Monetary Policy Analysis when Planning Horizons are Finite

Michael Woodford

No 12968, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: It is common to analyze the effects of alternative monetary policy commitments under the assumption of fully model-consistent expectations. This implicitly assumes unrealistic cognitive abilities on the part of economic decision makers. The relevant question, however, is not whether the assumption can be literally correct, but how much it would matter to model decision making in a more realistic way. A model is proposed, based on the architecture of artificial intelligence programs for problems such as chess or go, in which decision makers look ahead only a finite distance into the future, and use a value function learned from experience to evaluate situations that may be reached after a finite sequence of actions by themselves and others. Conditions are discussed under which the predictions of a model with finite-horizon forward planning are similar to those of a rational expectations equilibrium, and under which they are instead quite different. The model is used to re-examine the consequences that should be expected from a central-bank commitment to maintain a fixed nominal interest rate for a substantial period of time. “Neo-Fisherian†predictions are shown to depend on using rational expectations equilibrium analysis under circumstances in which it should be expected to be unreliable.

Keywords: Forward guidance; Bounded rationality; Neo-fisherianism (search for similar items in EconPapers)
JEL-codes: E03 E52 (search for similar items in EconPapers)
Date: 2018-06
New Economics Papers: this item is included in nep-dge, nep-mac, nep-mon and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (50)

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Related works:
Chapter: Monetary Policy Analysis When Planning Horizons Are Finite (2018)
Working Paper: Monetary Policy Analysis when Planning Horizons are Finite (2018)
Working Paper: Monetary Policy Analysis when Planning Horizons are Finite (2018)
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