Accounting for missing values in score-driven time-varying parameter models
Andre Lucas (),
Anne Opschoor and
Economics Letters, 2016, vol. 148, issue C, 96-98
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: C53 C52 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
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)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:148:y:2016:i:c:p:96-98
Access Statistics for this article
Economics Letters is currently edited by Economics Letters Editorial Office
More articles in Economics Letters from Elsevier
Series data maintained by Dana Niculescu ().