GE (version 0.2.9)

gemPersistentTechnologicalProgress: Some Examples of Market Clearing Paths with Persistent Technological Progress

Description

Some examples of market clearing paths with persistent technological progress. From the fifth period, technological progress occurs.

Usage

gemPersistentTechnologicalProgress(...)

Arguments

...

arguments to be passed to the function sdm2.

Examples

# NOT RUN {
#### a 2-by-2 example with labor-saving technological progress
tpr <- 0.03 # technological progress rate

dst.firm <- node_new(
  "prod",
  type = "SCES",
  es = 0.5, alpha = 1,
  beta = c(0.5, 0.5),
  "prod", "cc1"
)
node_set(dst.firm, "cc1",
         type = "Leontief", a = 1,
         "lab"
)

dst.consumer <- node_new(
  "util",
  type = "Leontief", a = 1,
  "prod"
)

dstl <- list(dst.firm, dst.consumer)

ge <- 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 = "prod",
  ts = TRUE,
  policy = list(
    function(time, A) {
      if (time >= 5) {
        node_set(A[[1]], "cc1",
                 a = (1 + tpr)^-(time - 4)
        )
      }
    },
    policyMarketClearingPrice
  ),
  numberOfPeriods = 40,
  maxIteration = 1,
  z0 = c(200, 100),
  p0 = c(1, 1)
)

matplot(growth_rate(ge$ts.z), type = "o", pch = 20)
matplot(growth_rate(ge$ts.p), type = "o", pch = 20)

#### a 3-by-3 example with labor-saving technological progress
tpr <- 0.03 # technological progress rate

dst.manu <- node_new("manu",
                     type = "SCES", es = 0.5, alpha = 1,
                     beta = c(0.6, 0.4),
                     "manu", "cc1"
)
node_set(dst.manu, "cc1",
         type = "Leontief", a = 1,
         "lab"
)

dst.serv <- node_new("serv",
                     type = "SCES", es = 0.5, alpha = 1,
                     beta = c(0.4, 0.6),
                     "manu", "lab"
)

dst.consumer <- node_new("util",
                         type = "SCES", es = 0.5, alpha = 1,
                         beta = c(0.4, 0.6),
                         "manu", "serv"
)

dstl <- list(dst.manu, dst.serv, dst.consumer)

ge <- sdm2(
  A = dstl,
  B = matrix(c(
    1, 0, 0,
    0, 1, 0,
    0, 0, 0
  ), 3, 3, TRUE),
  S0Exg = {
    S0Exg <- matrix(NA, 3, 3)
    S0Exg[3, 3] <- 100
    S0Exg
  },
  names.commodity = c("manu", "serv", "lab"),
  names.agent = c("manu", "serv", "consumer"),
  numeraire = c("manu"),
  ts = TRUE,
  policy = list(
    function(time, A) {
      if (time >= 5) {
        node_set(A[[1]], "cc1",
                 a = (1 + tpr)^-(time - 4)
        )
      }
    },
    policyMarketClearingPrice
  ),
  numberOfPeriods = 40,
  maxIteration = 1,
  z0 = c(160, 60, 100),
  p0 = c(1, 1, 1)
)

matplot(ge$ts.z, type = "o", pch = 20)
matplot(growth_rate(ge$ts.z), type = "o", pch = 20)
matplot(growth_rate(ge$ts.p), type = "o", pch = 20)
# }