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Chan, N.H. and Palma, W. (2006) Estimation of Long-Memory Time Series Models: A Survey of Different Likelihood Based Approaches. In: Fomby, T.H. and Terrel, D., Eds., Econometric Analysis of Economic and Financial Time Series, Advances in Econometrics, Vol. 20, Emerald Group Publishing Limited, Bingley, 89-121.

has been cited by the following article:

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

  AUTHORS: Claudio Morana

  KEYWORDS: Long and Short Memory, Structural Breaks, Common Factors, Principal Components Analysis, Fractionally Integrated Heteroskedastic Factor Vector Autoregressive Model

  JOURNAL NAME: Open Journal of Statistics, Vol.4 No.4, June 20, 2014

  ABSTRACT: 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.