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.Economies 2019, 7, 104 2 of 18 increases or decreases in forecasting skill. The present study addresses the first of these modes. The LL method is not itself a forecasting method.We examine three leading indexes and one coinciding/lagging index to Industrial production (IP) with respect to their LL relations. Sentiment-based indexes are frequently used as a forecasting device for the economy in the popular press that deals with economic issues, e.g., CNNmoney (2018) and FinancialTimes (2018). The ifo business climate index is a survey-based sentiment index for Germany from the ifo institute for economic research (IFO 2016). The ZEW business cycle index is from the ZEW (Centre for European Economic Research) (ZEW 2016). The third index is a series for "order flow" (OF) that we interpreted as a behavioral-based index. The fourth index is the standard unemployment index (UE), which is a coinciding/lagging index to IP (Enders 2010;Heij et al. 2011;Balcilar et al. 2013). The LL method can be applied to any pairs comprised of candidate leading time series and target time series, e.g., to update composite leading indicators (Abberger et al. 2018).In the present application, we calculate rolling average LL strength over three observations, and then over a longer time window (9 to 13 observations) to obtain a significance measure. By doing this, we can identify time windows where LL strength becomes weaker or stronger, or changes sign. This is a novel feature of the LL method compared to earlier applications.