Users should refer to the original published version of the material for the full abstract.The widespread use of ‘statistical significance’ as a license for making a claim of a scientific finding leads to considerable distortion of the scientific process (according to the American Statistical Association). No warranty is given about the accuracy of the copy. However, users may print, download, or email articles for individual use. Copyright of Statistical Papers is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission.An empirical application to Bitcoin returns shows that taking into account the data-dredging bias, which is incurred by looking at the data, can lead to different test decisions. We also show that eye-balling a stretch of historical data for possible changes in a parameter does not invalidate the subsequent procedure that monitors for structural change in new incoming observations. In this paper, we formalize the eye-balling procedure and theoretically derive the implied size distortion of the structural break test. This, however, can distort the result of a structural break test for that parameter, because the data themselves suggested the hypothesis. Without any a priori knowledge of the type of breaks to expect, eye-balling the data can indicate changes in some parameter, e.g., the mean. Abstract: Structural break tests are often applied as a pre-step to ensure the validity of subsequent statistical analyses.
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