Monte Carlo experiments show that the test has good finite-sample size and power properties.
We derive the null distributions, validity of a bootstrap procedure, and local and global power properties of our tests.
Local power properties, one-sided test, and comparison under the generalized empirical likelihood-based measure of fit are also investigated.
Power analyses confirm the generally good power properties of the test design.
We illustrate the size and power properties of the proposed tests through Monte Carlo simulations.
Simulations indicate that tests based on these methods have improved size properties relative to conventional tests and better power properties than other tests that use Bartlett or other traditional kernels with no truncation.
Analysis and simulations indicate that sharp origin kernels lead to tests with improved size properties relative to conventional tests and better power properties than other tests using Bartlett and other conventional kernels without truncation.
In South Korea and elsewhere in Asia, wild ginseng's roots have traditionally been prized for their supposed preternatural healing powers, properties believed to be missing in the farmed variety.
Simulations show that the proposed estimators work well in empirically realistic settings and that the tests have good size and power properties in discriminating characteristics in the data that differ from typical unit root behaviour.
Simulations show that in regression testing with the sharp origin kernel, the power properties are better than those with simple untruncated kernels (where ρ = 1) and at least as good as those with truncated kernels.
According to the power properties, microgrids can be divided into AC and DC microgrids.
