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

    Miller, J. Isaac
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    [PDF] CointegratingRegressionsMessyRegressors.pdf (341.9Kb)
    Date
    2009
    Format
    Working Paper
    Metadata
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    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.
    URI
    http://hdl.handle.net/10355/2541
    Part of
    Working papers (Department of Economics);WP 07-22
    Part of
    Economics publications
    Citation
    Department of Economics, 2009
    Rights
    OpenAccess.
    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
    Collections
    • Economics publications (MU)

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