Comparing Sentiment- and Behavioral-Based Leading Indexes for Industrial Production: When Does Each Fail?

Abstract

We apply a relatively novel leading−lagging (LL) method to four leading and one lagging indexes for industrial production (IP) in Germany. We obtain three sets of results. First, we show that the sentiment-based ifo index performs best in predicting the general changes in IP (−0.596, range −1.0 to 1.0, −1.0 being best). The ZEW index is very close (−0.583). In third place comes, somewhat unexpectedly, the behavioral-based unemployment index (−0.564), and last comes order flow, OF (−0.186). Second, we applied the LL method to predefined recession and recovery time windows. The recessions were best predicted (−0.70), the recoveries worst (−0.32), and the overall prediction was intermediate (−0.48). Third, the method identifies time windows automatically, even for short time windows, where the leading indexes fail. All indexes scored low during time windows around 1997 and 2005. Both periods correspond to anomalous periods in the German economy. The 1997 period coincides with “the great moderation” in the US at the end of a minor depression in Germany. Around 2005, oil prices increased from $10 to $60 a barrel. There were few orders, and monetary supply was low. Our policy implications suggest that the ZEW index performs best (including recessions and recoveries), but unemployment and monetary supply should probably be given more weight in sentiment forecasting.

Keywords

• leading indexes
• industrial production
• prediction skill
• survey-based indexes
• sentiment-based index
• germany