| Article ID: | iaor200971693 |
| Country: | United Kingdom |
| Volume: | 60 |
| Issue: | 12 |
| Start Page Number: | 1767 |
| End Page Number: | 1774 |
| Publication Date: | Dec 2009 |
| Journal: | Journal of the Operational Research Society |
| Authors: | Kuosmanen T |
A first systematic attempt to use data containing missing values in data envelopment analysis (DEA) is presented. It is formally shown that allowing missing values into the data set can only improve estimation of the best-practice frontier. Technically, DEA can automatically exclude the missing data from the analysis if blank data entries are coded by appropriate numerical values.