dc.contributor.author | Miller, J. Isaac | eng |
dc.date.issued | 2009 | eng |
dc.description.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 variance-based 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. | eng |
dc.identifier.citation | Department of Economics, 2009 | eng |
dc.identifier.uri | http://hdl.handle.net/10355/2541 | eng |
dc.publisher | Department of Economics | eng |
dc.relation.ispartof | Economics publications | eng |
dc.relation.ispartofcommunity | University of Missouri-Columbia. College of Arts and Sciences. Department of Economics | eng |
dc.relation.ispartofseries | Working papers (Department of Economics);WP 07-22 | eng |
dc.rights | OpenAccess. | eng |
dc.rights.license | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License. | |
dc.source.uri | http://economics.missouri.edu/working-papers/2007/wp0722_zmiller.pdf | eng |
dc.subject | messy data | eng |
dc.subject | missing data | eng |
dc.subject.lcsh | Cointegration | eng |
dc.subject.lcsh | Regression analysis -- Asymptotic theory | eng |
dc.title | Cointegrating Regressions with Messy Regressors: Missingness, Mixed Frequency, and Measurement Error | eng |
dc.type | Working Paper | eng |