With Scott Brave and David Kelley.
Published in Journal of Statistical Software, 104(10), 2022: 1-40. https://doi.org/10.18637/jss.v104.i10
Abstract: The use of mixed frequency data is now common in many applications, ranging from the analysis of high frequency financial time series to large cross-sections of macroeconomic time series. In this article, we show how state space methods can easily facilitate both estimation and inference in these settings. After presenting a unified treatment of the state space approach to mixed frequency data modeling, we provide a series of applications to demonstrate how our Mixed Frequency State Space (MFSS) MATLAB toolbox can make the estimation and post-processing of these models straightforward.
The most recent version of the working paper is available as a pdf. (37 pages, 772 KB)
For the current version of the toolbox and source files, see Software.