Testing for A Set of Linear Restrictions in VARMA Models Using Autoregressive Metric: An Application to Granger Causality Test
Francesca Di Iorio and
Umberto Triacca ()
Additional contact information
Umberto Triacca: Department of Computer Engineering, Computer Science and Mathematics, University of L'Aquila, via Vetoio, I-67010 Coppito, L'Aquila, Italy
Econometrics, 2014, vol. 2, issue 4, 1-14
In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M 0 and M 1 , introduced by Piccolo in 1990. In particular, we show that this set of linear restrictions is equivalent to a null distance d (M0,M1 ) between two given ARMA models. This result provides the logical basis for using d ( M 0 ,M 1 ) = 0 as a null hypothesis in our test. Some Monte Carlo evidence about the finite sample behavior of our testing procedure is provided and two empirical examples are presented.
Keywords: VARMA; linear restriction; autoregressive metric; bootstrap (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:gam:jecnmx:v:2:y:2014:i:4:p:203-216:d:43816
Access Statistics for this article
Econometrics is currently edited by Prof. Dr. Kerry Patterson
More articles in Econometrics from MDPI, Open Access Journal
Bibliographic data for series maintained by XML Conversion Team ().