When multicollinearity is present, removing from the regression one of two or more highly correlated variables does not markedly reduce the proportion of variance in the dependent variable accounted for. Eliminating some of the independent variables, obtaining new data, or utilizing a priori information concerning the coefficients are possible solutions to the problem. The last two methods were judged to be unsatisfactory for this study. Then using all observations, successful and unsuccessful, a measure of the probability of success in generating any jobs is determined. A number of economic development theories suggest variables to include in a model predicting the success of a job-creating development project in a region.
Location theory suggests that industry moves to areas with the greatest profit potential.
Although market incentives may be distorted in depressed areas needing assistance to expand the employment base, firms are expected to respond to profit potential as evident in availability of low-cost inputs, agglomeration economies, adequate transportation, and nearness to large markets. Central place theory, growth center theory, and growth pole theory are related to neoclassical theory but heavily stress agglomeration economies growing out of external and internal economies of scale, availability of business credit, and other supportive public and private services, especially as found in larger cities. But all of the variables are considered to be relevant on theoretical grounds to explain cost-effectiveness. All the theoretically admissible variables were selected and arranged in seven reasonably homogeneous groups for convenience in applying the ad hoc procedure to reduce the number of closely related variables included in the final model. The relative location group is made up of six variables which are the distances to cities of various sizes and to an interstate highway.