When a model has more parameters, it will fit the model better. Therefore, it is required to balance how good you fit the data with a variety of models.
It is common statistical practice that likelihood functions are used in the comparison of models for the same data. However, I do not recommend to use the loglikelihoods in your model comparison.
There have been several proposals to address this issue.
1. EViews also provides the Akaike Information Criterion (AIC) or Schwarz Criterion (or BIC). The best model usually displays the lowest AIC/BIC.
2. The BMA addin provides the most likely models as well as the averaged quantities of interest over all possible models.