We propose a new approach based on conditional means and variances to avoid the computational difficulties of the traditional Cox test. This approach can be extended to more complicated time series models. Monte Carlo experiments are performed to investigate the potential applicability of the proposed test. Empirical applications to two different non-linear error equation models are also examined.