If right-hand side variables are unavailable or unknown, then a time series method may be more appropriate. Simple time series methods fit the time series to its own past values. More complex time series methods can relate several time series to each other and also include right-hand side variables.
Some questions are still more complex, requiring combinations of regression and time series methods.
These combinations include time series cross-sectional methods and transfer functions. Transfer functions enable you to incorporate the variability of the right-hand side variables into the forecasts of the dependent variable for more realistic forecasts. To fit a transfer function, you fit a time series model to the right-hand side variables in addition to fitting a regression model to the dependent variable. After estimating your model, you may want to test and validate it with individual and joint parameter hypothesis tests. Tests of the residuals may also assist in assessing the acceptability of your model.