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Using Survey Data of Inflation Expectations in the Estimation of Learning and Rational Expectations Models
Author(s) -
ORMEÑO ARTURO,
MOLNÁR KRISZTINA
Publication year - 2015
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.12224
Subject(s) - rational expectations , macro , inflation (cosmology) , new keynesian economics , survey data collection , adaptive expectations , econometrics , survey of professional forecasters , computer science , adaptive learning , estimation , economics , monetary policy , artificial intelligence , keynesian economics , statistics , mathematics , physics , theoretical physics , programming language , management
Does survey data contain useful information for estimating macroeconomic models? We address this question by using survey data of inflation expectations to estimate the New Keynesian model by Smets and Wouters ([Smets, Frank, 2007]) and compare its performance under rational expectations and adaptive learning. The survey information serves as an additional moment restriction and helps us to determine the learning agents' forecasting model for inflation. Adaptive learning fares similarly to rational expectations in fitting macro data, but clearly outperforms rational expectations in fitting macro and survey data simultaneously. In other words, survey data contain additional information that is not present in the macro data alone.