Cointegrating Regressions with Messy Regressors: Missingness, Mixed Frequency, and Measurement Error

J. Miller

No 722, Working Papers from Department of Economics, University of Missouri

Abstract: We consider a cointegrating regression in which the integrated regressors are messy in the sense that they contain data that may be mismeasured, missing, observed at mixed frequencies, or have other irregularities that cause the econometrician to observe them with mildly nonstationary noise. Least squares estimation of the cointegrating vector is consistent. Existing prototypical variancebased estimation techniques, such as canonical cointegrating regression (CCR), are both consistent and asymptotically mixed normal. This result is robust to weakly dependent but possibly nonstationary disturbances.

Keywords: cointegration; canonical cointegrating regression; near-epoch dependence; messy data; missing data; mixed-frequency data; measurement error; interpolation (search for similar items in EconPapers)
JEL-codes: C13 C14 C32 (search for similar items in EconPapers)
Pages: 30 pgs.
Date: 2007-11-27, Revised 2009-04-15
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published as "Cointegrating Regressions with Messy Regressors and an Application to Mixed-frequency Series" in Journal of Time Series Analysis 2010

Downloads: (external link)
https://drive.google.com/file/d/1STT29yfRsiZ2H4plM ... hwp/view?usp=sharing (application/pdf)

Related works:
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:umc:wpaper:0722

Access Statistics for this paper

More papers in Working Papers from Department of Economics, University of Missouri Contact information at EDIRC.
Bibliographic data for series maintained by Chao Gu ().