# \donttest{
np <- 15 # the number of economic periods, firms.
gr <- 0 # the growth rate of the labor supply
eis <- 0.5 # the elasticity of intertemporal substitution
Gamma.beta <- 0.9 # the subjective discount factor
y1 <- 100 # the initial product supply
n <- 2 * np # the number of commodity kinds
m <- np + 1 # the number of agent kinds
names.commodity <- c(paste0("prod", 1:np), paste0("lab", 1:np))
names.agent <- c(paste0("firm", 1:np), "consumer")
# the exogenous supply matrix.
S0Exg <- matrix(NA, n, m, dimnames = list(names.commodity, names.agent))
# the supply of labor.
S0Exg[paste0("lab", 1:np), "consumer"] <- 100 * (1 + gr)^(0:(np - 1))
S0Exg["prod1", "firm1"] <- y1
# the output coefficient matrix.
B <- matrix(0, n, m, dimnames = list(names.commodity, names.agent))
for (k in 1:(np - 1)) {
B[paste0("prod", k + 1), paste0("firm", k)] <- 1
}
dstl.firm <- list()
for (k in 1:np) {
dstl.firm[[k]] <- node_new(
"prod",
type = "CD", alpha = 2, beta = c(0.5, 0.5),
paste0("lab", k), paste0("prod", k)
)
}
dst.consumer <- node_new(
"util",
type = "CES", es = eis,
alpha = 1, beta = prop.table(Gamma.beta^(1:np)),
paste0("prod", 1:np)
)
policy.PublicFirm <- function(state) {
for (k in 1:(np - 1)) {
state$S[k + 1, k + 1] <- state$S[k + 1, k]
state$S[k + 1, k] <- 0
}
state
}
ge <- sdm2(
A = c(dstl.firm, dst.consumer),
B = B,
S0Exg = S0Exg,
names.commodity = names.commodity,
names.agent = names.agent,
numeraire = "prod1",
policy=policy.PublicFirm
)
ge$p
ge$z[1:15]
#### the sequential form of the above model.
dst.firm <- node_new(
"prod",
type = "CD", alpha = 2, beta = c(0.5, 0.5),
"prod", "lab"
)
dst.consumer <- node_new(
"util",
type = "Leontief", a = 1,
"prod"
)
dstl <- list(dst.firm, dst.consumer)
ge.seq <- sdm2(
A = dstl,
B = matrix(c(
1, 0,
0, 0
), 2, 2, TRUE),
S0Exg = matrix(c(
NA, NA,
NA, 100
), 2, 2, TRUE),
names.commodity = c("prod", "lab"),
names.agent = c("firm", "consumer"),
numeraire = "lab",
z0 = c(100, 1),
ts = TRUE,
policy = policyMarketClearingPrice,
numberOfPeriods = 20,
maxIteration = 1
)
growth_rate(ge$p[paste0("prod", 1:np)]) + 1
growth_rate(ge$p[paste0("lab", 1:np)]) + 1
1 / (1 + sserr(eis, Gamma.beta, gr))
ge.seq$ts.z[, 1]
# }
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