%0 Journal Article
%T Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks
%A Claudio Morana
%J Open Journal of Statistics
%P 292-312
%@ 2161-7198
%D 2014
%I Scientific Research Publishing
%R 10.4236/ojs.2014.44030
%X <p style=\"text-align:justify;\">
	<span style=\"font-size:10pt;font-family:Verdana;\">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.</span> 
</p>
%K Long and Short Memory
%K Structural Breaks
%K Common Factors
%K Principal Components Analysis
%K Fractionally Integrated Heteroskedastic Factor Vector Autoregressive Model
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=47087