Quantitative Techniques in Management - I

Session 25Reading: SfM Ch. 15Quantitative Techniques in Management - ILogistic RegressionNonlinear relationships: Quadratic regressionTransforming Regression ModelsCollinearityModel buildingThere is one dependent variable and many possible independent variablesParsimony dictates that we use the regression model with fewest variables.First, evaluate the VIFs of all independent variables, and eliminate those with high collinearityThen use stepwise regression. First, use partial F-test or t-test to see which model with one independent variable is the best fit.Then, choose a second independent variable (all tests normally at 5% sig.) which shows a positive contribution to the model, and has the largest contribution.Then choose a third, or a fourth, as long as the independent variables pass the test to show a positive contribution to the model.Best-subsets approach to model buildingLook at the data in Session 24.xlsx. Subset-regression shows that the best option is to use all three dependent variables. In Stepwise regression, the first variable to be added is X3, followed by X2, then X1. VIF-analysis shows that removing X1 (CO2 emissions) greatly reduces collinearity.