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

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. (C) 2020 The Author(s). Published by Elsevier B.V.