I am attempting to model monthly retail electricity sales. To account for both the effects of seasonality and weather, I created an interaction term by multiplying 12 monthly dummy variables by the corresponding month's max temperature, such that:
Jan_dum_temp = Jan_dum * Jan_max_temp, Feb_dum_temp = Feb_dum * Feb_max_temp, . . . Dec_dum_temp = Dec_dum * Dec_max_temp
The resulting model will be:
y(hat) = b1 + b2Jan_dum_temp + b3Feb_dum_temp + ... + b13Dec_dum_temp + other explanatory variables
When adding these interaction terms to the regression, should I leave one interaction term out to avoid the dummy variable trap? If possible, please provide a source for your answer.