We examine the conditions under which each individual series that is generated by a vector autoregressive model can be represented as an autoregressive model that is augmented with the lags of a few linear combinations of all the variables in the system. We call this multivariate index-augmented autoregression (MIAAR) modelling. We show that the parameters of the MIAAR can be estimated by a switching algorithm that increases the Gaussian likelihood at each iteration. Since maximum likelihood estimation may perform poorly when the number of parameters increases, we propose a regularized version of our algorithm for handling a medium–large number of time series. We illustrate the usefulness of the MIAAR modelling by both empirical applications and simulations.

Cubadda, G., Guardabascio, B. (2019). Representation, estimation and forecasting of the multivariate index-augmented autoregressive model. INTERNATIONAL JOURNAL OF FORECASTING, 35(1), 67-79 [10.1016/j.ijforecast.2018.08.002].

Representation, estimation and forecasting of the multivariate index-augmented autoregressive model

Cubadda, Gianluca
;
2019-01-01

Abstract

We examine the conditions under which each individual series that is generated by a vector autoregressive model can be represented as an autoregressive model that is augmented with the lags of a few linear combinations of all the variables in the system. We call this multivariate index-augmented autoregression (MIAAR) modelling. We show that the parameters of the MIAAR can be estimated by a switching algorithm that increases the Gaussian likelihood at each iteration. Since maximum likelihood estimation may perform poorly when the number of parameters increases, we propose a regularized version of our algorithm for handling a medium–large number of time series. We illustrate the usefulness of the MIAAR modelling by both empirical applications and simulations.
2019
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore SECS-S/03 - STATISTICA ECONOMICA
English
Con Impact Factor ISI
Cubadda, G., Guardabascio, B. (2019). Representation, estimation and forecasting of the multivariate index-augmented autoregressive model. INTERNATIONAL JOURNAL OF FORECASTING, 35(1), 67-79 [10.1016/j.ijforecast.2018.08.002].
Cubadda, G; Guardabascio, B
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/214539
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