Can you do the wrong thing and still be right? Hypothesis testing in I(2) and near-I(2) cointegrated VARs.

In this paper, we investigate the small-sample performance of LR tests on long-run coefficients in theI(2) model; we focus on a comparison betweenI(2) and near-I(2) data, i.e.I(1) data with a second root very close to unity, and report the results of some Monte Carlo experiments. With near-I(2) data, the finite-sample properties of the tests are (i) similar to those found with genuineI(2) data, (ii) systematically superior to those of the analogous tests constructed in theI(1) model, even if the latter is, in principle, correctly specified and the former is not. Therefore, there seems to be strong support to the idea that, in practice, modelling near-I(2) data using theI(2) model may be a good idea, despite the inherent misspecification. [ABSTRACT FROM AUTHOR]