An investigation of the sensitivity of DEA to data errors

The predictive value of a common measure of efficiency and the robustness o f the data envelopment analysis (DEA) technique is examined when statistica l noise is present in the data. Inferences are drawn from a hypothetical ex ample regarding the potential limitations of the efficiency measure and pit falls in both the single- and multistage applications of DEA. We propose a simple procedure to investigate the robustness of DEA results. The procedur e maintains the relative computational simplicity of DEA and is easy to app ly and interpret. Using this procedure, we examine the robustness of the re sults reported in two published DEA studies and find that, indeed, pitfalls occur in practical applications. We conclude with recommendations for rese archers applying the technique and implications for managers. (C) 2001 Else vier Science Ltd. All rights reserved.