Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This article presents further evidence on the hypothesis of news driven business cycles. I use a structural Vector Error Correction Model (VECM) approach to identify news shocks as in Beaudry and Lucke (BL, 2010). I document three facts: first, news shocks identified by BL are Granger causal for US patent data; second, BL's analysis applied to German macro data reveals very similar patterns: activity is largely driven by news, and news shocks explain a sizable and increasing share of Total Factor Productivity (TFP) variance at long horizons; and third, German news shocks are Granger causal for German patent data and the pattern is, again, very similar to the US. Since patent data in the US and Germany are almost uncorrelated, the similarity is striking and strongly suggests a technology interpretation of news shocks.