Common Components Structural VARs

Small scale VAR models are subject to two major issues: first, the information set might
be too narrow; second, many macroeconomic variables are measured with error. The two
features produce distorted estimates of the impulse response functions. We propose a
new procedure, called Common Components Structural VARs (CC-SVAR), which solves
both problems. It consists in (a) treating the variables, prior to estimation, in order to
extract their common components; this eliminates measurement errors; (b) estimating a
VAR with m > q common components, that is a singular VAR, where q is the number
of shocks driving the economy; this solves the fundamentalness problem. SVARs and
CC-SVARs are compared in the empirical analysis of monetary policy and technology
shocks. The results obtained by SVARs are not robust, in that they strongly depend
on the choice and the treatment of the variables considered. On the contrary, using CCSVARs (i) contractionary monetary shocks produce a decrease of prices independently of
the variables included in the model, (ii) irrespective of whether hours worked enter the
model in log-levels or growth rates, technology improvements produce an increase in hours
worked