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
Date Written: March 2006
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: Suggested Citation