R/gemstEndogenousProductionFunction_2_2.R

In GE: General Equilibrium Modeling

#' @export
#' @title A General Equilibrium Model with Endogenous Production Function
#' @aliases gemstEndogenousProductionFunction_2_2
#' @description
#' These are examples of spot-trading dynamic equilibria with endogenous production functions.
#' In these models, the parameters of the production functions vary with the output level in the previous period.
#'
#' To address locally or globally increasing returns to scale, we can use an endogenous CES-type production function with constant returns to scale, instead of adopting a more complex functional form.
#'
#' @param ... arguments to be passed to the function sdm2.
#' @seealso \code{\link{gemstIntertemporal_EndogenousProductionFunction_2_2}}
#' @examples
#' \donttest{
#' dst.firm <- node_new(
#'   "output",
#'   type = "CD", alpha = NA, beta = c(0.5, 0.5),
#'   "prod", "lab"
#' )
#'
#' dst.consumer <- node_new(
#'   "util",
#'   type = "Leontief", a = 1,
#'   "prod"
#' )
#'
#' ge <- sdm2(
#'   A = list(dst.firm, dst.consumer),
#'   B = matrix(c(
#'     1, 0,
#'     0, 0
#'   ), 2, 2, TRUE),
#'   S0Exg = matrix(c(
#'     NA, NA,
#'     NA, 1
#'   ), 2, 2, TRUE),
#'   names.commodity = c("prod", "lab"),
#'   names.agent = c("firm", "consumer"),
#'   numeraire = "lab",
#'   z0 = c(1, 1),
#'   p0 = c(1, 1),
#'   ts = TRUE,
#'   policy = list(
#'     function(A, state) {
#'       A[[1]]$alpha <- 5 * state$last.z[1]^0.1
#'     },
#'     policyMarketClearingPrice
#'   ),
#'   numberOfPeriods = 40,
#'   maxIteration = 1
#' )
#'
#' matplot(ge$ts.z, type = "o", pch = 20)
#'
#' # #### An example of a spot-trading dynamic equilibrium with corrective taxation.
#' # tau <- 0.2
#' #
#' # dst.firm <- node_new(
#' #   "output",
#' #   type = "CD", alpha = NA, beta = c(0.5, 0.5),
#' #   "prod", "lab"
#' # )
#' #
#' # dst.consumer <- node_new(
#' #   "util",
#' #   type = "Leontief", a = 1,
#' #   "prod"
#' # )
#' #
#' # ge <- sdm2(
#' #   A = list(dst.firm, dst.consumer),
#' #   B = matrix(c(
#' #     1, 0,
#' #     0, 0
#' #   ), 2, 2, TRUE),
#' #   S0Exg = matrix(c(
#' #     NA, NA,
#' #     100 * tau, 100 * (1 - tau)
#' #   ), 2, 2, TRUE),
#' #   names.commodity = c("prod", "lab"),
#' #   names.agent = c("firm", "consumer"),
#' #   numeraire = "lab",
#' #   z0 = c(100, 100),
#' #   p0 = c(1, 1),
#' #   ts = TRUE,
#' #   policy = list(
#' #     function(A, state) {
#' #       A[[1]]$alpha <- 2 * state$last.z[1]^0.1
#' #     },
#' #     policyMarketClearingPrice
#' #   ),
#' #   numberOfPeriods = 40,
#' #   maxIteration = 1
#' # )
#' #
#' # matplot(ge$ts.z, type = "o", pch = 20)
#' # ge$z
#' }

gemstEndogenousProductionFunction_2_2 <- function(...) sdm2(...)