Kalman filtering with truncated normal state variables for Bayesian estimation of macroeconomic models
By: by Michael J. Dueker.
Contributors: Federal Reserve Bank of St. Louis.
Series: Working paper ;; 2005-057A; Working paper (Federal Reserve Bank of St. Louis : Online) ;; 2005-057A.
Publisher: Federal Reserve Bank of St. Louis
Published: 2005
Place of publication: [St. Louis, Mo.]
Language: eng
Format: Electronic resource
Subjects: Kalman filtering.; Econometric models.
Description: "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"--Federal Reserve Bank of St. Louis web site.
Notes: Includes bibliographical references.
Title from PDF file as viewed on 9/27/2005.
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Mode of access: World Wide Web.