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Cointegrating regressions with messy regressors and an application to mixed‐frequency series
Authors:J Isaac Miller
Affiliation:1. University of Missouri;2. E‐mail:
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, 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  mixed‐frequency data  linear interpolation  C13  C14  C32
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