Infinite-dimensional VARs and factor models
This paper proposes a novel approach for dealing with the 'curse of dimensionality' in the case of infinite-dimensional vector autoregressive (IVAR) models. It is assumed that each unit or variable in the IVAR is related to a small number of neighbors and a large number of non-neighbors. The neighborhood effects are fixed and do not change with the number of units (N), but the coefficients of non-neighboring units are restricted to vanish in the limit as N tends to infinity. Problems of estimation and inference in a stationary IVAR model with an unknown number of unobserved common factors are investigated. A cross-section augmented least-squares (CALS) estimator is proposed and its asymptotic distribution is derived. Satisfactory small-sample properties are documented by Monte Carlo experiments. An empirical illustration shows the statistical significance of dynamic spillover effects in modeling of US real house prices across the neighboring states.
Year of publication: |
2011
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Authors: | Chudik, Alexander ; Pesaran, M. Hashem |
Published in: |
Journal of Econometrics. - Elsevier, ISSN 0304-4076. - Vol. 163.2011, 1, p. 4-22
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Publisher: |
Elsevier |
Keywords: | Large N and T panels Weak and strong cross-section dependence VARs Spatial models Factor models |
Saved in:
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