A unifying framework for analysing common cyclical features in cointegrated time series

DOI10.1016/j.csda.2007.07.004zbMath1452.62625OpenAlexW3123710773MaRDI QIDQ1020892

Gianluca Cubadda

Publication date: 2 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2108/10050

zbMATH Keywords

reduced rank regressioncommon features

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (4)

Studying co-movements in large multivariate data prior to multivariate modelling ⋮ Testing for common autocorrelation in data-rich environments ⋮ Modelling comovements of economic time series: a selective survey ⋮ Editorial: 2nd special issue on statistical signal extraction and filtering

Cites Work

• Unnamed Item
• Common cyclical features analysis in VAR models with cointegration
• Common trends and cycles in I(2) VAR systems
• Small-sample improvements in the statistical analysis of seasonally cointegrated systems
• Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK
• Multivariate reduced-rank regression
• Canonical correlation analysis and reduced rank regression in autoregressive models
• Identifying restrictions of linear equations with applications to simultaneous equations and cointegration
• A simple message for autocorrelation correctors: Don't
• Testing For and Dating Common Breaks in Multivariate Time Series
• Co-Integration and Error Correction: Representation, Estimation, and Testing
• On non-contemporaneous short-run co-movements

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