Computational Macroeconomics for the Open Economy by G. C. Lim, Paul D. McNelis

By G. C. Lim, Paul D. McNelis

Policymakers desire quantitative in addition to qualitative solutions to urgent coverage questions. due to advances in computational equipment, quantitative estimates are actually derived from coherent nonlinear dynamic macroeconomic versions embodying measures of probability and calibrated to trap particular features of real-world occasions. this article indicates how such versions should be made obtainable and operational for confronting coverage concerns. The booklet starts off with an easy environment in accordance with market-clearing cost flexibility. It progressively contains departures from the easy aggressive framework within the type of expense and salary stickiness, taxes, rigidities in funding, monetary frictions, and behavior endurance in intake. such a lot chapters finish with computational workouts; the Matlab code for the bottom version are available within the appendix. because the types evolve, readers are inspired to switch the codes from the 1st easy version to extra advanced extensions. Computational Macroeconomics for the Open financial system can be utilized via graduate scholars in economics and finance in addition to policy-oriented researchers.

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The second reason is that adopting a Taylor rule in the flexible price case introduces a type of informational rigidity, and comparing results from a model with the rule to a model without the rule allows us to assess how this type of behavior affects dynamic adjustments in the economy. Taxes and Domestic Debt fixed in this chapter: Government spending G is assumed to be Gt ¼ G: ð2:15Þ The Treasury receives lump-sum taxes Taxt and borrows Bt , where B is a one-period domestic bond. The evolution of bonds is Bt ¼ ð1 þ Rt 1 ÞBt 1 þ Pt Gt À Taxt : ð2:16Þ For this chapter, G is set at zero and B is fixed.

But we note that fat tails and volatility clustering are pervasive features of observed macroeconomic data, so there is no reason not to use wider classes of distributions for solving and simulating dynamic stochastic models. As Fernandez-Villaverde (2005) and Justiniano and Primiceri (2006) emphasize, there is no reason for a stochastic dynamic general equilibrium model not to have a richer structure than normal innovations. However, for the first-order perturbation approach, small normally distributed innovations are necessary.

In this section we examine the effects of one alternative factor—exogenous changes in foreign demand for the export goods of the domestic country. We use the same model, only this time, a demand factor, rather than a supply factor, is the key variable forcing the dynamic response of the economy. This is a natural juxtaposition, since we can readily compare the effects of demand with supply impulses, and check to see, in this simple framework, if they agree with widely shared intuition about how the macroeconomic variables should respond to underlying changes in demand as well as supply.

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