A Practitioner's Guide and MATLAB Toolbox for Mixed Frequency State Space Models
37 Pages Posted: 3 Mar 2020
Date Written: February 5, 2020
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 MATLAB toolbox can make the estimation and post-processing of these models straightforward.
Keywords: mixed frequency, state space, Kalman filter, maximum likelihood, MATLAB
JEL Classification: C87, C22, C53
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