  "agri", "manu", "serv"
)
node_set(dst.agri, "cc.VA",
  type = "SCES", es = 0.5, alpha = 1,
  beta = prop.table(c(500, 190)),
  "lab", "cap"
)

dst.manu <- node_new("output",
  type = "SCES", es = 0, alpha = 1,
  beta = prop.table(c(300 + 400 + 420, 250 + 230)),
  "cc.II", "cc.VA"
)
node_set(dst.manu, "cc.II",
  type = "SCES", es = 0, alpha = 1,
  beta = prop.table(c(300, 400, 420)),
  "agri", "manu", "serv"
)
node_set(dst.manu, "cc.VA",
  type = "SCES", es = 0.5, alpha = 1,
  beta = prop.table(c(250, 230)),
  "lab", "cap"
)

dst.serv <- node_new("output",
  type = "SCES", es = 0, alpha = 1,
  beta = prop.table(c(150 + 250 + 240, 330 + 180)),
  "cc.II", "cc.VA"
)
node_set(dst.serv, "cc.II",
  type = "SCES", es = 0, alpha = 1,
  beta = prop.table(c(150, 250, 240)),
  "agri", "manu", "serv"
)
node_set(dst.serv, "cc.VA",
  type = "SCES", es = 0.5, alpha = 1,
  beta = prop.table(c(330, 180)),
  "lab", "cap"
)

dst.consumer <- node_new("util",
  type = "SCES", es = 0.5, alpha = 1,
  beta = prop.table(c(280, 550, 350)),
  "agri", "manu", "serv"
)

dst.investor <- node_new("util",
  type = "SCES", es = 0.5, alpha = 1,
  beta = prop.table(c(70, 320, 110)),
  "agri", "manu", "serv"
)

ge2.benchmark <- sdm2(list(dst.agri, dst.manu, dst.serv, dst.consumer, dst.investor),
  B = matrix(c(
    1, 0, 0, 0, 0,
    0, 1, 0, 0, 0,
    0, 0, 1, 0, 0,
    0, 0, 0, 0, 0,
    0, 0, 0, 0, 0
  ), 5, 5, TRUE),
  S0Exg = {
    S0Exg <- matrix(NA, 5, 5)
    S0Exg[4:5, 4] <- c(1080, 600) * (1180 / (1180 + 500))
    S0Exg[4:5, 5] <- c(1080, 600) * (500 / (1180 + 500))
    S0Exg
  },
  names.commodity = c("agri", "manu", "serv", "lab", "cap"),
  names.agent = c("agri", "manu", "serv", "consumer", "investor"),
  numeraire = c("lab")
)

addmargins(ge2.benchmark$D)
addmargins(ge2.benchmark$S)