Frequency domain estimation of cointegrating vectors with mixed frequency and mixed sample data

Marcus Chambers

Journal of Econometrics, 2020, vol. 217, issue 1, 140-160

Abstract: This paper proposes a simple method for exploiting the information contained in mixed frequency and mixed sample data in the estimation of cointegrating vectors. The asymptotic properties of easy-to-compute spectral regression estimators of the cointegrating vectors are derived and these estimators are shown to belong to the class of optimal cointegration estimators. Furthermore, Wald statistics based on these estimators have asymptotic chi-square distributions which enable inferences to be made straightforwardly. Simulation experiments suggest that the spectral regression estimators considered perform well in finite samples and are at least as good as time domain fully modified estimators. The finite sample size and power properties of the spectral regression-based Wald statistic are also found to be good.

Keywords: Mixed frequency data; Mixed sample data; Cointegration; Spectral regression (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Working Paper: Frequency Domain Estimation of Cointegrating Vectors with Mixed Frequency and Mixed Sample Data (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:217:y:2020:i:1:p:140-160

DOI: 10.1016/j.jeconom.2019.10.010

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