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    Analysts’ annual earnings forecasts and changes to the I/B/E/S database

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    Name:
    2020 1-03 CHWY.pdf
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    Description:
    Final Accepted Manuscript
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    Author
    Call, Andrew C.
    Hewitt, Max
    Watkins, Jessica
    Yohn, Teri Lombardi
    Affiliation
    Univ Arizona
    Issue Date
    2020-09-16
    Keywords
    I/B/E/S
    Analysts
    Earnings forecasts
    Consensus
    Market expectations
    
    Metadata
    Show full item record
    Publisher
    SPRINGER
    Citation
    Call, A.C., Hewitt, M., Watkins, J. et al. Analysts’ annual earnings forecasts and changes to the I/B/E/S database. Rev Account Stud (2020). https://doi.org/10.1007/s11142-020-09560-x
    Journal
    REVIEW OF ACCOUNTING STUDIES
    Rights
    Copyright © Springer Science+Business Media, LLC, part of Springer Nature 2020.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    I/B/E/S is a common source of analyst earnings forecast data, and the reliability of these data is important for practice and academic research. Examining a common sample period, we compare annual earnings forecasts across two versions of the I/B/E/S detail file, one made available in 2009 and the other made available in 2015. We find substantial differences in the contents of these two versions of the detail file as well as significant differences in the attributes of the earnings forecasts available in each version. Specifically, the earnings forecasts in the more recent version are more accurate and less biased, and they identify substantially different firms as meeting or just beating analysts' expectations than those in the older version. To highlight the potential impact of these differences, we show that the economic magnitude of the effects of analyst experience and brokerage size on earnings forecast accuracy change by over 30% when we use the more recent version. Additional analyses suggest that the differences across versions of the detail file are ongoing. In contrast, we find that different versions of the summary file exhibit only minor differences over time. We also find significant differences in the properties of consensus earnings forecasts calculated from the individual earnings forecasts available in the detail file and consensus earnings estimates from the summary file. Finally, we provide guidance to researchers using I/B/E/S for analyst earnings forecast data.
    Note
    12 month embargo; published 16 September 2020
    ISSN
    1380-6653
    EISSN
    1573-7136
    DOI
    10.1007/s11142-020-09560-x
    Version
    Final accepted manuscript
    ae974a485f413a2113503eed53cd6c53
    10.1007/s11142-020-09560-x
    Scopus Count
    Collections
    UA Faculty Publications

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