This paper is the first attempt to investigate the performance of different learning rules in fitting survey data of household and expert inflation expectations in five core European economies (France, Germany, Italy, Netherlands and Spain). Overall it is found that constant gain learning performs well in out-of-sample forecasting. It is also shown that households in high inflation countries are using higher best fitting constant gain parameters than those in low inflation countries. They are hence able to pick up structural changes faster. Professional forecasters update their information sets more frequently than households. Furthermore, household expectations in the Euro Area have not converged to the inflation goal of the ECB, which is to keep inflation below to but close to 2% in the medium run. This contrasts the findings for professional experts, which seem to be more inclined to incorporate the implications of monetary union for the convergence in inflation rates into their expectations. --
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)