Editor:
Universidad Carlos III de Madrid. Departamento de Economía
Issued date:
2019-05-19
ISSN:
2340-5031
xmlui.dri2xhtml.METS-1.0.item-contributor-funder:
Comunidad de Madrid Ministerio de Economía y Competitividad (España)
Sponsor:
Blazsek and Licht acknowledge funding from Universidad Francisco Marroquín. Escribano acknowledges funding from Ministerio de Economía, Industria y Competitividad (ECO2016-00105-001 and MDM 2014-0431) and Comunidad de Madrid (MadEco-CM S2015/HUM-3444).
Serie/No.:
Working paper. Economics 19-08
Project:
Gobierno de España. ECO2015-65599-P Gobierno de España. MDM 2014-0431 Comunidad de Madrid. S2015/HUM-3444/MadEco-CM
Keywords:
Multivariate Dynamic Conditional Score (Dcs) Models
,
Robustness To Outliers
,
Cointegration
,
Common Trends
,
Quasi-Vector Autoregressive Moving Average (Qvarma) Model
Rights:
Atribución-NoComercial-SinDerivadas 3.0 España
Abstract:
Co-integration and common trends are studied for time series variables, by introducing the new t-QVARMA (quasi-vector autoregressive moving average) model. t-QVARMA is an
outlier-robust nonlinear score-driven model for the multivariate t-distribution. In t-QVCo-integration and common trends are studied for time series variables, by introducing the new t-QVARMA (quasi-vector autoregressive moving average) model. t-QVARMA is an
outlier-robust nonlinear score-driven model for the multivariate t-distribution. In t-QVARMA,
the I(0) and I(1) components of the variables are separated in a way that is similar to the
Granger-representation of VAR models. The relationship between the co-integrated federal
funds effective rate and United States (US) inflation rate variables is studied for the period of
July 1954 to January 2019. The in-sample statistical and out-of-sample forecasting performances
of t-QVARMA are superior to those of the classical Gaussian-VAR model[+][-]