The formation of European inflation expectations: One learning rule does not fit all

We empirically investigate how well different learning rules manage to explain the formation of household inflation expectations in six key member countries of the euro area. Our findings reveal a pronounced heterogeneity in the learning rules employed on the country level. While the expectation formation process in some countries can be best explained by rules that incorporate forward-looking elements (Germany, Italy, the Netherlands), households in other countries employ information on energy prices (France) or form their expectations by means of more traditional learning rules (Belgium, Spain). Moreover, our findings suggest that least squares based algorithms significantly outperform their stochastic gradient counterparts, not only in replicating inflation expectation data but also in forecasting actual inflation rates.

Keywords: Inflation expectations, adaptive learning algorithms, household survey. 
JEL classifications: E31, E37, D84, C53.

Working paper no. 472