Markov-switching dynamic factor models in real time

Pérez-Quirós, Gabriel, Pilar Poncela and Maximo Camacho
Authors registered in the RePEc Author Service: Gabriel Perez Quiros

No 8866, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: We extend the Markov-switching dynamic factor model to account for some of the specificities of the day-to-day monitoring of economic developments from macroeconomic indicators, such as ragged edges and mixed frequencies. We examine the theoretical benefits of this extension and corroborate the results through several MonteCarlo simulations. Finally, we assess its empirical reliability to compute real-time inferences of the US business cycle.

Keywords: Business cycles; Output growth; Time series (search for similar items in EconPapers)
JEL-codes: C22 E27 E32 (search for similar items in EconPapers)
Date: 2012-02
New Economics Papers: this item is included in nep-bec, nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (27)

Downloads: (external link)
https://cepr.org/publications/DP8866 (application/pdf)
CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org

Related works:
Journal Article: Markov-switching dynamic factor models in real time (2018)
Working Paper: Markov-switching dynamic factor models in real time (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:8866

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP8866

Access Statistics for this paper

More papers in CEPR Discussion Papers from C.E.P.R. Discussion Papers Centre for Economic Policy Research, 33 Great Sutton Street, London EC1V 0DX.
Bibliographic data for series maintained by ().