Nonstationary Time Series and Missing Data

Shin, Dong-Wan;Lee, Oe-Sook

  • Received : 20091200
  • Accepted : 20100100
  • Published : 2010.02.28


Missing values for unit root processes are imputed by the most recent observations. Treating the imputed observations as if they are complete ones, semiparametric unit root tests are extended to missing value situations. Also, an invariance principle for the partial sum process of the imputed observations is established under some mild conditions, which shows that the extended tests have the same limiting null distributions as those based on complete observations. The proposed tests are illustrated by analyzing an unequally spaced real data set.


High frequency data;invariance principle;missing value imputation;semiparametric unit root test


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