We consider the bootstrap unit root tests based on finite order autoregressive integrated models driven by iid innovations, with or without deterministic time trends. A general methodology is developed to approximate asymptotic distributions for the models driven by integrated time series, and used to obtain asymptotic expansions for the Dickey-Fuller unit root tests. The second-order terms in their expansions are of stochastic orders Op(n-1/4) and Op(n-1/2), and involve functionals of Brownian motions and normal random variates. The asymptotic expansions for the bootstrap tests are also derived and compared with those of the Dickey-Fuller tests. We show in particular that the bootstrap offers asymptotic refinements for the Dickey-Fuller tests, i.e., it corrects their second-order errors. More precisely, it is shown that the critical values obtained by the bootstrap resampling are correct up to the second-order terms, and the errors in rejection probabilities are of order o(n-1/2) if the tests are based upon the bootstrap critical values. Through simulations, we investigate how effective is the bootstrap correction in small samples.
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Paper provided by Rice University, Department of Economics in its series Working Papers with number
2003-04.
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Evans, G B A & Savin, N E, 1984.
"Testing for Unit Roots: 2,"
Econometrica,
Econometric Society, vol. 52(5), pages 1241-69, September.
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Evans, G B A & Savin, N E, 1981.
"Testing for Unit Roots: 1,"
Econometrica,
Econometric Society, vol. 49(3), pages 753-79, May.
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