Computing Markov-Perfect Optimal Policies in Business-Cycle Models

Richard Dennis and Tatiana Kirsanova
Authors registered in the RePEc Author Service: Charles Nolan

Working Papers from Business School - Economics, University of Glasgow

Abstract: Time-inconsistency is an essential feature of many policy problems (Kydland and Prescott, 1977). This paper presents and compares three methods for computing Markov-perfect opti- mal policies in stochastic nonlinear business cycle models. The methods considered include value function iteration, generalized Euler-equations, and parameterized shadow prices. In the context of a business cycle model in which a scal authority chooses government spending and income taxation optimally, while lacking the ability to commit, we show that the solutions obtained using value function iteration and generalized Euler equations are somewhat more accurate than that obtained using parameterized shadow prices. Among these three methods, we show that value function iteration can be applied easily, even to environments that include a risk-sensitive scal authority and/or inequality constraints on government spending. We show that the risk-sensitive scal authority lowers government spending and income-taxation, reducing the disincentive households face to accumulate wealth.

Keywords: Markov-Perfect Policy; Time-Consistency; Fiscal Policy (search for similar items in EconPapers)
JEL-codes: C61 C63 E62 (search for similar items in EconPapers)
Date: 2014-11
New Economics Papers: this item is included in nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Journal Article: COMPUTING MARKOV-PERFECT OPTIMAL POLICIES IN BUSINESS-CYCLE MODELS (2016)
Working Paper: Computing Markov-Perfect Optimal Policies in Business-Cycle Models (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:gla:glaewp:2014_21

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