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Title:Multivariate methods for monitoring structural change PDF Logo
Authors:Groen, Jan J. J.
Kapetanios, George
Price, Simon
Issue Date:2010
Series/Report no.:Working Paper // School of Economics and Finance, Queen Mary, University of London 658
Abstract:Detection of structural change is a critical empirical activity, but continuous 'monitoring' of series, for structural changes in real time, raises well-known econometric issues that have been explored in a single series context. If multiple series co-break then it is possible that simultaneous examination of a set of series helps identify changes with higher probability or more rapidly than when series are examined on a case-by-case basis. Some asymptotic theory is developed for maximum and average CUSUM detection tests. Monte Carlo experiments suggest that these both provide an improvement in detection relative to a univariate detector over a wide range of experimental parameters, given a sufficiently large number of co-breaking series. This is robust to a cross-sectional correlation in the errors (a factor structure) and heterogeneity in the break dates. We apply the test to a panel of UK price indices.
Subjects:monitoring
structural change
panel
CUSUM
fluctuation test
JEL:C10
C59
Document Type:Working Paper
Appears in Collections:Working Paper Series, School of Economics and Finance, Queen Mary, University of London

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