1. Try to select a set of "important" explanatory variables.
2. There are very strong linear relationships between the explanatory variables, giving rise to the phenomenon of multicollinearity.
3. Some regression models contain outliers. Remove them and reexamine your model.
4. Since, you are dealing with time ordered data check for the presence of autocorrelation.