This paper proposes nonparametric tests of change in the distribution function of a time series. The limiting null distributions of the test statistics depend on a nuisance parameter, and critical values cannot be tabulated a priori. To circumvent this problem, a new simulation-based statistical method is developed. The validity of our simulation procedure is established in terms of size, local power, and test consistency. The finite-sample properties of the proposed tests are evaluated in a set of Monte Carlo experiments, and the distributional stability in financial markets is examined.
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Article provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 17 (2001) Issue (Month): 01 (February) Pages: 156-187 Download reference. The following formats are available: HTML
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