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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| Department/Agency | Bank of Canada. |
|---|---|
| Title | Markov‐switching three‐pass regression filter / by Pierre Guérin, Danilo Leiva‐Leon and Massimiliano Marcellino. |
| Series title | Bank of Canada staff working paper, 1701-9397 ; 2017-13 |
| Publication type | Series - View Master Record |
| Language | [English] |
| Format | Electronic |
| Electronic document | |
| Note(s) | "April 2017." Includes bibliographical references (p. 23-26). Includes abstract in French. |
| Publishing information | [Ottawa] : Bank of Canada, 2017. |
| Author / Contributor | Guérin, Pierre,1984- Marcellino, Massimiliano. Leiva-Leon, Danilo. |
| Description | ii, 38 p. : col. charts |
| Catalogue number |
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| Subject terms | Economic forecasting Statistical analysis |