Too Many Shocks Spoil the Interpretation
42 Pages Posted: 6 Apr 2020
There are 2 versions of this paper
Too Many Shocks Spoil the Interpretation
Too Many Shocks Spoil the Interpretation
Date Written: April 2, 2020
Abstract
We show that when a model has more shocks than observed variables the estimated filtered and smoothed shocks will be correlated. This is despite no correlation being present in the data generating process. Additionally the estimated shock innovations may be autocorrelated. These correlations limit the relevance of impulse responses, which assume uncorrelated shocks, for interpreting the data. Excess shocks occur frequently, e.g. in Unobserved-Component (UC) models, filters, including Hodrick-Prescott (1997), and some Dynamic Stochastic General Equilibrium (DSGE) models. Using several UC models and an estimated DSGE model, Ireland (2011), we demonstrate that sizable correlations among the estimated shocks can result.
Keywords: Partial Information; Structural Shocks; Kalman Filter; Measurement Error; DSGE
JEL Classification: E37; C51; C52
Suggested Citation: Suggested Citation