VC - A Method For Estimating Time-Varying Coefficients in Linear Models

Ekkehart Schlicht

Discussion Papers in Economics from University of Munich, Department of Economics

Abstract: This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. A penalized least squares estimation is linked to the GLS (Aitken) estimates of the corresponding linear model with time-invariant parameters. The VC estimator is a moments estimator that does not require the disturbances be Gaussian, but if they are, its estimates are asymptotically equivalent to maximum likelihood estimates. In contrast to Kalman filtering, no specification of an initial state or an initial covariance matrix is required. While the Kalman filter is one- sided, the VC filter is two-sided and uses more of the available information for estimating intermediate states.. Further, the VC filter has a clear descriptive interpretation.

Keywords: Time-series analysis; linear model; state-space estimation; time-varying coefficients; moments estimation; Kalman filtering; penalized least squares. (search for similar items in EconPapers)
JEL-codes: C2 C22 C51 C52 (search for similar items in EconPapers)
Date: 2019-11
New Economics Papers: this item is included in nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://epub.ub.uni-muenchen.de/69765/1/schlicht-VC-v2.6%20long.pdf (application/pdf)

Related works:
Working Paper: VC - A Method For Estimating Time-Varying Coefficients in Linear Models (2020)
Working Paper: VC - A method for estimating time-varying coefficients in linear models (2019)
Working Paper: VC - A Method For Estimating Time-Varying Coefficients in Linear Models (2006)
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:lmu:muenec:69765

Access Statistics for this paper

More papers in Discussion Papers in Economics from University of Munich, Department of Economics Ludwigstr. 28, 80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Tamilla Benkelberg ().