Date: 2006
Type: Working Paper
Business Cycle Analysis and VARMA Models
Working Paper, EUI ECO, 2006/37
KASCHA, Christian, MERTENS, Karel, Business Cycle Analysis and VARMA Models, EUI ECO, 2006/37 - https://hdl.handle.net/1814/6450
Retrieved from Cadmus, EUI Research Repository
An important question in empirical macroeconomics is whether
structural vector autoregressions (SVARs) can reliably discriminate
between competing DSGE models. Several recent papers have sug-
gested that one reason SVARs may fail to do so is because they are
finite-order approximations to infinite-order processes. In this context,
we investigate the performance of models that do not suffer from this
type of misspecification. We estimate VARMA and state space models
using simulated data from a standard economic model and compare
true with estimated impulse responses. For our examples, we find that
one cannot gain much by using algorithms based on a VARMA rep-
resentation. However, algorithms that are based on the state space
representation do outperform VARs. Unfortunately, these alternative
estimates remain heavily biased and very imprecise. The findings of
this paper suggest that the reason SVARs perform weakly in these
types of simulation studies is not because they are simple finite-order
approximations. Given the properties of the generated data, their fail-
ure seems almost entirely due to the use of small samples.
Cadmus permanent link: https://hdl.handle.net/1814/6450
ISSN: 1725-6704
Series/Number: EUI ECO; 2006/37
Publisher: European University Institute
Keyword(s): E32 C15 C52 Structural VARs VARMA State space models Identification Business cycles