Heterogeneous Information about the Term Structure of Interest rates, Least-Squares Learning and Optimal Interest Rate Rules for Inflation Forecast Targeting

E. Schaling, S.C.W. Eijffinger, M.F. Tesfaselassie

Research output: Working paperDiscussion paperOther research output

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Abstract

In this paper we incorporate the term structure of interest rates in a standard inflation forecast targeting framework.Learning about the transmission process of monetary policy is introduced by having heterogeneous agents - i.e. the central bank and private agents - who have different information sets about the future sequence of short-term interest rates.We analyse inflation forecast targeting in two environments.One in which the central bank has perfect knowledge, in the sense that it understands and observes the process by which private sector interest rate expectations are generated, and one in which the central bank has imperfect knowledge and has to learn the private sector forecasting rule for short-term interest rates.In the case of imperfect knowledge, the central bank has to learn about private sector interest rate expectations, as the latter affect the impact of monetary policy through the expectations theory of the term structure of interest rates.Here following Evans and Honkapohja (2001), the learning scheme we investigate is that of least-squares learning (recursive OLS) using the Kalman filter.We find that optimal monetary policy under learning is a policy that separates estimation and control.Therefore, this model suggests that the practical relevance of the breakdown of the separation principle and the need for experimentation in policy may be limited.
Original languageEnglish
Place of PublicationTilburg
PublisherMacroeconomics
Number of pages35
Volume2004-14
Publication statusPublished - 2004

Publication series

NameCentER Discussion Paper
Volume2004-14

Fingerprint

Term structure of interest rates
Central bank
Inflation forecasts
Interest rate rules
Targeting
Least squares learning
Private sector
Short-term interest rates
Interest rates
Monetary policy
Experimentation
Breakdown
Optimal monetary policy
Heterogeneous agents
Kalman filter
Practical relevance
Expectations theory

Keywords

  • information
  • term structure of interest rates
  • least squares
  • optimization
  • inflation
  • forecasting
  • learning
  • rational expectations
  • kalman filter

Cite this

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Heterogeneous Information about the Term Structure of Interest rates, Least-Squares Learning and Optimal Interest Rate Rules for Inflation Forecast Targeting. / Schaling, E.; Eijffinger, S.C.W.; Tesfaselassie, M.F.

Tilburg : Macroeconomics, 2004. (CentER Discussion Paper; Vol. 2004-14).

Research output: Working paperDiscussion paperOther research output

TY - UNPB

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AU - Eijffinger, S.C.W.

AU - Tesfaselassie, M.F.

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N2 - In this paper we incorporate the term structure of interest rates in a standard inflation forecast targeting framework.Learning about the transmission process of monetary policy is introduced by having heterogeneous agents - i.e. the central bank and private agents - who have different information sets about the future sequence of short-term interest rates.We analyse inflation forecast targeting in two environments.One in which the central bank has perfect knowledge, in the sense that it understands and observes the process by which private sector interest rate expectations are generated, and one in which the central bank has imperfect knowledge and has to learn the private sector forecasting rule for short-term interest rates.In the case of imperfect knowledge, the central bank has to learn about private sector interest rate expectations, as the latter affect the impact of monetary policy through the expectations theory of the term structure of interest rates.Here following Evans and Honkapohja (2001), the learning scheme we investigate is that of least-squares learning (recursive OLS) using the Kalman filter.We find that optimal monetary policy under learning is a policy that separates estimation and control.Therefore, this model suggests that the practical relevance of the breakdown of the separation principle and the need for experimentation in policy may be limited.

AB - In this paper we incorporate the term structure of interest rates in a standard inflation forecast targeting framework.Learning about the transmission process of monetary policy is introduced by having heterogeneous agents - i.e. the central bank and private agents - who have different information sets about the future sequence of short-term interest rates.We analyse inflation forecast targeting in two environments.One in which the central bank has perfect knowledge, in the sense that it understands and observes the process by which private sector interest rate expectations are generated, and one in which the central bank has imperfect knowledge and has to learn the private sector forecasting rule for short-term interest rates.In the case of imperfect knowledge, the central bank has to learn about private sector interest rate expectations, as the latter affect the impact of monetary policy through the expectations theory of the term structure of interest rates.Here following Evans and Honkapohja (2001), the learning scheme we investigate is that of least-squares learning (recursive OLS) using the Kalman filter.We find that optimal monetary policy under learning is a policy that separates estimation and control.Therefore, this model suggests that the practical relevance of the breakdown of the separation principle and the need for experimentation in policy may be limited.

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KW - rational expectations

KW - kalman filter

M3 - Discussion paper

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BT - Heterogeneous Information about the Term Structure of Interest rates, Least-Squares Learning and Optimal Interest Rate Rules for Inflation Forecast Targeting

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