Forecasting is a very interesting topic for economists. There are many techniques, but basically the key is to compare your forecast against a base model, which could be validation data (test data), a naïve model (really basic estimation) or a more complex model.
Forecasters tend to use the Root Mean Squared Error (RMSE) or Mean Absolute Percent Error (MAPE) statistics to compare models, but there are also others like the Akaike Information Criterion (AIC), Bayesian Information Criterio (BIC), etc. You can google them out easily.
Finally, in the case of VAR model, an actual forecast of the data is not the most useful tool, but the Impulse Response Function (IRF) which is basically a simulation of what could happen (response) to a variable if another changes due to a shock (impulse). This response is dynamic (not constant) over time, to the difference of the typical regression coefficients.