Identifying Government Spending Shocks: It's all in the Timing*

TLDR

Standard VAR identification methods find that government spending raises consumption and real wages, whereas the Ramey–Shapiro narrative approach finds the opposite. The study constructs richer government spending news variables from 1939 to 2008 using a narrative method to better measure anticipations. A narrative method is employed to construct richer government spending news variables covering 1939–2008. The analysis reveals that the key difference between approaches is timing, with professional forecasts and narrative shocks Granger‑causing VAR shocks, and implied government spending multipliers range from 0.6 to 1.2.

Abstract

Standard vector autoregression (VAR) identification methods find that government spending raises consumption and real wages; the Ramey–Shapiro narrative approach finds the opposite. I show that a key difference in the approaches is the timing. Both professional forecasts and the narrative approach shocks Granger-cause the VAR shocks, implying that these shocks are missing the timing of the news. Motivated by the importance of measuring anticipations, I use a narrative method to construct richer government spending news variables from 1939 to 2008. The implied government spending multipliers range from 0.6 to 1.2.