Asymptotic theory for linear diffusions under alternative sampling schemes
2015
Zhou, Qiankun | Yu, Jun
The asymptotic distributions of the maximum likelihood estimator of the persistence parameter are developed in a linear diffusion model under three sampling schemes, long-span, in-fill and double. Simulations suggest that the in-fill asymptotic distribution gives a more accurate approximation to the finite sample distribution than the other two distributions. An empirical application highlights the difference in unit root testing based on the alternative asymptotic distributions.
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