Abstract
This dissertation deals with a firm level decision making process that involves the acquisition and use of information in a high volume credit scoring environment. A two stage model is developed to describe the choice a decision maker has between alternative levels of information acquisition. The first stage of the model describes the optimal set of credit decisions based upon on a given level of information. The second stage describes the comparison of alternative information choices that leads to the optimal level of information acquisition. The data for this study, 12,000 observations of credit characteristics and performance, were obtained from a factoring firm and a major provider of commercial credit information. Using these data and a logistic regression technique, models are developed to generate default probabilities for four competing sets of explanatory variables. The probabilities are then used in an economic model to determine whether to approve or deny a credit applicant. The results demonstrate the feasibility of valuing competing sets of information. While these results lead to the conclusion that the optimal strategy is to purchase all available information, they are specific to the particular firm in this study. The general information evaluation methodology described here may lead to other conclusions in case studies where different economic assumptions apply.
Edwards, David Michael (1990). Firms' information acquisition decisions in a microeconomic context. Texas A&M University. Texas A&M University. Libraries. Available electronically from
https : / /hdl .handle .net /1969 .1 /DISSERTATIONS -1108884.