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

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  • Peter Burridge
  • Daniela Hristova

Abstract

. 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, α, 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.

Suggested Citation

  • Peter Burridge & Daniela Hristova, 2008. "Consistent estimation and order selection for nonstationary autoregressive processes with stable innovations," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(4), pages 695-718, July.
    • Handle: RePEc:bla:jtsera:v:29:y:2008:i:4:p:695-718
    DOI: 10.1111/j.1467-9892.2008.00579.x
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    Cited by:

    1. Burridge, Peter, 2011. "A research agenda on general-to-specific spatial model search," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 21, pages 71-90.
    2. Antonio Noriega & Carlos Capistrán & Manuel Ramos-Francia, 2013. "On the dynamics of inflation persistence around the world," Empirical Economics, Springer, vol. 44(3), pages 1243-1265, June.

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