Accounting for missing values in score-driven time-varying parameter models

Andre Lucas, Anne Opschoor and Julia Schaumburg

Economics Letters, 2016, vol. 148, issue C, 96-98

Abstract: Two alternative perspectives on dealing with missing data in the context of the score-driven time-varying parameter models of~Creal et al. (2013) and Harvey (2013) lead to precisely the same dynamic transition equations. This ties the score-driven approach theoretically to the Expectation–Maximization framework for dealing with missing values.

Keywords: Generalized autoregressive score models; Missing values; Expectation–Maximization (search for similar items in EconPapers)
JEL-codes: C52 C53 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0165176516303858
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Accounting for Missing Values in Score-Driven Time-Varying Parameter Models (2016)
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:eee:ecolet:v:148:y:2016:i:c:p:96-98

DOI: 10.1016/j.econlet.2016.09.026

Access Statistics for this article

Economics Letters is currently edited by Economics Letters Editorial Office

More articles in Economics Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().