@TechReport{dp-676,
  author      = {Sibbertsen, Philipp and Wenger, Kai and Wingert, Simon},
  astring     = {Philipp Sibbertsen and Kai Wenger and Simon Wingert}, 
  title       = {Testing for Multiple Structural Breaks in Multivariate Long Memory Time Series},
  year        = {2020},
  month       = {November},
  number      = {676},
  pages       = {51},  
  size	      = {686},
  abstract    = {This paper considers estimation and testing of multiple breaks that occur at unknown dates in multivariate long-memory time series. We propose a likelihood ratio based approach for estimating breaks in the mean and the covariance of a system of long-memory time series. The limiting distribution of these estimates as well as consistency of the estimators is derived. A testing procedure to determine the unknown number of break points is given based on iterative testing on the regression residuals. A Monte Carlo exercise shows the finite sample performance of our method. An empirical application to inflation series illustrates the usefulness of our procedures.},
  language    = {en},
  jelclass    = {C12, C22, C58, G15},
  keywords    = {Multivariate Long Memory ; Multiple Structural Breaks ; Hypothesis Testing}
}