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Title:Infinite dimensional VARs and factor models PDF Logo
Authors:Chudik, Alexander
Pesaran, Mohammad Hashem
Issue Date:2007
Series/Report no.:CESifo working paper 2176
Abstract:This paper introduces a novel approach for dealing with the 'curse of dimensionality' in the case of large linear dynamic systems. Restrictions on the coefficients of an unrestricted VAR are proposed that are binding only in a limit as the number of endogenous variables tends to infinity. It is shown that under such restrictions, an infinite-dimensional VAR (or IVAR) can be arbitrarily well characterized by a large number of finite-dimensional models in the spirit of the global VAR model proposed in Pesaran et al. (JBES, 2004). The paper also considers IVAR models with dominant individual units and shows that this will lead to a dynamic factor model with the dominant unit acting as the factor. The problems of estimation and inference in a stationary IVAR with unknown number of unobserved common factors are also investigated. A cross section augmented least squares estimator is proposed and its asymptotic distribution is derived. Satisfactory small sample properties are documented by Monte Carlo experiments. An empirical application to modelling of real GDP growth and investment-output ratios provides an illustration of the proposed approach. Considerable heterogeneities across countries and significant presence of dominant effects are found. The results also suggest that increase in investment as a share of GDP predict higher growth rate of GDP per capita for non-negligible fraction of countries and vice versa.
Subjects:large N and T panels
weak and strong cross section dependence
VAR
global VAR
factor models
capital accumulation and growth
JEL:C10
C33
C51
O40
Document Type:Working Paper
Appears in Collections:CESifo Working Papers, CESifo Group Munich

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