SSAS is completely capable of handling forecasting tasks utilizing a variety of different econometric algorithms.

I would STRONGLY urge readers to consult with a professional statistician or economist before undertaking this type of project.

There are a number of different data afflictions that can have serious adverse impacts on the accuracy of an econometric forecasting solution.

Autocorrelated error terms, unit roots, non-linear time series and others that can cause issues when building ARIMA or regression models and result in spurrious relationships. A trained practitioner will know what to look for and, more importantly, how to correct for these conditions. The spurrious relationships that can result from improper econometric data analysis can result in using independent variables that really have no impact on the dependent variable or throwing out independent variables that actually do have a statistically significant relationship but just need a little prep work that a trained econometrician would understand.

When these forecasting tools are used to base critical business decisions that impact people's lives and livelihoods, PLEASE be sure and leave this type of work to the experts.