A permutation test (based on a finite random sample of
permutations) for unit root in an autoregressive process is considered.
The test can easily be carried out in practice and the proposed permutation
test is neither limited to large sample sizes nor normal white noises.
Simulations show that the power of the permutation test is reasonable when
sample sizes are small or when the white noises have a heavy tailed
distribution. The test is shown to be consistent.
Cite this paper
Li, J. , Tran, L. and Niwitpong, S. (2013) A Permutation Test for Unit Root in an Autoregressive Model. Applied Mathematics
, 1629-1634. doi: 10.4236/am.2013.412221
 W. A. Fuller, “Introduction to Statistical Times Series,” John Wiley & Sons, New York, 1976.
 D. A. Dickey, “Estimation and Hypothesis Testing in Nonstationary Time Series,” Ph.D. Dissertation, Iowa State University, Ames, 1976.
 N. H. Chan and L. T. Tran, “Nonparametric Tests for Serial Dependence,” Journal of Time Series Analysis, Vol. 13, No. 1, 1992, pp. 19-28.http://dx.doi.org/10.1111/j.1467-9892.1992.tb00092.x
 H. J. Skaug and D. Dad Tjóstheim, “A Nonparametric Test of Serial Independence Based on the Empirical Distribution Function. Consistent Nonparametric Multiple Regression: The Fixed Design Case,” Biometrika, Vol. 3, 1988, pp. 591-602.
 J. P. Gould and C. R. Nelson, “The Stochastic Structure of the Velocity of Money,” The American Economic Review, Vol. 64, No. 3, 1974, pp. 405-417.
 M. Friedman and A. J. Schwartz, “A Monetary History of the United States 1867-1960,” Princeton University Press, Princeton, 1963.