A1068
Title: Estimation of VAR systems from mixed-frequency data: The stock and the flow case
Authors: Lukas Koelbl - Vienna University of Technology (Austria) [presenting]
Alexander Braumann - Vienna University of Technology (Austria)
Elisabeth Felsenstein - Vienna University of Technology (Austria)
Manfred Deistler - Vienna University of Technology (Austria)
Abstract: Estimation and properties of estimators of VAR systems are considered in the case of observations with different sampling rates, the so-called mixed-frequency (MF) observations. Only the case where the output variable can be separated into a fast (high-frequency) and a slow (low-frequency) component will be given attention. It is assumed that the underlying system generates the output at each time point, the so-called high grid, however, the output of the slow component is only observed at an integer multiple of the high grid. As mentioned above, the asymptotic behavior of estimators of autoregressive systems is a central theme. The main focus is on estimators that are based on the extended Yule-Walker (XYW) equations as well as on (Gaussian) maximum likelihood type estimators based on the EM algorithm. Two cases for the slow component are considered: the stock and the flow case. In addition, the XYW estimator and the generalized method of moments estimator (GMM) are discussed and it is shown that they are asymptotically normal under certain assumptions. Therefore, a generalization of Bartlett's formula for the mixed-frequency case is required. As shown by examples, the GMM estimator is, in general, not efficient. Finally, the loss of information due to mixed-frequency data when compared to the high-frequency situation as well as the gain of information when using mixed-frequency data relative to low-frequency data is discussed.
