Open Access
Business Cycle Analysis and VARMA Models
Loading...
License
Access Rights
Cadmus Permanent Link
Full-text via DOI
ISBN
ISSN
1725-6704
Issue Date
Type of Publication
LC Subject Heading
Other Topic(s)
EUI Research Cluster(s)
Initial version
Published version
Succeeding version
Preceding version
Published version part
Earlier different version
Initial format
Author(s)
Citation
EUI ECO; 2006/37
Cite
KASCHA, Christian, MERTENS, Karel, Business Cycle Analysis and VARMA Models, EUI ECO, 2006/37 - https://hdl.handle.net/1814/6450
Abstract
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.