makePolicyStickyPrice: Make a Policy of Sticky Price

In GE: General Equilibrium Modeling

Make a Policy of Sticky Price

Description

Given a stickiness value and a time window vector, this function returns a policy function that sets the current prices equal to the weighted mean of the market-clearing prices and the current prices during this time window. When the stickiness value is 0, the prices will be set to the market-clearing prices. When the stickiness value is 1, the current prices will keep unchanged.

Usage

makePolicyStickyPrice(stickiness = 0.5, time.win = c(1, Inf), tolCond = 1e-06)

Arguments

stickiness	a stickiness value between 0 and 1.
time.win	the time window vector, i.e. a 2-vector specifying the start time and end time of policy implementation.
tolCond	the tolerance condition for computing the market-clearing price vector.

Value

A policy function, which is often used as an argument of the function sdm2.

Note

Three major price adjustment methods can be used in the structural dynamic model. The corresponding three kinds of prices are exploratory prices (the default case), market clearing prices, and sticky prices. The exploratory prices are computed based on the prices and sales rates of the previous period. In economic reality, the market clearing prices are unknown, so exploratory prices are more realistic.

When the stickiness value is positive and the priceAdjustmentVelocity parameter in sdm2 is set to 0 (meaning the current prices are equal to those from the previous period), executing the sticky-price policy will yield current prices that are the weighted average of the market-clearing prices and the prices from the previous period. Typically, this function should be utilized in this manner.

See Also

sdm2

Examples

InitialEndowments <- {
  tmp <- matrix(0, 3, 2)
  tmp[1, 1] <- 0.01
  tmp[2, 2] <- tmp[3, 2] <- 1
  tmp
}

ge <- gemCanonicalDynamicMacroeconomic_3_2(
  priceAdjustmentVelocity = 0,
  policy.supply = makePolicySupply(InitialEndowments),
  policy.price = makePolicyStickyPrice(stickiness = 0.5),
  ts = TRUE,
  maxIteration = 1,
  numberOfPeriods = 50
)

par(mfrow = c(1, 2))
matplot(ge$ts.z, type = "o", pch = 20)
matplot(ge$ts.p, type = "o", pch = 20)

GE documentation built on Nov. 8, 2023, 9:07 a.m.