Wild bootstrap testing for cointegration in an ESTAR error correction model

This paper proposes a bootstrap cointegration test in an exponential smooth transition autoregressive (ESTAR) error correction model (ECM). We introduce the t-type test that has a null hypothesis of no cointegration and an alternative hypothesis of the ESTAR-ECM and develop the test using a wild bootstrap. Monte Carlo simulation results show that the t-type test and conventional tests considerably overreject the null hypothesis of no cointegration in the presence of multivariate GARCH errors and multivariate stochastic volatility, whereas the proposed wild bootstrap test has correct empirical sizes, in contrast to other tests, and reasonable powers under cointegration with the ESTAR-ECM.