A Practitioner's Guide and MATLAB Toolbox for Mixed Frequency State Space Models

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 MATLAB toolbox can make the estimation and post-processing of these models straightforward.

Keywords

• mixed frequency
• state space
• Kalman filter
• maximum likelihod
• MATLAB