This paper proposes consistency conditions for frontier efficiency measures to be useful for regulatory analysis. The efficiency estimates should be consistent in their efficiency levels, rankings, and identification of best and worst firms, consistent over time and with competitive conditions in the market, and consistent with standard nonfrontier measures of performance. The authors evaluate and compare efficiency estimates from four major approaches—Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA), Thick Frontier Analysis (TFA), and Distribution-Free Analysis (DFA)—on U.S. bank efficiency. They find mixed results, indicating that while some approaches are consistent with each other and with standard performance measures, others are not. The authors argue that it is not necessary to have a consensus on the best frontier approach for efficiency measurement, but rather that efficiency measures should meet certain consistency conditions to be useful for regulatory analysis. These conditions include comparable means and standard deviations, similar rankings, identification of similar best and worst firms, stability over time, consistency with market conditions, and consistency with standard nonfrontier performance measures. The authors conclude that while there is some evidence of consistency among the approaches, the results are mixed, and further research is needed to better understand the consistency of frontier efficiency approaches for regulatory analysis.This paper proposes consistency conditions for frontier efficiency measures to be useful for regulatory analysis. The efficiency estimates should be consistent in their efficiency levels, rankings, and identification of best and worst firms, consistent over time and with competitive conditions in the market, and consistent with standard nonfrontier measures of performance. The authors evaluate and compare efficiency estimates from four major approaches—Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA), Thick Frontier Analysis (TFA), and Distribution-Free Analysis (DFA)—on U.S. bank efficiency. They find mixed results, indicating that while some approaches are consistent with each other and with standard performance measures, others are not. The authors argue that it is not necessary to have a consensus on the best frontier approach for efficiency measurement, but rather that efficiency measures should meet certain consistency conditions to be useful for regulatory analysis. These conditions include comparable means and standard deviations, similar rankings, identification of similar best and worst firms, stability over time, consistency with market conditions, and consistency with standard nonfrontier performance measures. The authors conclude that while there is some evidence of consistency among the approaches, the results are mixed, and further research is needed to better understand the consistency of frontier efficiency approaches for regulatory analysis.