Forecasting euro area inflation using a huge panel of survey expectations

TL;DR

This paper develops an econometric model using extensive survey expectation data to improve euro area inflation forecasts, highlighting the predictive value of firms' and consumers' economic outlooks.

Contribution

It introduces a novel approach leveraging a large panel of survey expectations and recent computational techniques for inflation forecasting.

Findings

Survey expectations improve inflation forecasts.

Firms' expectations have more predictive power than consumers'.

Including diverse survey data enhances predictive accuracy.

Abstract

In this paper, we forecast euro area inflation and its main components using an econometric model which exploits a massive number of time series on survey expectations for the European Commission's Business and Consumer Survey. To make estimation of such a huge model tractable, we use recent advances in computational statistics to carry out posterior simulation and inference. Our findings suggest that the inclusion of a wide range of firms and consumers' opinions about future economic developments offers useful information to forecast prices and assess tail risks to inflation. These predictive improvements do not only arise from surveys related to expected inflation but also from other questions related to the general economic environment. Finally, we find that firms' expectations about the future seem to have more predictive content than consumer expectations.