Testing for a unit root in autoregressive moving-average models with missing data

Dong Wan Shin, Sahadeb Sarkar

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Testing for a single autoregressive unit root in an autoregressive moving-average (ARMA) model is considered in the case when data contain missing values. The proposed test statistics are based on an ordinary least squares type estimator of the unit root parameter which is a simple approximation of the one-step Newton-Raphson estimator. The limiting distributions of the test statistics are the same as those of the regression statistics in AR(1) models tabulated by Dickey and Fuller (Distribution of the estimators for autoregressive time series with a unit root. J. Am. Stat. Assoc. 74 (1979), 427-31) for the complete data situation. The tests accommodate models with a fitted intercept and a fitted time trend.

Original languageEnglish
Pages (from-to)601-608
Number of pages8
JournalJournal of Time Series Analysis
Volume19
Issue number5
DOIs
StatePublished - Sep 1998

Keywords

  • Autoregressive moving average
  • Maximum likelihood estimation
  • Missing
  • Time series
  • Unit root

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