I propose to identify announcement-specific decompositions of asset price changes into monetary policy shocks exploiting heteroskedasticity in intraday data, accommodating both changes in the nature of shocks and the state of the economy across announcements. I compute decompositions with respect to Fed Funds, forward guidance, asset purchase, and Fed information shocks from January 1996 to December 2019. The decompositions illustrate which announcements of unconventional policy measures had significant effects during the Great Recession. Overall, forward guidance and asset purchases have significant effects on yields, spreads, equities, and uncertainty, but the effects of monetary policy vary over time, particularly asset purchases.

Identification via heteroskedasticity exploits variance changes between regimes to identify parameters in simultaneous equations. Weak identification occurs when shock variances change very little or multiple variances change close to proportionally, making standard inference unreliable. I propose an F -test for weak identification in a common simple version of the model. More generally, I establish conditions for validity of nonconservative robust inference on subsets of the parameters, which can be used to test for weak identification. I study monetary policy shocks identified using heteroskedasticity in high-frequency data. I detect weak identification, invalidating standard inference, in daily data, while intraday data provide strong identification.