Estimating Models of Program Management

This research effort models decision-making behavior in a dynamic, uncertain environment. We derive consistent estimating procedures that model observed data that results from the decisions. This is accomplished by mating a Bayesian econometric process with a dynamic programming model of contractor behavior. This is used to demonstrate the dramatic increases in precision that can be obtained with just a few observations on program cost. The result of this effort can be used to develop a procedure for using routine data to help manage large programs in much the same way that control charts are routinely used to management production processes today.