When all we have is not enough: a search for the optimal method of quantifying inflation expectations

Although inflation expectations are pivotal variables for central banks, they are not directly observable. Therefore, central banks use qualitative survey results to proxy consumer expectations, and their quantification in this manner is often criticized. In this study, we investigate and identify an optimal quantification procedure for survey results based on a set of regression and probabilistic models. Specifically, we seek to identify the method that returns time series that are most highly correlated with an unbiased representative of survey-based expectation: balance statistics. We place additional constraints on this criterion to identify the procedure that returns expectations that are most closely related to consumer intentions (directional co-movements and forecast accuracy). Our sample covers the European Union member states over the period of January 2002 to June 2019. We also test a post-crisis subsample. Our results suggest that different procedures may be optimal for different economies, in line with previous findings on cross-country divergences of expectations formation. However, we find that the most applied assumption of normal distribution does not prove to be the best one. Our recommendation is to apply probabilistic procedures rather than regression methods.