Can you recursively forecast one variable using two variables?
If it is possible to have actual values of the other variables for example let’s say variable $y$ is always provided by statistical bureau with 5 year lag but for second variable $x$ the values are always up to date you can use them.

However, if you have data for both $y$ and $x$ up to date and you want to make forecasts for next year and further in the future you will have to do auxiliary forecasts for $x$ as well.

When you are doing some out of sample evaluation and you want to make a thought experiment of how the model forecasts $y$ conditional on knowing what was the $x$ then you can do that, but such evaluation won’t be indicative of actual performance when in real life both future $y$ and $x$ is unknown. This is the biggest downside of multivariate forecasting. 

However, you can always make an auxiliary forecast for the $x$. Let’s say with an auxiliary AR model for the $x$ variable.