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A Toolkit for Solving Models with a Lower Bound on Interest Rates of Stochastic Duration

Gauti Eggertsson, Sergey K. Egiev, Alessandro Lin, Josef Platzer and Luca Riva ()

No 2020-14, Working Papers from Brown University, Department of Economics

Abstract: This paper presents a toolkit to solve for equilibrium in economies with the effective lower bound (ELB) on the nominal interest rate in a computationally efficient way under a special assumption about the underlying shock process, a two-state Markov process with an absorbing state. We illustrate the algorithm in the canonical New Keynesian model, replicating the optimal monetary policy in Eggertsson and Woodford (2003), as well as showing how the toolkit can be used to analyse the medium-scale DSGE model developed by the Federal Reserve Bank of New York. As an application, we show how various policy rules perform relative to the optimal commitment equilibrium. A key conclusion is that previously suggested strategies – such as price level targeting and nominal GDP targeting – do not perform well when there is a small drop in the price level, as observed during the Great Recession, because they do not imply a sufficiently strong commitment to low future interest rates (†make-up strategy†). We propose two new policy rules, Cumulative Nominal GDP Targeting Rule and Symmetric Dual-Objective Targeting Rule that are more robust. Had these policies been in place in 2008, they would have reduced the output contraction by approximately 80 percent. If the Federal Reserve had followed Average Inflation Targeting – which can arguably approximate the new policy

Date: 2020
New Economics Papers: this item is included in nep-cba, nep-dge, nep-mac and nep-mon
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Citations: View citations in EconPapers (7)

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Journal Article: A Toolkit for Solving Models with a Lower Bound on Interest Rates of Stochastic Duration (2021) Downloads
Working Paper: A Toolkit for Solving Models with a Lower Bound on Interest Rates of Stochastic Duration (2020) Downloads
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