Theories can be produced by individuals seeking a good reputation of knowledge. Hence, a significant question is how to test theories anticipating that they might have been produced by (potentially uninformed) experts who prefer their theories not to be rejected. If a theory that predicts exactly like the data generating process is not rejected with high probability then the test is said to not reject the truth. On the other hand, if a false expert, with no knowledge over the data generating process, can strategically select theories that will not be rejected then the test can be ignorantly passed. These tests have limited use because they cannot feasibly dismiss completely uninformed experts. Many tests proposed in the literature (e.g., calibration tests) can be ignorantly passed. Dekel and Feinberg (2006) introduced a class of tests that seemingly have some power of dismissing uninformed experts. We show that some tests from their class can also be ignorantly passed. One of those tests, however, does not reject the truth and cannot be ignorantly passed. Thus, this empirical test can dismiss false experts.We also show that a false reputation of knowledge can be strategically sustained for an arbitrary, but given, number of periods, no matted which test is used (provided that it does not reject the truth). However, false experts can be discredited, even with bounded data sets, if the domain of permissible theories is mildly restricted.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
file. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by Northwestern University, Center for Mathematical Studies in Economics and Management Science in its series Discussion Papers with number
1425.
Length: Date of creation: Mar 2006 Date of revision: Handle: RePEc:nwu:cmsems:1425
Contact details of provider: Postal: Center for Mathematical Studies in Economics and Management Science, Northwestern University, 580 Jacobs Center, 2001 Sheridan Road, Evanston, IL 60208-2014 Phone: 847/491-3527 Fax: 847/491-2530 Email: Web page: http://www.kellogg.northwestern.edu/research/math/ More information through EDIRC
Order Information: Email:
For technical questions regarding this item, or to correct its listing, contact: (Fran Walker).
Related research
Keywords:
This paper has been announced in the following NEP Reports:
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Ehud Kalai, 1995.
"Calibrated Forecasting and Merging,"
Discussion Papers
1144, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
[Downloadable!]
Other versions:
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)