Confidence Bands for ROC Curves with Serially Dependent Data
We propose serial correlation robust asymptotic confidence bands for the receiver operating characteristic (ROC) curves estimated by quasi-maximum likelihood in the binormal model. Our simulation experiments confirm that this new method performs fairly well in finite samples. The conventional procedure is found to be markedly undersized in terms of yielding empirical coverage probabilities lower than the nominal level, especially when the serial correlation is strong. We evaluate the three-quarter-ahead probability forecasts for real GDP declines from the Survey of Professional Forecasters, and find that one would draw a misleading conclusion about forecasting skill if serial correlation is ignored.
|Date of creation:||2013|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (518) 442-4735
Fax: (518) 442-4736
|Order Information:|| Postal: Department of Economics, BA 110 University at Albany State University of New York Albany, NY 12222 U.S.A.|
Web: http://www.albany.edu/economics/research/workingp/index.shtml Email:
When requesting a correction, please mention this item's handle: RePEc:nya:albaec:13-07. 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: (John Bailey Jones)
If references are entirely missing, you can add them using this form.