What advantages do the multiple regressive models have over the other techniques? Disadvantages? ...

Multiple regression models incorporate more than one causal or independent variable to predict the movement in the dependent variable. The main advantage of this method is the better coverage of the factors that will cause the dependent variable to change in one direction or

another. The multiple regression method, in general, has the advantage of factoring in change in the external environment such as the economy and pricing conditions. This element is absent from qualitative forecasting and autoregression. Simple regression models (one causal variable) can take external factors into account but only one independent variable is incorporated in the forecasting equation so the coverage is less than in a multiple regression model. The main disadvantage lies in the fact that the process requires much experiment in determining which independent variables to select. This may prove to be a lengthy process, which means that ample resources and time are allotted to the effort.