 Sensitivity bounds for use with flawed dataDenzil Fiebig and Pierre-Francois Uldry Mathematics and Computers in Simulation (MATCOM), 1999, vol. 48, issue 4, 479-486 Abstract: Data do not adhere to the usual statistical assumptions and applied work is made difficult by the need to cope with the myriad of problems that arise from flawed data. Prominent examples are data that contain missing values or where variables are only available in categorised form. Standard solutions include omitting incomplete records and replacing missing or categorised observations by some representative values. In these and other cases of flawed data, there is some information available on the potential range into which any particular observation could feasibly fall. We contend that there is considerable diagnostic value in exploiting this information to compute bounds for the coefficient estimates and related statistics such as t-ratios. While one of the standard solutions may ultimately be used to produce a set of estimates, the bounds provide an indication of how sensitive these results are to the particular solution chosen. This approach is developed and illustrated by way of several examples. Keywords: Sensitivity bound; Flawed data; Diagnostic (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:48:y:1999:i:4:p:479-486 Access Statistics for this article Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.