Robust non-parametric quantile estimation of efficiency and productivity change in U.S. commercial banking, 1985-2004
This paper describes a non-parametric, unconditional, hyperbolic quantile estimator that unlike traditional non-parametric frontier estimators is both robust to data outliers and has a root-n convergence rate. We use this estimator to examine changes in the efficiency and productivity of U.S. banks between 1985 and 2004. We find that larger banks experienced larger efficiency and productivity gains than small banks, consistent with the presumption that recent changes in regulation and information technology have favored larger banks.
|Date of creation:||2007|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.stlouisfed.org/
More information through EDIRC
|Order Information:|| Email: |
When requesting a correction, please mention this item's handle: RePEc:fip:fedlwp:2006-041. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Anna Xiao)
If references are entirely missing, you can add them using this form.