R/gemConstantGrowthPath_TechnologyProgress_3_3.R

In GE: General Equilibrium Modeling

#' @export
#' @title Constant Growth Paths with Technology Progress
#' @aliases gemConstantGrowthPath_TechnologyProgress_3_3
#' @description This is an example of a market-clearing path converging to a constant growth path.
#' In a constant growth path, the supply of each commodity grows at a constant rate.
#' The balanced growth path is a special case of the constant growth path.
#' @param ... arguments to be passed to the function sdm2.
#' @examples
#' \donttest{
#' dst.firm1 <- node_new(
#'   "output",
#'   type = "CD", alpha = 1, beta = c(0.35, 0.65),
#'   "prod1", "lab"
#' )
#'
#' dst.firm2 <- node_new(
#'   "output",
#'   type = "CD", alpha = 1, beta = c(0.4, 0.6),
#'   "prod1", "lab"
#' )
#'
#' dst.consumer <- node_new(
#'   "util",
#'   type = "Leontief", a = 1,
#'   "prod2"
#' )
#'
#' ge <- sdm2(
#'   A = list(dst.firm1, dst.firm2, dst.consumer),
#'   B = matrix(c(
#'     1, 0, 0,
#'     0, 1, 0,
#'     0, 0, 0
#'   ), 3, 3, TRUE),
#'   S0Exg = matrix(c(
#'     NA, NA, NA,
#'     NA, NA, NA,
#'     NA, NA, 1
#'   ), 3, 3, TRUE),
#'   names.commodity = c("prod1", "prod2", "lab"),
#'   names.agent = c("firm1", "firm2", "consumer"),
#'   numeraire = "lab",
#'   z0 = c(0.2, 0.2, 1),
#'   ts = TRUE,
#'   policy = list(
#'     function(time, A, state) {
#'       A[[1]]$alpha <- exp(time * 0.01)
#'       A[[2]]$alpha <- exp(time * 0.01)
#'       state$S[3, 3] <- exp(time * 0.01)
#'       state
#'     },
#'     policyMarketClearingPrice
#'   ),
#'   numberOfPeriods = 20,
#'   maxIteration = 1
#' )
#'
#' matplot(ge$ts.z, type = "l")
#' matplot(log(ge$ts.z[, 1:2]), type = "l")
#' matplot(growth_rate(ge$ts.z[, 1:2], log = TRUE), type = "o", pch = 20)
#' matplot(growth_rate(ge$ts.p[, 1:2], log = TRUE), type = "o", pch = 20)
#' }

gemConstantGrowthPath_TechnologyProgress_3_3 <- function(...) sdm2(...)