TESTING FOR AND DATING COMMON BREAKS IN MULTIVARIATE TIME-SERIES

This paper develops methods for constructing asymptotically valid conf idence intervals for the date of a single break in multivariate time s eries, including I(0), I(1), and deterministically trending regressors . Although the width of the asymptotic confidence interval does not de crease as the sample size increases, it is inversely related to the nu mber of series which have a common break date, so there are substantia l gains to multivariate inference about break dates. These methods are applied to two empirical examples: the mean growth rate of output in three European countries, and the mean growth rate of U.S. consumption , investment, and output.