Kalman filtering with truncated normal state variables for Bayesian estimation of macroeconomic models

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

MoreLess

Year of publication:	2006
Authors:	Dueker, Michael
Institutions:	Federal Reserve Bank of St. Louis
Subject:	Macroeconomics \| Econometric models

More details

Extent:	application/pdf
Series:	Working Papers.
Type of publication:	Book / Working Paper
Language:	English
Notes:	Number 2005-057
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005707653