A unified framework to derive the distribution of conventional statistics under a unit root is presented. It is based on formulae which can generate (analytically as well as numerically) the densities and distributions of statistics such as the t ratio, the normalized autocorrelation...

It is shown that the bias of estimated parameters in autoregressive models can increase as the sample size grows. This bias is also a nonmonotonic function of the largest autoregressive root, contrary to what asymptotic approximations had indicated so far in the literature. These unusual results...

When testing for cointegration, the asymptotic inference typically in use can be plagued by size distortion due to an inadequate first order approximation. Hence, for practical purposes the inference can be completely misleading and result in false conclusions regarding the presence of long-run...

A new test for invertibility of moving average processes is proposed. The test is based on an explicit local approximation of the likelihood ratio. A simulation study compares the power with two previously suggested tests: a score type test and a numerical likelihood ratio test. Local to the...

We propose a nonlinear heterogeneous panel unit root test for testing the null hypothesis of unit-roots processes against the alternative that allows a proportion of units to be generated by globally stationary ESTAR processes and a remaining non-zero proportion to be generated by unit root...