Computing the mean square error of unobserved components extracted by misspecified time series models

DOI10.1016/j.jedc.2008.05.007zbMath1167.93403OpenAlexW2018545384MaRDI QIDQ2271628

Davide Delle Monache, Andrew C. Harvey

Publication date: 7 August 2009

Published in: Journal of Economic Dynamics \& Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jedc.2008.05.007

zbMATH Keywords

smootherKalman filterHodrick-Prescott filterexponentially weighted moving averagedetrending

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Filtering in stochastic control theory (93E11) Economic time series analysis (91B84) Time series analysis of dynamical systems (37M10)

Related Items (2)

Ignoring cross-correlated idiosyncratic components when extracting factors in dynamic factor models ⋮ Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters

Uses Software

• Ox
• SsfPack
• STAMP

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Signal extraction from nonstationary time series
• Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter
• SMOOTHING WITH AN UNKNOWN INITIAL CONDITION
• Robustness of maximum likelihood estimates for multi-step predictions: The exponential smoothing case
• Exact Initial Kalman Filtering and Smoothing for Nonstationary Time Series Models

This page was built for publication: Computing the mean square error of unobserved components extracted by misspecified time series models