Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations

"This paper examines the technical efficiency of U.S. Federal reserve check processing offices over 1980-2003. We use new unconditional quantile estimator of efficiency that avoids some drawbacks of other recently proposed estimators. The new estimator is fully non-parametric, robust with respect to outliers, super-consistent, and converges at rate root-n this avoiding the curse of dimensionality that plagues data envelopment analysis (DEA) estimators. Our methods could be used by policymakers to compare inefficiency levels across offices or by managers of individual offices to identify peer offices"--Federal Reserve Bank of St. Louis web site.