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Measuring Inflation Expectations Uncertainty Using High‐Frequency Data
Author(s) -
CHAN JOSHUA C.C.,
SONG YONG
Publication year - 2018
Publication title -
journal of money, credit and banking
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.763
H-Index - 108
eISSN - 1538-4616
pISSN - 0022-2879
DOI - 10.1111/jmcb.12498
Subject(s) - inflation (cosmology) , economics , measure (data warehouse) , recession , econometrics , great recession , construct (python library) , monetary policy , macroeconomics , keynesian economics , computer science , physics , theoretical physics , programming language , database
Inflation expectations play a key role in determining future economic outcomes. The associated uncertainty provides a direct gauge of how well‐anchored the inflation expectations are. We construct a model‐based measure of inflation expectations uncertainty by augmenting a standard unobserved components model of inflation with information from noisy and possibly biased measures of inflation expectations obtained from financial markets. This new model‐based measure of inflation expectations uncertainty is more accurately estimated and can provide valuable information for policymakers. Using U.S. data, we find significant changes in inflation expectations uncertainty during the Great Recession.