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

37 Pages Posted: 3 Mar 2020

See all articles by Scott A. Brave

Scott A. Brave

Federal Reserve Bank of Chicago

R. Andrew Butters

Indiana University

David Kelley

Federal Reserve Bank of Chicago

Date Written: February 5, 2020

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 likelihood, MATLAB

JEL Classification: C87, C22, C53

Suggested Citation

Brave, Scott A. and Butters, R. and Kelley, David, A Practitioner's Guide and MATLAB Toolbox for Mixed Frequency State Space Models (February 5, 2020). Available at SSRN: https://ssrn.com/abstract=3532455 or http://dx.doi.org/10.2139/ssrn.3532455

Scott A. Brave

Federal Reserve Bank of Chicago ( email )

230 South LaSalle Street
Chicago, IL 60604
United States

R. Butters (Contact Author)

Indiana University ( email )

1309 E. Tenth St.
Bloomington, IN 47405
United States

HOME PAGE: http://https://kelley.iu.edu/BEPP/faculty/page14113.cfm?ID=46947

David Kelley

Federal Reserve Bank of Chicago ( email )

230 South LaSalle Street
Chicago, IL 60604
United States

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