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

DOI10.1016/J.ECONLET.2006.03.040zbMath1254.91653OpenAlexW3126070745MaRDI QIDQ1929441

Michael J. Dueker

Publication date: 8 January 2013

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: http://research.stlouisfed.org/wp/2005/2005-057.pdf

zbMATH Keywords

probit modelKalman filtertruncated normalmacroeconometric models

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Filtering in stochastic control theory (93E11) Economic time series analysis (91B84)

Related Items (2)

Moments of truncated normal/independent distributions ⋮ REGIME-SWITCHED VOLATILITY OF BRENT CRUDE OIL FUTURES WITH MARKOV-SWITCHING ARCH MODEL

Cites Work

• BUSINESS-CYCLE FILTERING OF MACROECONOMIC DATA VIA A LATENT BUSINESS-CYCLE INDEX
• A Smoothed Maximum Score Estimator for the Binary Response Model
• DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
• Partial non-Gaussian state space
• On Gibbs sampling for state space models
• The simulation smoother for time series models
• Bayesian Analysis of Binary and Polychotomous Response Data

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