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From the same journal

Consistent estimation and order selection for nonstationary autoregressive processes with stable innovations

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Publication details

JournalJournal of Time Series Analysis
DatePublished - Jul 2008
Issue number4
Number of pages24
Pages (from-to)695-718
Original languageEnglish


A possibly nonstationary autoregressive process, of unknown finite order, with possibly infinite-variance innovations is studied. The ordinary least squares autoregressive parameter estimates are shown to be consistent, and their rate of convergence, which depends on the index of stability, alpha, is established. We also establish consistency of lag-order selection criteria in the nonstationary case. A small experiment illustrates the relative performance of different lag-length selection criteria in finite samples.

    Research areas

  • consistent estimation, infinite-variance innovations, unit-root AR processes, consistent order-selection criteria, INFINITE-VARIANCE, TIME-SERIES, UNIT-ROOT, INFORMATION CRITERION, MOVING AVERAGES, MODEL SELECTION, LIMIT THEORY, REGRESSION

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