Learning in MacroeconomicsAn Empirical Approach
Learning in Macroeconomics
An Empirical Approach
View/Type of Scholarly Publication
DissertationDate of Exam
06.04.2009Date of Publication
23.04.2009Advisor
von Hagen, JürgenCo-Referee
Linnemann, LudgerMetadata
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Abstract
This thesis explores the role of adaptive learning in explaining empirical phenomena such as the Great Inflation. We show that the historic monetary policy deviated from the optimally recommended policy under learning. These deviations are caused by Brainard-type uncertainty which induces a conservative policy stance. Accounting for both imperfect knowledge and estimation uncertainty, the optimal policy under adaptive learning is consistent with historic policy behavior. However, we show that an optimizing but informationally constrained policy maker would most likely have experienced a Great Inflation like episode. Furthermore, we develop an estimation method to implement the adaptive learning hypothesis into DSGE modelling, thus extending the standard estimation toolbox.
Subjects
Adaptives Lernen, Erwartungsbildung, DSGE-Schätzung, Optimale Geldpolitik, Unvollständige Information, Neu-Keynesianische Modelle, Große Inflation, Adaptive learning, expectations formation, DSGE estimation, optimal monetary policy, imperfect information, New Keynesian models, Great Inflation
Classification (DDC)
330 WirtschaftJunker, Simon: Learning in Macroeconomics : An Empirical Approach. - Bonn, 2009. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5-17222
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5-17222
@phdthesis{handle:20.500.11811/3998,
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5-17222,
author = {{Simon Junker}},
title = {Learning in Macroeconomics : An Empirical Approach},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2009,
month = apr,
note = {This thesis explores the role of adaptive learning in explaining empirical phenomena such as the Great Inflation. We show that the historic monetary policy deviated from the optimally recommended policy under learning. These deviations are caused by Brainard-type uncertainty which induces a conservative policy stance. Accounting for both imperfect knowledge and estimation uncertainty, the optimal policy under adaptive learning is consistent with historic policy behavior. However, we show that an optimizing but informationally constrained policy maker would most likely have experienced a Great Inflation like episode. Furthermore, we develop an estimation method to implement the adaptive learning hypothesis into DSGE modelling, thus extending the standard estimation toolbox.},
url = {https://hdl.handle.net/20.500.11811/3998}
}
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5-17222,
author = {{Simon Junker}},
title = {Learning in Macroeconomics : An Empirical Approach},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2009,
month = apr,
note = {This thesis explores the role of adaptive learning in explaining empirical phenomena such as the Great Inflation. We show that the historic monetary policy deviated from the optimally recommended policy under learning. These deviations are caused by Brainard-type uncertainty which induces a conservative policy stance. Accounting for both imperfect knowledge and estimation uncertainty, the optimal policy under adaptive learning is consistent with historic policy behavior. However, we show that an optimizing but informationally constrained policy maker would most likely have experienced a Great Inflation like episode. Furthermore, we develop an estimation method to implement the adaptive learning hypothesis into DSGE modelling, thus extending the standard estimation toolbox.},
url = {https://hdl.handle.net/20.500.11811/3998}
}
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