Kalman Filtering with Truncated Normal State Variables for Bayesian Estimation of Macroeconomic Models

FRB of St. Louis Working Paper No. 2005-057B

9 Pages Posted: 9 Nov 2005

See all articles by Michael Dueker

Michael Dueker

Federal Reserve Banks - Federal Reserve Bank of St. Louis

Date Written: March 2006

Abstract

A pair of simple modifications to the Kalman filter recursions makes possible the filtering of models in which one or more state variables is truncated normal. Such recursions are broadly applicable to macroeconometric models that have one or more probit-type equation, such as vector autoregressions and estimated dynamic stochastic general equilibrium models.

Keywords: Kalman Filter, truncated normal, probit model, macroeconometric models

JEL Classification: C32, C35, E37

Suggested Citation

Dueker, Michael, Kalman Filtering with Truncated Normal State Variables for Bayesian Estimation of Macroeconomic Models (March 2006). FRB of St. Louis Working Paper No. 2005-057B, Available at SSRN: https://ssrn.com/abstract=840185 or http://dx.doi.org/10.2139/ssrn.840185

Michael Dueker (Contact Author)

Federal Reserve Banks - Federal Reserve Bank of St. Louis ( email )

411 Locust St
Saint Louis, MO 63011
United States

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