R/demCreditPolicy.R

In GE: General Equilibrium Modeling

#' @export
#' @title A Disequilibrium Model with Credit
#' @aliases demCreditPolicy
#' @description These are some examples to illustrate that credit policies may lead to business cycles.
#' When the firm's profit rate is high, the laborer lends labor or labor income to the firm; when the firm's profit rate is low, the firm repays the loan with products.
#' @param ... arguments to be passed to the function sdm2.
#' @examples
#' \donttest{
#' dst.firm <- node_new("output",
#'   type = "CD", alpha = 1.2,
#'   beta = c(0.5, 0.5),
#'   "prod", "lab"
#' )
#'
#' dst.consumer <- node_new("utility",
#'   type = "Leontief", a = 1,
#'   "prod"
#' )
#'
#' f <- function(policy = NULL) {
#'   ge <- sdm2(
#'     A = list(dst.firm, dst.consumer),
#'     B = matrix(c(
#'       1, 0,
#'       0, 1
#'     ), 2, 2, TRUE),
#'     S0Exg = matrix(c(
#'       NA, NA,
#'       NA, 100
#'     ), 2, 2, TRUE),
#'     names.commodity = c("prod", "lab"),
#'     names.agent = c("firm", "consumer"),
#'     ts = TRUE,
#'     policy = policy,
#'     numberOfPeriods = 200,
#'     maxIteration = 1,
#'     priceAdjustmentVelocity = 0.05
#'   )
#'
#'   matplot(ge$ts.z, type = "o", pch = 20)
#'   ge
#' }
#'
#' ## no credit policy
#' ge <- f()
#'
#' ## credit policy
#' policy.credit <- function(time, state) {
#'   profit.rate <- state$p[1] / sum(state$last.A[, 1] * state$p) - 1
#'
#'   if (profit.rate > 0.01) {
#'     state$S[2, 2] <- 50
#'     state$S[2, 1] <- 50
#'   } else if (profit.rate < -0.01) {
#'     state$S[1, 2] <- state$S[1, 1] * 0.5
#'     state$S[1, 1] <- state$S[1, 1] * 0.5
#'   }
#'
#'   state
#' }
#'
#' de <- f(policy = policy.credit)
#'
#' #### an example with 3 firms.
#' policy.credit <- function(time, state) {
#'   if (time <= 10) {
#'     return(state)
#'   }
#'   profit.rate <- state$p[1] / sum(state$last.A[, 1] * state$p) - 1
#'
#'   if (profit.rate > 0.01) {
#'     state$S[3, 1] <- 30
#'     # state$S[3, 1:3] <- 10
#'     state$S[3, 4] <- 70
#'   } else if (profit.rate < -0.01) {
#'     state$S[1, 4] <- state$S[1, 1] * 0.3
#'     state$S[1, 1] <- state$S[1, 1] * 0.7
#'   }
#'
#'   state
#' }
#'
#' f <- function(policy = NULL,
#'               numberOfPeriods = 50) {
#'   ge <- sdm2(
#'     A = function(state) {
#'       a.firm.prod <- CD_A(alpha = 1, Beta = c(0, 0.5, 0.5, 0), state$p)
#'       a.firm.cap1 <- c(1, 0, 0.1, 0)
#'       a.firm.cap2 <- c(0, 0, 0.1, 1)
#'       a.consumer <- c(1, 0, 0, 0)
#'       cbind(a.firm.prod, a.firm.cap1, a.firm.cap2, a.consumer)
#'     },
#'     B = matrix(c(
#'       1, 0, 0, 0,
#'       0, 0, 1, 0,
#'       0, 0, 0, 0,
#'       0, 1, 0, 0
#'     ), 4, 4, TRUE),
#'     S0Exg = {
#'       tmp <- matrix(NA, 4, 4)
#'       tmp[3, 4] <- 100
#'       tmp
#'     },
#'     names.commodity = c("prod", "cap2", "lab", "cap1"),
#'     names.agent = c("firm.prod", "firm.cap1", "firm.cap2", "consumer"),
#'     numeraire = "lab",
#'     maxIteration = 1,
#'     numberOfPeriods = numberOfPeriods,
#'     ts = TRUE,
#'     p0 = c(4.191, 4.391, 1, 4.291),
#'     # The equilibrium output of firm.prod is 45.64.
#'     z0 = c(50, 21.78, 21.78, 23.86),
#'     policy = policy
#'   )
#'
#'   matplot(ge$ts.z, type = "o", pch = 20)
#'   ge
#' }
#'
#' ## a disequilibrium path
#' de <- f(numberOfPeriods = 500)
#'
#' ## market-clearing path converging to equilibrium
#' ge <- f(
#'   policy = policyMarketClearingPrice,
#'   numberOfPeriods = 40
#' )
#' ge$p
#' ge$z
#'
#' ## a market-clearing path with persisting fluctuations
#' de <- f(policy = list(
#'   policy.credit,
#'   policyMarketClearingPrice
#' ))
#' }

demCreditPolicy <- function(...) sdm2(...)