Abstract
Ever since their initiation 60 years ago, the harmonized European Business and Consumer Surveys (BCS) have risen to the challenge of performing as a solid data pillar for quantifying leading indicators of economic activity. However, mainstream research mainly focuses on publicly available composite BCS confidence indicators and inspects their predictive accuracy. We depart from this stance by considering a battery of novel techniques for quantifying BCS-based leading indicators with the particular aim to evaluate their predictive characteristics compared to conventional BCS leading indicators. We build upon the recently established weighted balance method, forecast disagreement, and surprise index. Additionally, we differ from the standpoint of rational expectations by introducing indicators of irrational sentiment and adaptive expectations, which have not previously been used in BCS studies of this sort. Our analysis in industry, consumer, and retail trade sectors of 28 European economies reveals that most of these novel techniques (especially irrational sentiment and adaptive expectations) produce more accurate predictions of economic activity than standard BCS benchmarks. These results are robust to several panel estimation procedures (heterogeneous panel Granger causality test and panel vector autoregressions, in particular). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11135-021-01306-4.