Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/38982
Authors: 
Pesaran, Mohammad Hashem
Chudik, Alexander
Year of Publication: 
2010
Series/Report no.: 
CESifo working paper Empirical and Theoretical Methods 3055
Abstract: 
This paper extends the analysis of infinite dimensional vector autoregressive models (IVAR) proposed in Chudik and Pesaran (2010) to the case where one of the variables or the cross section units in the IVAR model is dominant or pervasive. This extension is not straightforward and involves several technical difficulties. The dominant unit influences the rest of the variables in the IVAR model both directly and indirectly, and its effects do not vanish even as the dimension of the model (N) tends to infinity. The dominant unit acts as a dynamic factor in the regressions of the non-dominant units and yields an infinite order distributed lag relationship between the two types of units. Despite this it is shown that the effects of the dominant unit as well as those of the neighborhood units can be consistently estimated by running augmented least squares regressions that include distributed lag functions of the dominant unit. The asymptotic distribution of the estimators is derived and their small sample properties investigated by means of Monte Carlo experiments.
Subjects: 
IVAR models
dominant units
large panels
weak and strong cross section dependence
factor models
JEL: 
C10
C33
C51
Document Type: 
Working Paper

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