Combination of Tests for Cointegration in Cross-Correlated Panels

In this paper, Cheng and Sheng's (2017) combination of 'combinations of P-values' (CCP) is extended to a combination of more than two tests and applied for cointegration testing in cross-correlated panels. In a Monte Carlo experiment, power and size of the different combinations of combinations are investigated. If uncertainty about the panel configuration is taken into account, the results indicate that a multi-test combination can minimize power losses. Furthermore, the usefulness of the combinations studied is illustrated by an application to international interest rate linkage. Cross-sectional dependencies in both the simulation and the empirical studies are accounted for by using the block bootstrap.