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Annukka Ristiniemi

4 May 2020
WORKING PAPER SERIES - No. 2399
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Abstract
We consider the effects of quantitative easing on liquidity and prices of bonds in a search-and matching model. The model explicitly distinguishes between demand and supply effects of central bank asset purchases. Both are shown to lead to a decline in yields, while they have opposite effects on market liquidity. This results in a price-liquidity trade-off. Initially, liquidity improves in reaction to central bank demand. As the central bank buys and holds bonds, supply becomes scarcer and other buyers are crowded out. As a result, liquidity can fall below initial levels. The magnitude of the effects depend on the presence of preferred habitat investors. In markets with a higher share of these investors, bonds are scarcer and central bank asset purchases lower yields more. With a lower share of preferred habitat investors and a relatively illiquid market, central bank demand has a stronger positive effect on liquidity. We are the first to construct an index from bond holding data to measure the prevalence of preferred habitat investors in each euro area country. Subsequently, we calibrate the model to the euro area and show how yields and liquidity are affected by the European Central Banks asset purchase programme.
JEL Code
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
19 May 2021
WORKING PAPER SERIES - No. 2555
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Abstract
This paper presents a toolkit for generating optimal policy projections. It makes five contributions. First, the toolkit requires a minimal set of inputs: only a baseline projection for target and instrument variables and impulse responses of those variables to policy shocks. Second, it solves optimal policy projections under commitment, limited-time commitment, and discretion. Third, it handles multiple policy instruments. Fourth, it handles multiple constraints on policy instruments such as a lower bound on the policy rate and an upper bound on asset purchases. Fifth, it allows alternative approaches to address the forward guidance puzzle. The toolkit that accompanies this paper is Dynare compatible, which facilitates its use. Examples replicate existing results in the optimal monetary policy literature and illustrate the usefulness of the toolkit for highlighting policy trade-offs. We use the toolkit to analyse US monetary policy at the height of the Great Financial Crisis. Given the Fed’s early-2009 baseline macroeconomic projections, we find the Fed’s planned use of the policy rate was close to optimal whereas a more aggressive QE program would have been beneficial.
JEL Code
C61 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Optimization Techniques, Programming Models, Dynamic Analysis
C63 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Computational Techniques, Simulation Modeling
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies