Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit

By A. Chudik, M. Pesaran. Social Science Research Network, 2013

178 citations recorded by the source corpus.

This paper extends the analysis of infinite dimensional vector autoregressive (IVAR) models proposed in Chudik and Pesaran (2011) to the case where one of the variables or the cross-section units in the IVAR model is dominant or pervasive. It is an important extension from empirical as well theoretical perspectives. In the theory of networks a dominant unit is the centre node of a star network and arises as an efficient outcome of a distance-based utility model. Empirically, the extension poses a number of technical challenges that goes well beyond the analysis of IVAR models provided in Chudik and Pesaran. This is because the dominant unit influences the rest of the variables in the IVAR model both directly and indirectly, and its effects do not vanish 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 and its neighbors (if any). The asymptotic distribution of the estimators is derived and their small sample properties investigated by means of Monte Carlo experiments.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/bf371727d083465f19c5f810d6c1f98319e3a4ef

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In Economics and Econometrics

Citations in the corpus

Theory and Practice of GVAR Modeling (2016, unknown): “The analysis of DdPS has been further extended by Chudik and Pesaran (2011) and Chudik and Pesaran (2013b) to allow for joint asymptotics (i.e. as N and T →∞, jointly), and weak cross sectional dependence in the errors in the case of stationary variables.”
Quantile Connectedness: Modelling Tail Behaviour in the Topology of Financial Networks (2018, unknown): “…and financial performance (e.g. Dees, di Mauro, Pesaran and Smith, 2007; Chudik and Fratzscher, 2011; Helbling, Huidrom, Kose and Otrok, 2011; Longstaff et al., 2011; Pesaran and Chudik, 2013). available from Ken French via http://mba.tuck.dartmouth.edu/pages/faculty/ken. french/data_library.html.”
Determinants of Global Spillovers from US Monetary Policy (2015, background): “Finally, in order to account for the extraordinary role of the US in the global economy, I treat the US as a dominant unit in the sense of Pesaran and Chudik (2010).7”