Efficiency Evaluation of Michigan Prisons Using Data Envelopment Analysis

Abstract

The purpose of this study is to demonstrate the utility of data envelopment analysis (DEA) in the evaluation of the administration of justice. The study incorporates a set of inputs and outputs that state and federal agencies as well as prison managers can utilize to assess the relative efficiency of prison operations and to set targets for improvement. DEA is a linear programming technique that constructs a frontier of relatively efficient "decision making units" (DMUs) by optimally allocating weights among the multiple inputs and multiple outputs of the DMUs. DMUs that fall behind that frontier are classified as inefficient. This analysis presents DEA to criminal justice evaluation, demonstrates the general applicability of DEA to prison administration, and serves as a starting point for making comparative evaluations of prisons. An application of DEA to Michigan prisons is used to identify prisons that are inefficient, provide some insight into the source of the inefficiency, and identify potential remedies and target performance levels.