Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks

In the paper, a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independently of persistence and heteroskedasticity properties, accounting for common determini...

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Bibliographic Details
Published inOpen journal of statistics Vol. 4; no. 4; pp. 292 - 312
Main Author Morana, Claudio
Format Journal Article
LanguageEnglish
Published 01.06.2014
Subjects
Accounting
Cross sections
Mathematical analysis
Mathematical models
Samples
Statistics
Time series
Vectors (mathematics)
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ISSN2161-718X
2161-7198
DOI10.4236/ojs.2014.44030

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Summary:In the paper, a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independently of persistence and heteroskedasticity properties, accounting for common deterministic and stochastic factors. Monte Carlo results strongly support the proposed methodology, validating its use also for relatively small cross-sectional and temporal samples.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:2161-718X
2161-7198
DOI:10.4236/ojs.2014.44030