Instrumental Variable Identification of Dynamic Variance Decompositions

Citation:

Plagborg-Møller, Mikkel, and Christian K. Wolf. Forthcoming. “Instrumental Variable Identification of Dynamic Variance Decompositions.” Journal of Political Economy.

Abstract:

Macroeconomists increasingly use external sources of exogenous variation for causal inference. However, unless such external instruments (proxies) capture the underlying shock without measurement error, existing methods are silent on the importance of that shock for macroeconomic fluctuations. We show that, in a general moving average model with external instruments, variance decompositions for the instrumented shock are interval-identified, with informative bounds. Various additional restrictions guarantee point identification of both variance and historical decompositions. Unlike SVAR analysis, our methods do not require invertibility. Applied to U.S. data, they give a tight upper bound on the importance of monetary shocks for inflation dynamics.

Notes:

Matlab code suite and data (GitHub)

arXiv

Last updated on 12/03/2021