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Inference about long run canonical correlations
Author(s) -
Dovo Prosper,
Hall Alastair R.,
Jana Kalidas
Publication year - 2012
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2012.00798.x
Subject(s) - mathematics , cointegration , inference , independence (probability theory) , statistical hypothesis testing , null hypothesis
This article proposes methods for testing the null hypothesis that a number of so‐called long run canonical correlations (LRCCs) are zero. Two test statistics are proposed and their limiting distributions are derived under the null hypothesis. The finite sample properties of the tests are illustrated via a number of simulation studies that reveal the asymptotic theory provides a good guidance to behaviour in moderate or large sized samples. It is shown that the statistics provide a natural way for testing the asymptotic independence of two standardized sums. The usefulness of the tests is illustrated via the following examples: inference about cointegrating vector in a particular cointegration model; inference about break points in a cointegration model; moment estimation; parameter estimation in Generalized Method of Moments estimation.