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The limiting distribution for M-estimates in a non-stationary autoregressivemodel with heavy-tailed error is computationally intractable. To makeinferences based on the M-estimates, the bootstrap procedure can be used toapproximate the sampling distribution. In this paper, we show that thebootstrap scheme with $m=o(n)$ resampling sample size when $m/n \to 0$ isapproximately valid in a multiple unit roots time series with innovations inthe domain of attraction of a stable law with index $0<\alpha\leq2$.

A Note on Bootstrapping M-estimates from Unstable AR(2) Process with Infinite Variance Innovations