Working Papers, School of Business, Örebro University
Robust critical values for unit root tests for series with conditional heteroscedasticity errors: An application of the simple NoVaS transformation
Abstract: In this paper, we introduce a set of critical values for
unit root tests that are robust in the presence of conditional
heteroscedasticity errors using the normalizing and variance-stabilizing
transformation (NoVaS) in Politis (2007) and examine their properties using
Monte Carlo methods. In terms of the size of the test, our analysis reveals
that unit root tests with NoVaS-modified critical values have actual sizes
close to the nominal size. For the power of the test, we find that unit
root tests with NoVaS-modified critical values either have the same power
as, or slightly better than, tests using conventional Dickey–Fuller
critical values across the sample range considered.
Keywords: Critical values; normalizing and variance-stabilizing transformation; unit root tests; (follow links to similar papers)
JEL-Codes: C01; C12; C15; (follow links to similar papers)
24 pages, February 2, 2012
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