I am provided with 3 years worth of Sales data (broken down by month) along with data for multiple potential independent variables like Ad Spend (broken down by TV and Digital), Population Increase, Consumer purchase index. I am required to a) Forecast Sales data and B) find the effect of these dependent variables on Sales and what is the optimal mix of Ad spend (TV vs Digital) for Sales.
I wish to run an equivalent of multiple linear regression in Python but for Time Series data. All the examples that I have read for Time Series focus on 1 independent variable. How can I incorporate multiple independent variables into a linear regression model for Time Series ? What other models can I use for this analysis ?
Note: Sales Data is non stationary and has seasonality.