Comparing sentiment- and behavioral-based leading indexes for industrial production:When does each fail?
Journal article, Peer reviewed
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Date
2019Metadata
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Original version
Seip KL, Yilmaz Y, Schröder M. Comparing Sentiment- and Behavioral-BasedLeading Indexes for Industrial Production:When Does Each Fail?. Economies. 2019;7 https://dx.doi.org/10.3390/economies7040104Abstract
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.
Publisher
MDPISeries
Economies; Volume 7 / Issue 4Journal
Economies
Except where otherwise noted, this item's license is described as © 2019 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/.