The objective of this simulation study is to investigate whether the likelihood ratio (LR) test can pick the optimal lag order in the vector autoregressive model when the most applied information criteria (i.e. vector Schwarz-Bayesian, SBC and vector Hannan-Quinn, HQC) suggest two different lag orders. This lag-choosing procedure has been suggested by Hatemi-J (1999). The results based on the Monte Carlo simulations show that combining the LR test with SBC and HQC causes a substantial increase in the success rate of choosing the optimal lag order compared to cases when only SBC or HQC are used. This appears to be the case irrespective of homoscedasticity or conditional heteroscedasticity properties of the error-term in small sample sizes. This improvement in choosing the right lag order also tends to improve the forecasting capability of the underlying model.