Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We resume the line of research pioneered by C. A. Sims and Zha (Macroeconomic Dynamics, 2006, 10, 231–272) and make two novel contributions. First, we provide a formal treatment of partial fundamentalness—that is, the idea that a structural vector autoregression (VAR) can recover, either exactly or with good approximation, a single shock or a subset of shocks, even when the underlying model is nonfundamental. In particular, we extend the measure of partial fundamentalness proposed by Sims and Zha to the finite‐order case and study the implications of partial fundamentalness for impulse‐response and variance‐decomposition analysis. Second, we present an application where we validate a theory of news shocks and find it to be in line with the empirical evidence.