Statistical Inference for Independent Component Analysis

Christian Gourieroux and Alain Monfort

No 2015-03, Working Papers from Center for Research in Economics and Statistics

Abstract: The modelling of error terms in multivariate dynamic models by independent component analysis (ICA) is required for reliable impulse response analysis in macroeconomic applications. Since the introduction of ICA by Comon (1994), a large number of semi-parametric estimation methods have been proposed for "orthogonalizing" the error terms. These methods can be pseudo-maximum likelihood (PML) approaches, recursive PML, or moment methods. However several of these approaches are not consistent, and the other ones can be signi cantly sube cient. The aim of our paper is to derive the asymptotic properties of the PML approaches, in particular to study their consistency (or lack of consistency). Moreover we introduce covariance estimators and explain how to improve their e ciency. Finally we discuss the empirical likelihood approach.

Keywords: Independent Component Analysis; Pseudo-Maximum Likelihood; Method of Moments; Empirical Likelihood; Identi cation; Cayley Transform. (search for similar items in EconPapers)
Pages: 59
Date: 2015-06
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