Markov‐switching three‐pass regression filter / by Pierre Guérin, Danilo Leiva‐Leon and Massimiliano Marcellino. : FB3-5/2017-13E-PDF

“We introduce a new approach for the estimation of high-dimensional factor models with regime-switching factor loadings by extending the linear three-pass regression filter to settings where parameters can vary according to Markov processes. The new method, denoted as Markov-switching three-pass regression filter (MS-3PRF), is suitable for datasets with large cross-sectional dimensions, since estimation and inference are straightforward, as opposed to existing regime-switching factor models where computational complexity limits applicability to few variables. In a Monte Carlo experiment, we study the finite sample properties of the MS-3PRF and find that it performs favourably compared with alternative modelling approaches whenever there isstructural instability in factor loadings. For empirical applications, we consider forecasting economic activity and bilateral exchange rates, finding that the MS-3PRF approach is competitive in both cases"--Abstract, p. ii.

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Renseignements sur la publication
Ministère/Organisme Bank of Canada.
Titre Markov‐switching three‐pass regression filter / by Pierre Guérin, Danilo Leiva‐Leon and Massimiliano Marcellino.
Titre de la série Bank of Canada staff working paper, 1701-9397 ; 2017-13
Type de publication Série - Voir l'enregistrement principal
Langue [Anglais]
Format Électronique
Document électronique
Note(s) "April 2017."
Includes bibliographical references (p. 23-26).
Includes abstract in French.
Information sur la publication [Ottawa] : Bank of Canada, 2017.
Auteur / Contributeur Guérin, Pierre,1984-
Marcellino, Massimiliano.
Leiva-Leon, Danilo.
Description ii, 38 p. : col. charts
Numéro de catalogue
  • FB3-5/2017-13E-PDF
Descripteurs Economic forecasting
Statistical analysis
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