Seasonal quasi-vector autoregressive models for macroeconomic data

Blazsek, Szabolcs; Escribano, Álvaro; Licht, Adrian

Seasonal quasi-vector autoregressive models for macroeconomic data

Author(s): Blazsek, Szabolcs; Escribano, Álvaro; Licht, Adrian

Editor: Universidad Carlos III de Madrid. Departamento de Economía

Issued date: 2018-02-15

ISSN: 2340-5031

Sponsor: We are thankful to Luc Bauwens, Matthew Copley, Eric Ghysels, Joachim Grammig, Andrew Harvey, Eric Renault, Genaro Sucarrat and GESG seminar participants at Universidad Francisco Marroquín (December 7, 2017) for all help, comments and suggestions. Szabolcs Blazsek and Adrian Licht acknowledge funding from Universidad Francisco Marroquín. Alvaro 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.: UC3M Working papers Economics
18-03

Project: Comunidad de Madrid. S2015/HUM-3444/MADECO-CM
Gobierno de España. ECO2016-00105-001
Gobierno de España. MDM 2014-0431

Keywords: Dynamic conditional score (DCS) models , Score-driven stochastic seasonality , Nonlinear multivariate dynamic location models , Basic structural model , Vector autoregressive (VAR) model , Vector autoregressive moving average (VARMA) model , Crude oil production

JEL Classification: C32 , C52

URI: http://hdl.handle.net/10016/26316

Rights: Atribución-NoComercial-SinDerivadas 3.0 España

Abstract:

We introduce the Seasonal-QVAR (quasi-vector autoregressive) model for world crude oil production and global real economic activity that identifies the hidden seasonality not found in linear VAR and VARMA models. World crude oil production has an annual season [+]

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