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Bootstrapping Autoregressive Processes with Possible Unit Roots

Author

Listed:
  • Atsushi Inoue

    (Department of Agricultural and Resource Economics, North Carolina State University, U.S.A.)

  • Lutz Kilian

    (Department of Economics, University of Michigan, U.S.A.)

Abstract
An important question in applied work is how to bootstrap autoregressive processes involving highly persistent time series of unknown order of integration. In this paper, we show that in many cases of interest in applied work the standard bootstrap algorithm for unrestricted autoregressions remains valid for processes with exact unit roots; no pre-tests are required, at least asymptotically, and applied researchers may proceed as in the stationary case. Specifically, we prove the first-order asymptotic validity of bootstrapping any linear combination of the slope parameters in autoregressive models with drift. We also establish the bootstrap validity for the marginal distribution of slope parameters and for most linear combinations of slope parameters in higher-order autoregressions without drift. The latter result is in sharp contrast to the well-known bootstrap invalidity result for the random walk without drift. A simulation study examines the finite-sample accuracy of the bootstrap approximation both for integrated and for near-integrated processes. We find that in many, but not all circumstances, the bootstrap distribution closely approximates the exact finite- sample distribution.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Atsushi Inoue & Lutz Kilian, 2002. "Bootstrapping Autoregressive Processes with Possible Unit Roots," Econometrica, Econometric Society, vol. 70(1), pages 377-391, January.
    • Handle: RePEc:ecm:emetrp:v:70:y:2002:i:1:p:377-391
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    References listed on IDEAS

    as
    1. Faust, Jon, 1996. "Near Observational Equivalence and Theoretical size Problems with Unit Root Tests," Econometric Theory, Cambridge University Press, vol. 12(4), pages 724-731, October.
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